diff --git a/README.md b/README.md index 767ba1fb2796234374f380bf3d14e29d5430daa9..84a9a8a43454617d7cfa086836fbd61a3d4a4a01 100644 --- a/README.md +++ b/README.md @@ -35,7 +35,7 @@ PaddleSeg是基于[PaddlePaddle](https://www.paddlepaddle.org.cn)开发的端到 - **高性能** -PaddleSeg支持多进程I/O、多卡并行、跨卡Batch Norm同步等训练加速策略，结合飞桨核心框架的显存优化功能，可大幅度减少分割模型的显存开销，让开发者更低成本、更高效地完成图像分割训练。 +PaddleSeg支持多进程I/O、多卡并行等训练加速策略，结合飞桨核心框架的显存优化功能，可大幅度减少分割模型的显存开销，让开发者更低成本、更高效地完成图像分割训练。 - **工业级部署** diff --git a/contrib/ACE2P/__init__.py b/contrib/ACE2P/__init__.py index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0e7c9f39543584630fdaedf13d2879a663a789f0 100644 --- a/contrib/ACE2P/__init__.py +++ b/contrib/ACE2P/__init__.py @@ -0,0 +1,14 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/contrib/ACE2P/config.py b/contrib/ACE2P/config.py index a1fad0ec1e6c50493a0a8dfab0c5301add410ad0..68aeca024359b74d8c0adc675f7e19efdf6c4fc4 100644 --- a/contrib/ACE2P/config.py +++ b/contrib/ACE2P/config.py @@ -1,4 +1,18 @@ -# -*- coding: utf-8 -*- +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from utils.util import AttrDict, merge_cfg_from_args, get_arguments import os @@ -19,10 +33,10 @@ cfg.class_num = 20 # 均值, 图像预处理减去的均值 cfg.MEAN = 0.406, 0.456, 0.485 # 标准差，图像预处理除以标准差 -cfg.STD = 0.225, 0.224, 0.229 +cfg.STD = 0.225, 0.224, 0.229 # 多尺度预测时图像尺寸 -cfg.multi_scales = (377,377), (473,473), (567,567) +cfg.multi_scales = (377, 377), (473, 473), (567, 567) # 多尺度预测时图像是否水平翻转 cfg.flip = True diff --git a/contrib/ACE2P/download_ACE2P.py b/contrib/ACE2P/download_ACE2P.py index bb4d33771dbd879a2d77664d2e0e45ed33b9bcb2..419e93d4ab2c977c4425d7fa7d8a5a3c78533236 100644 --- a/contrib/ACE2P/download_ACE2P.py +++ b/contrib/ACE2P/download_ACE2P.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/ACE2P/infer.py b/contrib/ACE2P/infer.py index 16eddc1eab8628eec7e38d27b1f18df13dd480d7..838140e37f23a108ddb37af16286375b164211dc 100644 --- a/contrib/ACE2P/infer.py +++ b/contrib/ACE2P/infer.py @@ -1,4 +1,18 @@ -# -*- coding: utf-8 -*- +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import os import cv2 import numpy as np @@ -12,18 +26,19 @@ config = importlib.import_module('config') cfg = getattr(config, 'cfg') # paddle垃圾回收策略FLAG，ACE2P模型较大，当显存不够时建议开启 -os.environ['FLAGS_eager_delete_tensor_gb']='0.0' +os.environ['FLAGS_eager_delete_tensor_gb'] = '0.0' import paddle.fluid as fluid + # 预测数据集类 class TestDataSet(): def __init__(self): - self.data_dir = cfg.data_dir + self.data_dir = cfg.data_dir self.data_list_file = cfg.data_list_file self.data_list = self.get_data_list() self.data_num = len(self.data_list) - + def get_data_list(self): # 获取预测图像路径列表 data_list = [] @@ -56,10 +71,10 @@ class TestDataSet(): img_path = self.data_list[index] img = cv2.imread(img_path, cv2.IMREAD_COLOR) if img is None: - return img, img,img_path, None + return img, img, img_path, None img_name = img_path.split(os.sep)[-1] - name_prefix = img_name.replace('.'+img_name.split('.')[-1],'') + name_prefix = img_name.replace('.' + img_name.split('.')[-1], '') img_shape = img.shape[:2] img_process = self.preprocess(img) @@ -90,39 +105,44 @@ def infer(): if image is None: print(im_name, 'is None') continue - + # 预测 if cfg.example == 'ACE2P': # ACE2P模型使用多尺度预测 reader = importlib.import_module('reader') multi_scale_test = getattr(reader, 'multi_scale_test') - parsing, logits = multi_scale_test(exe, test_prog, feed_name, fetch_list, image, im_shape) + parsing, logits = multi_scale_test(exe, test_prog, feed_name, + fetch_list, image, im_shape) else: # HumanSeg,RoadLine模型单尺度预测 - result = exe.run(program=test_prog, feed={feed_name[0]: image}, fetch_list=fetch_list) + result = exe.run( + program=test_prog, + feed={feed_name[0]: image}, + fetch_list=fetch_list) parsing = np.argmax(result[0][0], axis=0) parsing = cv2.resize(parsing.astype(np.uint8), im_shape[::-1]) - + # 预测结果保存 result_path = os.path.join(cfg.vis_dir, im_name + '.png') if cfg.example == 'HumanSeg': - logits = result[0][0][1]*255 + logits = result[0][0][1] * 255 logits = cv2.resize(logits, im_shape[::-1]) ret, logits = cv2.threshold(logits, thresh, 0, cv2.THRESH_TOZERO) - logits = 255 *(logits - thresh)/(255 - thresh) + logits = 255 * (logits - thresh) / (255 - thresh) # 将分割结果添加到alpha通道 - rgba = np.concatenate((ori_img, np.expand_dims(logits, axis=2)), axis=2) + rgba = np.concatenate((ori_img, np.expand_dims(logits, axis=2)), + axis=2) cv2.imwrite(result_path, rgba) - else: + else: output_im = PILImage.fromarray(np.asarray(parsing, dtype=np.uint8)) output_im.putpalette(palette) output_im.save(result_path) if (idx + 1) % 100 == 0: print('%d processd' % (idx + 1)) - - print('%d processd done' % (idx + 1)) - + + print('%d processd done' % (idx + 1)) + return 0 diff --git a/contrib/ACE2P/reader.py b/contrib/ACE2P/reader.py index ef5cc370738daf8550adfc20c227f942f1dd300f..892f45ad25846a7c676857b385e1ff65a1409bbe 100644 --- a/contrib/ACE2P/reader.py +++ b/contrib/ACE2P/reader.py @@ -1,9 +1,24 @@ -# -*- coding: utf-8 -*- +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import numpy as np import paddle.fluid as fluid from config import cfg import cv2 + def get_affine_points(src_shape, dst_shape, rot_grad=0): # 获取图像和仿射后图像的三组对应点坐标 # 三组点为仿射变换后图像的中心点, [w/2,0], [0,0]，及对应原始图像的点 @@ -23,7 +38,7 @@ def get_affine_points(src_shape, dst_shape, rot_grad=0): # 原始图像三组点 points = [[0, 0]] * 3 - points[0] = (np.array([w, h]) - 1) * 0.5 + points[0] = (np.array([w, h]) - 1) * 0.5 points[1] = points[0] + 0.5 * affine_shape[0] * np.array([sin_v, -cos_v]) points[2] = points[1] - 0.5 * affine_shape[1] * np.array([cos_v, sin_v]) @@ -34,6 +49,7 @@ def get_affine_points(src_shape, dst_shape, rot_grad=0): return points, points_trans + def preprocess(im): # ACE2P模型数据预处理 im_shape = im.shape[:2] @@ -42,13 +58,10 @@ def preprocess(im): # 获取图像和仿射变换后图像的对应点坐标 points, points_trans = get_affine_points(im_shape, scale) # 根据对应点集获得仿射矩阵 - trans = cv2.getAffineTransform(np.float32(points), - np.float32(points_trans)) + trans = cv2.getAffineTransform( + np.float32(points), np.float32(points_trans)) # 根据仿射矩阵对图像进行仿射 - input = cv2.warpAffine(im, - trans, - scale[::-1], - flags=cv2.INTER_LINEAR) + input = cv2.warpAffine(im, trans, scale[::-1], flags=cv2.INTER_LINEAR) # 减均值测，除以方差，转换数据格式为NCHW input = input.astype(np.float32) @@ -66,19 +79,20 @@ def preprocess(im): return input_images -def multi_scale_test(exe, test_prog, feed_name, fetch_list, - input_ims, im_shape): - +def multi_scale_test(exe, test_prog, feed_name, fetch_list, input_ims, + im_shape): + # 由于部分类别分左右部位, flipped_idx为其水平翻转后对应的标签 flipped_idx = (15, 14, 17, 16, 19, 18) ms_outputs = [] - + # 多尺度预测 for idx, scale in enumerate(cfg.multi_scales): input_im = input_ims[idx] - parsing_output = exe.run(program=test_prog, - feed={feed_name[0]: input_im}, - fetch_list=fetch_list) + parsing_output = exe.run( + program=test_prog, + feed={feed_name[0]: input_im}, + fetch_list=fetch_list) output = parsing_output[0][0] if cfg.flip: # 若水平翻转，对部分类别进行翻转，与原始预测结果取均值 @@ -92,7 +106,8 @@ def multi_scale_test(exe, test_prog, feed_name, fetch_list, # 仿射变换回图像原始尺寸 points, points_trans = get_affine_points(im_shape, scale) M = cv2.getAffineTransform(np.float32(points_trans), np.float32(points)) - logits_result = cv2.warpAffine(output, M, im_shape[::-1], flags=cv2.INTER_LINEAR) + logits_result = cv2.warpAffine( + output, M, im_shape[::-1], flags=cv2.INTER_LINEAR) ms_outputs.append(logits_result) # 多尺度预测结果求均值，求预测概率最大的类别 @@ -100,4 +115,3 @@ def multi_scale_test(exe, test_prog, feed_name, fetch_list, ms_fused_parsing_output = np.mean(ms_fused_parsing_output, axis=0) parsing = np.argmax(ms_fused_parsing_output, axis=2) return parsing, ms_fused_parsing_output - diff --git a/contrib/ACE2P/utils/__init__.py b/contrib/ACE2P/utils/__init__.py index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0e7c9f39543584630fdaedf13d2879a663a789f0 100644 --- a/contrib/ACE2P/utils/__init__.py +++ b/contrib/ACE2P/utils/__init__.py @@ -0,0 +1,14 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/contrib/ACE2P/utils/palette.py b/contrib/ACE2P/utils/palette.py index 2186203cbc2789f6eff70dfd92f724b4fe16cdb7..f7f15441b2e2f80b332bb865c559243d9175e040 100644 --- a/contrib/ACE2P/utils/palette.py +++ b/contrib/ACE2P/utils/palette.py @@ -7,6 +7,7 @@ ## This source code is licensed under the MIT-style license found in the ## LICENSE file in the root directory of this source tree ##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + from __future__ import absolute_import from __future__ import division from __future__ import print_function diff --git a/contrib/ACE2P/utils/util.py b/contrib/ACE2P/utils/util.py index 7394870e7c94c1fb16169e314696b931eecdc3b2..955eb02b63298d0d36ebd23a92cec06b00a34a58 100644 --- a/contrib/ACE2P/utils/util.py +++ b/contrib/ACE2P/utils/util.py @@ -1,18 +1,32 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from __future__ import division from __future__ import print_function from __future__ import unicode_literals import argparse import os + def get_arguments(): parser = argparse.ArgumentParser() - parser.add_argument("--use_gpu", - action="store_true", - help="Use gpu or cpu to test.") - parser.add_argument('--example', - type=str, - help='RoadLine, HumanSeg or ACE2P') - + parser.add_argument( + "--use_gpu", action="store_true", help="Use gpu or cpu to test.") + parser.add_argument( + '--example', type=str, help='RoadLine, HumanSeg or ACE2P') + return parser.parse_args() @@ -34,6 +48,7 @@ class AttrDict(dict): else: self[name] = value + def merge_cfg_from_args(args, cfg): """Merge config keys, values in args into the global config.""" for k, v in vars(args).items(): @@ -44,4 +59,3 @@ def merge_cfg_from_args(args, cfg): value = v if value is not None: cfg[k] = value - diff --git a/contrib/HumanSeg/datasets/__init__.py b/contrib/HumanSeg/datasets/__init__.py index 81d3255640a0353943cdc9e968f17e3ea765b390..77dae995267f45ed2551b38ee6b1daf396fc0b8a 100644 --- a/contrib/HumanSeg/datasets/__init__.py +++ b/contrib/HumanSeg/datasets/__init__.py @@ -1,10 +1,11 @@ -# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/HumanSeg/datasets/dataset.py b/contrib/HumanSeg/datasets/dataset.py index 263c7af471444c49966c56f72000838a7c55c41e..07bfdebd4ac106c0c8e28726590d3ec3aeb148a8 100644 --- a/contrib/HumanSeg/datasets/dataset.py +++ b/contrib/HumanSeg/datasets/dataset.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/datasets/shared_queue/__init__.py b/contrib/HumanSeg/datasets/shared_queue/__init__.py index f4c3990e67d6ade96d20abd1aa34b34b1ff891cb..1662f739d491243a56d1cc70c13b7a91dbb46a7e 100644 --- a/contrib/HumanSeg/datasets/shared_queue/__init__.py +++ b/contrib/HumanSeg/datasets/shared_queue/__init__.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/datasets/shared_queue/queue.py b/contrib/HumanSeg/datasets/shared_queue/queue.py index 157df0a51ee3d552c810bafe5e826c1072c75649..7a67f98de700e74e0361ae80cfe983c594f88024 100644 --- a/contrib/HumanSeg/datasets/shared_queue/queue.py +++ b/contrib/HumanSeg/datasets/shared_queue/queue.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/datasets/shared_queue/sharedmemory.py b/contrib/HumanSeg/datasets/shared_queue/sharedmemory.py index 451faa2911185fe279627dfac76b89aa24c5c706..8df13752194575628d173ac6c96d40ae404590b5 100644 --- a/contrib/HumanSeg/datasets/shared_queue/sharedmemory.py +++ b/contrib/HumanSeg/datasets/shared_queue/sharedmemory.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -12,9 +13,6 @@ # See the License for the specific language governing permissions and # limitations under the License. -# utils for memory management which is allocated on sharedmemory, -# note that these structures may not be thread-safe - from __future__ import absolute_import from __future__ import division from __future__ import print_function diff --git a/contrib/HumanSeg/export.py b/contrib/HumanSeg/export.py index 6fcae141398a6718db5710d595d95842b1596753..c6444bb298cbf91fe980d6a57b8c92da30d8db5b 100644 --- a/contrib/HumanSeg/export.py +++ b/contrib/HumanSeg/export.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import models import argparse diff --git a/contrib/HumanSeg/infer.py b/contrib/HumanSeg/infer.py index 96aabac6c44c164504f6626accfadd36983219e5..dbb3038236416a43762decaa275b009f6daa5de0 100644 --- a/contrib/HumanSeg/infer.py +++ b/contrib/HumanSeg/infer.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import argparse import os import os.path as osp diff --git a/contrib/HumanSeg/models/__init__.py b/contrib/HumanSeg/models/__init__.py index 02704a07cc4a476253f80a8defbc42929f4175ad..f2fac79c41805e3207b4555b29a8ae3965e278c9 100644 --- a/contrib/HumanSeg/models/__init__.py +++ b/contrib/HumanSeg/models/__init__.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from .humanseg import HumanSegMobile from .humanseg import HumanSegServer from .humanseg import HumanSegLite diff --git a/contrib/HumanSeg/models/humanseg.py b/contrib/HumanSeg/models/humanseg.py index a3653f0489bc9a76e764e3af513fc8cb3306696b..60e89bde8b44130e286c127ef334e81ecba2133a 100644 --- a/contrib/HumanSeg/models/humanseg.py +++ b/contrib/HumanSeg/models/humanseg.py @@ -1,10 +1,11 @@ -# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/HumanSeg/models/load_model.py b/contrib/HumanSeg/models/load_model.py index 9d0786363863040fb3aa9e24a90963dd9e89fdaa..dadaa2b5c679b3d8e9c404b16fa0b613ba863729 100644 --- a/contrib/HumanSeg/models/load_model.py +++ b/contrib/HumanSeg/models/load_model.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/nets/__init__.py b/contrib/HumanSeg/nets/__init__.py index cab1682745084e736992e4aa5e555db6bc1d5c53..cb0cc37b82aec2dd8172b317a12063c45c573c16 100644 --- a/contrib/HumanSeg/nets/__init__.py +++ b/contrib/HumanSeg/nets/__init__.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from .backbone import mobilenet_v2 from .backbone import xception from .deeplabv3p import DeepLabv3p diff --git a/contrib/HumanSeg/nets/backbone/__init__.py b/contrib/HumanSeg/nets/backbone/__init__.py index 18f39d40802011843007ae7c6ca9cf4fb64aa789..338ee31482178cf8d1cdfda740fd571eac1e1141 100644 --- a/contrib/HumanSeg/nets/backbone/__init__.py +++ b/contrib/HumanSeg/nets/backbone/__init__.py @@ -1,2 +1,17 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from .mobilenet_v2 import MobileNetV2 from .xception import Xception diff --git a/contrib/HumanSeg/nets/backbone/mobilenet_v2.py b/contrib/HumanSeg/nets/backbone/mobilenet_v2.py index 845d5a3f6b997e2c323e577275670bdfc5193530..3e95026196366622ec6170286aeffd762be3c678 100644 --- a/contrib/HumanSeg/nets/backbone/mobilenet_v2.py +++ b/contrib/HumanSeg/nets/backbone/mobilenet_v2.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -10,6 +11,7 @@ # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and +# limitations under the License. from __future__ import absolute_import from __future__ import division diff --git a/contrib/HumanSeg/nets/backbone/xception.py b/contrib/HumanSeg/nets/backbone/xception.py index ad5c3821933e6ed10d7e5bbce810cc14b579a7b2..00a734eb814d8c83cfe77082bfe47a6899352841 100644 --- a/contrib/HumanSeg/nets/backbone/xception.py +++ b/contrib/HumanSeg/nets/backbone/xception.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/nets/deeplabv3p.py b/contrib/HumanSeg/nets/deeplabv3p.py index fb363c8ca1934c5276556b51f9a3d3a3e537b781..d076c808db7bf89f64f26a86d282e4cb7e8b58fb 100644 --- a/contrib/HumanSeg/nets/deeplabv3p.py +++ b/contrib/HumanSeg/nets/deeplabv3p.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/nets/hrnet.py b/contrib/HumanSeg/nets/hrnet.py index 13b8b9012e5c5cba7f92ff05c8f2ba22bc7f06bd..52e4949b9d70c04d83fa34d0504b5492c6b7f8d7 100644 --- a/contrib/HumanSeg/nets/hrnet.py +++ b/contrib/HumanSeg/nets/hrnet.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/nets/libs.py b/contrib/HumanSeg/nets/libs.py index 01fdad2cec6ce4b13cea2b7c957fb648edb4aeb2..f74c93fc3f4203663c1f8844aa8b87716d8ecd91 100644 --- a/contrib/HumanSeg/nets/libs.py +++ b/contrib/HumanSeg/nets/libs.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/nets/seg_modules.py b/contrib/HumanSeg/nets/seg_modules.py index 902c903fcc426e68de483ee249af16d21788a86c..a0794474a89a9a0ecf9befcc69c06ba4dee3b178 100644 --- a/contrib/HumanSeg/nets/seg_modules.py +++ b/contrib/HumanSeg/nets/seg_modules.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/nets/shufflenet_slim.py b/contrib/HumanSeg/nets/shufflenet_slim.py index dee6d1401844b1a30a869e0b54a8ac6aeb70140b..4ac7dc0076c0ea59371ce7a256fb0f3ed7f5c815 100644 --- a/contrib/HumanSeg/nets/shufflenet_slim.py +++ b/contrib/HumanSeg/nets/shufflenet_slim.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from __future__ import absolute_import from __future__ import division from __future__ import print_function diff --git a/contrib/HumanSeg/pretrained_weights/download_pretrained_weights.py b/contrib/HumanSeg/pretrained_weights/download_pretrained_weights.py index e573df05f94f5a612ef6c2f5a2eb2c9cd55cc2f1..0b74c5ebf42adb96673f48910258dfcaec756df6 100644 --- a/contrib/HumanSeg/pretrained_weights/download_pretrained_weights.py +++ b/contrib/HumanSeg/pretrained_weights/download_pretrained_weights.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/HumanSeg/quant_offline.py b/contrib/HumanSeg/quant_offline.py index 92a393f07bd2b70fc7df658290abf440f3069752..163b770680e609d9ee52d0a9426b7f3d94b25845 100644 --- a/contrib/HumanSeg/quant_offline.py +++ b/contrib/HumanSeg/quant_offline.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import argparse from datasets.dataset import Dataset import transforms diff --git a/contrib/HumanSeg/quant_online.py b/contrib/HumanSeg/quant_online.py index 04eea4d3d9f357897e300da87297a8f6c9515e06..2bf605185637f4de58db135738b0a00db3f6d670 100644 --- a/contrib/HumanSeg/quant_online.py +++ b/contrib/HumanSeg/quant_online.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import argparse from datasets.dataset import Dataset from models import HumanSegMobile, HumanSegLite, HumanSegServer diff --git a/contrib/HumanSeg/train.py b/contrib/HumanSeg/train.py index 01e3c7034d1602a434d99f94310e85fb7f902bbf..3f5f89f3dcc3ca11272e98f5ef91604e5bc15fea 100644 --- a/contrib/HumanSeg/train.py +++ b/contrib/HumanSeg/train.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import argparse from datasets.dataset import Dataset from models import HumanSegMobile, HumanSegLite, HumanSegServer diff --git a/contrib/HumanSeg/transforms/__init__.py b/contrib/HumanSeg/transforms/__init__.py index db17cedcac20183456e79121565b35ddaae82e1c..b537d3216c5b72c75bf3e201304d20638f3ea706 100644 --- a/contrib/HumanSeg/transforms/__init__.py +++ b/contrib/HumanSeg/transforms/__init__.py @@ -1,10 +1,11 @@ -# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/HumanSeg/transforms/functional.py b/contrib/HumanSeg/transforms/functional.py index a446f9097043b9447a4b6eeda0906bea6ebeb625..c3f0265b0e1f4a250b41d5b86717b3d87797351d 100644 --- a/contrib/HumanSeg/transforms/functional.py +++ b/contrib/HumanSeg/transforms/functional.py @@ -1,10 +1,11 @@ -# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/HumanSeg/transforms/transforms.py b/contrib/HumanSeg/transforms/transforms.py index f19359b24819ef7a91b78bc1058a308a7f48735e..261b29781f59ca211f66b240937952b51af5949f 100644 --- a/contrib/HumanSeg/transforms/transforms.py +++ b/contrib/HumanSeg/transforms/transforms.py @@ -1,10 +1,11 @@ -# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/HumanSeg/utils/__init__.py b/contrib/HumanSeg/utils/__init__.py index a7760ee48accc71122d07a35f6287117313ac51e..d196c743e86c1742cb8d0aa5d466f02f0517a639 100644 --- a/contrib/HumanSeg/utils/__init__.py +++ b/contrib/HumanSeg/utils/__init__.py @@ -1,10 +1,11 @@ -# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/HumanSeg/utils/humanseg_postprocess.py b/contrib/HumanSeg/utils/humanseg_postprocess.py index 44376726703c4f533f7fa3888c4dd694b19ff031..d4624541a74bfd6ec4e99dda225096f975f75ee6 100644 --- a/contrib/HumanSeg/utils/humanseg_postprocess.py +++ b/contrib/HumanSeg/utils/humanseg_postprocess.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import numpy as np import cv2 import os diff --git a/contrib/HumanSeg/utils/logging.py b/contrib/HumanSeg/utils/logging.py index 1669466f839b6953aa368dedc80e32a9a68725f7..6f0c25ff554cb80b9435e72ed47432d4bb6e6813 100644 --- a/contrib/HumanSeg/utils/logging.py +++ b/contrib/HumanSeg/utils/logging.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/utils/metrics.py b/contrib/HumanSeg/utils/metrics.py index 2898be028f3dfa03ad9892310da89f7695829542..f7bab020ab44131f5d46643cf0522dd6acf483ee 100644 --- a/contrib/HumanSeg/utils/metrics.py +++ b/contrib/HumanSeg/utils/metrics.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/utils/post_quantization.py b/contrib/HumanSeg/utils/post_quantization.py index f6d040e97deb561017eccbbaf0ce1d1ff587a65e..6adb060920484a6f38924c51efc3ba4a3cee8f7d 100644 --- a/contrib/HumanSeg/utils/post_quantization.py +++ b/contrib/HumanSeg/utils/post_quantization.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/HumanSeg/utils/utils.py b/contrib/HumanSeg/utils/utils.py index 0e09e8b232bfc1d7436ab94a391175446c8e12be..435374aea27e57db16fee13522cb09d68d40fbec 100644 --- a/contrib/HumanSeg/utils/utils.py +++ b/contrib/HumanSeg/utils/utils.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -205,11 +206,9 @@ def load_pretrained_weights(exe, main_prog, weights_dir, fuse_bn=False): vars_to_load.append(var) logging.debug("Weight {} will be load".format(var.name)) - fluid.io.load_vars( - executor=exe, - dirname=weights_dir, - main_program=main_prog, - vars=vars_to_load) + params_dict = fluid.io.load_program_state( + weights_dir, var_list=vars_to_load) + fluid.io.set_program_state(main_prog, params_dict) if len(vars_to_load) == 0: logging.warning( "There is no pretrain weights loaded, maybe you should check you pretrain model!" diff --git a/contrib/HumanSeg/val.py b/contrib/HumanSeg/val.py index cecdb5d5c579b22688a092d700863737ec35a13d..e671879f5f67eb14bf22684b93fe79718b9c22cd 100644 --- a/contrib/HumanSeg/val.py +++ b/contrib/HumanSeg/val.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import argparse from datasets.dataset import Dataset import transforms diff --git a/contrib/HumanSeg/video_infer.py b/contrib/HumanSeg/video_infer.py index b248669cf9455e908d2c8dfb98f8edae273f73a9..f37809366d06ee4553bb10d848b3e387a18797bd 100644 --- a/contrib/HumanSeg/video_infer.py +++ b/contrib/HumanSeg/video_infer.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import argparse import os import os.path as osp diff --git a/contrib/LaneNet/data_aug.py b/contrib/LaneNet/data_aug.py index bffb956c657e8d93edcffe5c7946e3b1437a1ef1..13f8dbfd72c63a0d5891bcf0b83f8ee761fe79ee 100644 --- a/contrib/LaneNet/data_aug.py +++ b/contrib/LaneNet/data_aug.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -21,6 +21,7 @@ from models.model_builder import ModelPhase from pdseg.data_aug import get_random_scale, randomly_scale_image_and_label, random_rotation, \ rand_scale_aspect, hsv_color_jitter, rand_crop + def resize(img, grt=None, grt_instance=None, mode=ModelPhase.TRAIN): """ 改变图像及标签图像尺寸 @@ -44,7 +45,8 @@ def resize(img, grt=None, grt_instance=None, mode=ModelPhase.TRAIN): if grt is not None: grt = cv2.resize(grt, target_size, interpolation=cv2.INTER_NEAREST) if grt_instance is not None: - grt_instance = cv2.resize(grt_instance, target_size, interpolation=cv2.INTER_NEAREST) + grt_instance = cv2.resize( + grt_instance, target_size, interpolation=cv2.INTER_NEAREST) elif cfg.AUG.AUG_METHOD == 'stepscaling': if mode == ModelPhase.TRAIN: min_scale_factor = cfg.AUG.MIN_SCALE_FACTOR diff --git a/contrib/LaneNet/dataset/download_tusimple.py b/contrib/LaneNet/dataset/download_tusimple.py index 1549cafdea4bbc97aca0401d84cd8844165324c8..1f082f3876b62274c9d128ca7b4be874a2666f50 100644 --- a/contrib/LaneNet/dataset/download_tusimple.py +++ b/contrib/LaneNet/dataset/download_tusimple.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/LaneNet/eval.py b/contrib/LaneNet/eval.py index 025fb4e7284adefdafa4365ace347a68e2addf48..e08d371f64f981cb1f22e166df53555f5166a562 100644 --- a/contrib/LaneNet/eval.py +++ b/contrib/LaneNet/eval.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -122,7 +122,10 @@ def evaluate(cfg, ckpt_dir=None, use_gpu=False, use_mpio=False, **kwargs): if ckpt_dir is not None: print('load test model:', ckpt_dir) - fluid.io.load_params(exe, ckpt_dir, main_program=test_prog) + try: + fluid.load(test_prog, os.path.join(ckpt_dir, 'model'), exe) + except: + fluid.io.load_params(exe, ckpt_dir, main_program=test_prog) # Use streaming confusion matrix to calculate mean_iou np.set_printoptions( diff --git a/contrib/LaneNet/loss.py b/contrib/LaneNet/loss.py index e7aa1a4ddf14ea57833b696cb9965411b666e8ae..3c97dcb7de659aa3b642af6b9451210f33f863ab 100644 --- a/contrib/LaneNet/loss.py +++ b/contrib/LaneNet/loss.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/LaneNet/models/__init__.py b/contrib/LaneNet/models/__init__.py index f750f6f7b42bb028f81a24edb2bb9e30c190578e..6a2095cef46e9744bc9db469c7f9e5deb711ec42 100644 --- a/contrib/LaneNet/models/__init__.py +++ b/contrib/LaneNet/models/__init__.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/LaneNet/models/model_builder.py b/contrib/LaneNet/models/model_builder.py index b274e95a7b761f0345923c7702f91420a2469404..03548efbe7d34828feeacb6deadc09fcf378e387 100644 --- a/contrib/LaneNet/models/model_builder.py +++ b/contrib/LaneNet/models/model_builder.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/LaneNet/models/modeling/lanenet.py b/contrib/LaneNet/models/modeling/lanenet.py index 68837983f08ce4220bfb5bb0ea7d96404687b259..b9365125f1a4a4a7e591aa4ba739a76c0ef136e6 100644 --- a/contrib/LaneNet/models/modeling/lanenet.py +++ b/contrib/LaneNet/models/modeling/lanenet.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -18,7 +18,6 @@ from __future__ import print_function import paddle.fluid as fluid - from utils.config import cfg from pdseg.models.libs.model_libs import scope, name_scope from pdseg.models.libs.model_libs import bn, bn_relu, relu @@ -86,7 +85,12 @@ def bottleneck(inputs, with scope('down_sample'): inputs_shape = inputs.shape with scope('main_max_pool'): - net_main = fluid.layers.conv2d(inputs, inputs_shape[1], filter_size=3, stride=2, padding='SAME') + net_main = fluid.layers.conv2d( + inputs, + inputs_shape[1], + filter_size=3, + stride=2, + padding='SAME') #First get the difference in depth to pad, then pad with zeros only on the last dimension. depth_to_pad = abs(inputs_shape[1] - output_depth) @@ -95,12 +99,16 @@ def bottleneck(inputs, net_main = fluid.layers.pad(net_main, paddings=paddings) with scope('block1'): - net = conv(inputs, reduced_depth, [2, 2], stride=2, padding='same') + net = conv( + inputs, reduced_depth, [2, 2], stride=2, padding='same') net = bn(net) net = prelu(net, decoder=decoder) with scope('block2'): - net = conv(net, reduced_depth, [filter_size, filter_size], padding='same') + net = conv( + net, + reduced_depth, [filter_size, filter_size], + padding='same') net = bn(net) net = prelu(net, decoder=decoder) @@ -137,13 +145,18 @@ def bottleneck(inputs, # Second conv block --- apply dilated convolution here with scope('block2'): - net = conv(net, reduced_depth, filter_size, padding='SAME', dilation=dilation_rate) + net = conv( + net, + reduced_depth, + filter_size, + padding='SAME', + dilation=dilation_rate) net = bn(net) net = prelu(net, decoder=decoder) # Final projection with 1x1 kernel (Expansion) with scope('block3'): - net = conv(net, output_depth, [1,1]) + net = conv(net, output_depth, [1, 1]) net = bn(net) net = prelu(net, decoder=decoder) @@ -172,9 +185,11 @@ def bottleneck(inputs, # Second conv block --- apply asymmetric conv here with scope('block2'): with scope('asymmetric_conv2a'): - net = conv(net, reduced_depth, [filter_size, 1], padding='same') + net = conv( + net, reduced_depth, [filter_size, 1], padding='same') with scope('asymmetric_conv2b'): - net = conv(net, reduced_depth, [1, filter_size], padding='same') + net = conv( + net, reduced_depth, [1, filter_size], padding='same') net = bn(net) net = prelu(net, decoder=decoder) @@ -211,7 +226,8 @@ def bottleneck(inputs, with scope('unpool'): net_unpool = conv(inputs, output_depth, [1, 1]) net_unpool = bn(net_unpool) - net_unpool = fluid.layers.resize_bilinear(net_unpool, out_shape=output_shape[2:]) + net_unpool = fluid.layers.resize_bilinear( + net_unpool, out_shape=output_shape[2:]) # First 1x1 projection to reduce depth with scope('block1'): @@ -220,7 +236,12 @@ def bottleneck(inputs, net = prelu(net, decoder=decoder) with scope('block2'): - net = deconv(net, reduced_depth, filter_size=filter_size, stride=2, padding='same') + net = deconv( + net, + reduced_depth, + filter_size=filter_size, + stride=2, + padding='same') net = bn(net) net = prelu(net, decoder=decoder) @@ -253,7 +274,10 @@ def bottleneck(inputs, # Second conv block with scope('block2'): - net = conv(net, reduced_depth, [filter_size, filter_size], padding='same') + net = conv( + net, + reduced_depth, [filter_size, filter_size], + padding='same') net = bn(net) net = prelu(net, decoder=decoder) @@ -281,17 +305,33 @@ def ENet_stage1(inputs, name_scope='stage1_block'): = bottleneck(inputs, output_depth=64, filter_size=3, regularizer_prob=0.01, type=DOWNSAMPLING, name_scope='bottleneck1_0') with scope('bottleneck1_1'): - net = bottleneck(net, output_depth=64, filter_size=3, regularizer_prob=0.01, - name_scope='bottleneck1_1') + net = bottleneck( + net, + output_depth=64, + filter_size=3, + regularizer_prob=0.01, + name_scope='bottleneck1_1') with scope('bottleneck1_2'): - net = bottleneck(net, output_depth=64, filter_size=3, regularizer_prob=0.01, - name_scope='bottleneck1_2') + net = bottleneck( + net, + output_depth=64, + filter_size=3, + regularizer_prob=0.01, + name_scope='bottleneck1_2') with scope('bottleneck1_3'): - net = bottleneck(net, output_depth=64, filter_size=3, regularizer_prob=0.01, - name_scope='bottleneck1_3') + net = bottleneck( + net, + output_depth=64, + filter_size=3, + regularizer_prob=0.01, + name_scope='bottleneck1_3') with scope('bottleneck1_4'): - net = bottleneck(net, output_depth=64, filter_size=3, regularizer_prob=0.01, - name_scope='bottleneck1_4') + net = bottleneck( + net, + output_depth=64, + filter_size=3, + regularizer_prob=0.01, + name_scope='bottleneck1_4') return net, inputs_shape_1 @@ -302,17 +342,38 @@ def ENet_stage2(inputs, name_scope='stage2_block'): name_scope='bottleneck2_0') for i in range(2): with scope('bottleneck2_{}'.format(str(4 * i + 1))): - net = bottleneck(net, output_depth=128, filter_size=3, regularizer_prob=0.1, - name_scope='bottleneck2_{}'.format(str(4 * i + 1))) + net = bottleneck( + net, + output_depth=128, + filter_size=3, + regularizer_prob=0.1, + name_scope='bottleneck2_{}'.format(str(4 * i + 1))) with scope('bottleneck2_{}'.format(str(4 * i + 2))): - net = bottleneck(net, output_depth=128, filter_size=3, regularizer_prob=0.1, type=DILATED, dilation_rate=(2 ** (2*i+1)), - name_scope='bottleneck2_{}'.format(str(4 * i + 2))) + net = bottleneck( + net, + output_depth=128, + filter_size=3, + regularizer_prob=0.1, + type=DILATED, + dilation_rate=(2**(2 * i + 1)), + name_scope='bottleneck2_{}'.format(str(4 * i + 2))) with scope('bottleneck2_{}'.format(str(4 * i + 3))): - net = bottleneck(net, output_depth=128, filter_size=5, regularizer_prob=0.1, type=ASYMMETRIC, - name_scope='bottleneck2_{}'.format(str(4 * i + 3))) + net = bottleneck( + net, + output_depth=128, + filter_size=5, + regularizer_prob=0.1, + type=ASYMMETRIC, + name_scope='bottleneck2_{}'.format(str(4 * i + 3))) with scope('bottleneck2_{}'.format(str(4 * i + 4))): - net = bottleneck(net, output_depth=128, filter_size=3, regularizer_prob=0.1, type=DILATED, dilation_rate=(2 ** (2*i+2)), - name_scope='bottleneck2_{}'.format(str(4 * i + 4))) + net = bottleneck( + net, + output_depth=128, + filter_size=3, + regularizer_prob=0.1, + type=DILATED, + dilation_rate=(2**(2 * i + 2)), + name_scope='bottleneck2_{}'.format(str(4 * i + 4))) return net, inputs_shape_2 @@ -320,52 +381,106 @@ def ENet_stage3(inputs, name_scope='stage3_block'): with scope(name_scope): for i in range(2): with scope('bottleneck3_{}'.format(str(4 * i + 0))): - net = bottleneck(inputs, output_depth=128, filter_size=3, regularizer_prob=0.1, - name_scope='bottleneck3_{}'.format(str(4 * i + 0))) + net = bottleneck( + inputs, + output_depth=128, + filter_size=3, + regularizer_prob=0.1, + name_scope='bottleneck3_{}'.format(str(4 * i + 0))) with scope('bottleneck3_{}'.format(str(4 * i + 1))): - net = bottleneck(net, output_depth=128, filter_size=3, regularizer_prob=0.1, type=DILATED, dilation_rate=(2 ** (2*i+1)), - name_scope='bottleneck3_{}'.format(str(4 * i + 1))) + net = bottleneck( + net, + output_depth=128, + filter_size=3, + regularizer_prob=0.1, + type=DILATED, + dilation_rate=(2**(2 * i + 1)), + name_scope='bottleneck3_{}'.format(str(4 * i + 1))) with scope('bottleneck3_{}'.format(str(4 * i + 2))): - net = bottleneck(net, output_depth=128, filter_size=5, regularizer_prob=0.1, type=ASYMMETRIC, - name_scope='bottleneck3_{}'.format(str(4 * i + 2))) + net = bottleneck( + net, + output_depth=128, + filter_size=5, + regularizer_prob=0.1, + type=ASYMMETRIC, + name_scope='bottleneck3_{}'.format(str(4 * i + 2))) with scope('bottleneck3_{}'.format(str(4 * i + 3))): - net = bottleneck(net, output_depth=128, filter_size=3, regularizer_prob=0.1, type=DILATED, dilation_rate=(2 ** (2*i+2)), - name_scope='bottleneck3_{}'.format(str(4 * i + 3))) + net = bottleneck( + net, + output_depth=128, + filter_size=3, + regularizer_prob=0.1, + type=DILATED, + dilation_rate=(2**(2 * i + 2)), + name_scope='bottleneck3_{}'.format(str(4 * i + 3))) return net -def ENet_stage4(inputs, inputs_shape, connect_tensor, - skip_connections=True, name_scope='stage4_block'): +def ENet_stage4(inputs, + inputs_shape, + connect_tensor, + skip_connections=True, + name_scope='stage4_block'): with scope(name_scope): with scope('bottleneck4_0'): - net = bottleneck(inputs, output_depth=64, filter_size=3, regularizer_prob=0.1, - type=UPSAMPLING, decoder=True, output_shape=inputs_shape, - name_scope='bottleneck4_0') + net = bottleneck( + inputs, + output_depth=64, + filter_size=3, + regularizer_prob=0.1, + type=UPSAMPLING, + decoder=True, + output_shape=inputs_shape, + name_scope='bottleneck4_0') if skip_connections: net = fluid.layers.elementwise_add(net, connect_tensor) with scope('bottleneck4_1'): - net = bottleneck(net, output_depth=64, filter_size=3, regularizer_prob=0.1, decoder=True, - name_scope='bottleneck4_1') + net = bottleneck( + net, + output_depth=64, + filter_size=3, + regularizer_prob=0.1, + decoder=True, + name_scope='bottleneck4_1') with scope('bottleneck4_2'): - net = bottleneck(net, output_depth=64, filter_size=3, regularizer_prob=0.1, decoder=True, - name_scope='bottleneck4_2') + net = bottleneck( + net, + output_depth=64, + filter_size=3, + regularizer_prob=0.1, + decoder=True, + name_scope='bottleneck4_2') return net -def ENet_stage5(inputs, inputs_shape, connect_tensor, skip_connections=True, +def ENet_stage5(inputs, + inputs_shape, + connect_tensor, + skip_connections=True, name_scope='stage5_block'): with scope(name_scope): - net = bottleneck(inputs, output_depth=16, filter_size=3, regularizer_prob=0.1, type=UPSAMPLING, - decoder=True, output_shape=inputs_shape, - name_scope='bottleneck5_0') + net = bottleneck( + inputs, + output_depth=16, + filter_size=3, + regularizer_prob=0.1, + type=UPSAMPLING, + decoder=True, + output_shape=inputs_shape, + name_scope='bottleneck5_0') if skip_connections: net = fluid.layers.elementwise_add(net, connect_tensor) with scope('bottleneck5_1'): - net = bottleneck(net, output_depth=16, filter_size=3, regularizer_prob=0.1, decoder=True, - name_scope='bottleneck5_1') + net = bottleneck( + net, + output_depth=16, + filter_size=3, + regularizer_prob=0.1, + decoder=True, + name_scope='bottleneck5_1') return net @@ -378,14 +493,16 @@ def decoder(input, num_classes): segStage3 = ENet_stage3(stage2) segStage4 = ENet_stage4(segStage3, inputs_shape_2, stage1) segStage5 = ENet_stage5(segStage4, inputs_shape_1, initial) - segLogits = deconv(segStage5, num_classes, filter_size=2, stride=2, padding='SAME') + segLogits = deconv( + segStage5, num_classes, filter_size=2, stride=2, padding='SAME') # Embedding branch with scope('LaneNetEm'): emStage3 = ENet_stage3(stage2) emStage4 = ENet_stage4(emStage3, inputs_shape_2, stage1) emStage5 = ENet_stage5(emStage4, inputs_shape_1, initial) - emLogits = deconv(emStage5, 4, filter_size=2, stride=2, padding='SAME') + emLogits = deconv( + emStage5, 4, filter_size=2, stride=2, padding='SAME') elif 'vgg' in cfg.MODEL.LANENET.BACKBONE: encoder_list = ['pool5', 'pool4', 'pool3'] @@ -396,14 +513,16 @@ def decoder(input, num_classes): encoder_list = encoder_list[1:] for i in range(len(encoder_list)): with scope('deconv_{:d}'.format(i + 1)): - deconv_out = deconv(score, 64, filter_size=4, stride=2, padding='SAME') + deconv_out = deconv( + score, 64, filter_size=4, stride=2, padding='SAME') input_tensor = input[encoder_list[i]] with scope('score_{:d}'.format(i + 1)): score = conv(input_tensor, 64, 1) score = fluid.layers.elementwise_add(deconv_out, score) with scope('deconv_final'): - emLogits = deconv(score, 64, filter_size=16, stride=8, padding='SAME') + emLogits = deconv( + score, 64, filter_size=16, stride=8, padding='SAME') with scope('score_final'): segLogits = conv(emLogits, num_classes, 1) emLogits = relu(conv(emLogits, 4, 1)) @@ -415,7 +534,8 @@ def encoder(input): model = vgg_backbone(layers=16) #output = model.net(input) - _, encode_feature_dict = model.net(input, end_points=13, decode_points=[7, 10, 13]) + _, encode_feature_dict = model.net( + input, end_points=13, decode_points=[7, 10, 13]) output = {} output['pool3'] = encode_feature_dict[7] output['pool4'] = encode_feature_dict[10] @@ -427,8 +547,9 @@ def encoder(input): stage2, inputs_shape_2 = ENet_stage2(stage1) output = (initial, stage1, stage2, inputs_shape_1, inputs_shape_2) else: - raise Exception("LaneNet expect enet and vgg backbone, but received {}". - format(cfg.MODEL.LANENET.BACKBONE)) + raise Exception( + "LaneNet expect enet and vgg backbone, but received {}".format( + cfg.MODEL.LANENET.BACKBONE)) return output diff --git a/contrib/LaneNet/reader.py b/contrib/LaneNet/reader.py index 29af37b8caf15da8cdabc73a847c30ca88d65c4a..b051c71a1aaac6c7867102b1f6bbd01a74ed72cf 100644 --- a/contrib/LaneNet/reader.py +++ b/contrib/LaneNet/reader.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -58,7 +58,8 @@ class LaneNetDataset(): if self.shuffle and cfg.NUM_TRAINERS > 1: np.random.RandomState(self.shuffle_seed).shuffle(self.all_lines) num_lines = len(self.all_lines) // cfg.NUM_TRAINERS - self.lines = self.all_lines[num_lines * cfg.TRAINER_ID: num_lines * (cfg.TRAINER_ID + 1)] + self.lines = self.all_lines[num_lines * cfg.TRAINER_ID:num_lines * + (cfg.TRAINER_ID + 1)] self.shuffle_seed += 1 elif self.shuffle: np.random.shuffle(self.lines) @@ -86,7 +87,8 @@ class LaneNetDataset(): if self.shuffle and cfg.NUM_TRAINERS > 1: np.random.RandomState(self.shuffle_seed).shuffle(self.all_lines) num_lines = len(self.all_lines) // self.num_trainers - self.lines = self.all_lines[num_lines * self.trainer_id: num_lines * (self.trainer_id + 1)] + self.lines = self.all_lines[num_lines * self.trainer_id:num_lines * + (self.trainer_id + 1)] self.shuffle_seed += 1 elif self.shuffle: np.random.shuffle(self.lines) @@ -118,7 +120,8 @@ class LaneNetDataset(): def batch_reader(is_test=False, drop_last=drop_last): if is_test: imgs, grts, grts_instance, img_names, valid_shapes, org_shapes = [], [], [], [], [], [] - for img, grt, grt_instance, img_name, valid_shape, org_shape in reader(): + for img, grt, grt_instance, img_name, valid_shape, org_shape in reader( + ): imgs.append(img) grts.append(grt) grts_instance.append(grt_instance) @@ -126,14 +129,15 @@ class LaneNetDataset(): valid_shapes.append(valid_shape) org_shapes.append(org_shape) if len(imgs) == batch_size: - yield np.array(imgs), np.array( - grts), np.array(grts_instance), img_names, np.array(valid_shapes), np.array( - org_shapes) + yield np.array(imgs), np.array(grts), np.array( + grts_instance), img_names, np.array( + valid_shapes), np.array(org_shapes) imgs, grts, grts_instance, img_names, valid_shapes, org_shapes = [], [], [], [], [], [] if not drop_last and len(imgs) > 0: - yield np.array(imgs), np.array(grts), np.array(grts_instance), img_names, np.array( - valid_shapes), np.array(org_shapes) + yield np.array(imgs), np.array(grts), np.array( + grts_instance), img_names, np.array( + valid_shapes), np.array(org_shapes) else: imgs, labs, labs_instance, ignore = [], [], [], [] bs = 0 @@ -144,12 +148,14 @@ class LaneNetDataset(): ignore.append(ig) bs += 1 if bs == batch_size: - yield np.array(imgs), np.array(labs), np.array(labs_instance), np.array(ignore) + yield np.array(imgs), np.array(labs), np.array( + labs_instance), np.array(ignore) bs = 0 imgs, labs, labs_instance, ignore = [], [], [], [] if not drop_last and bs > 0: - yield np.array(imgs), np.array(labs), np.array(labs_instance), np.array(ignore) + yield np.array(imgs), np.array(labs), np.array( + labs_instance), np.array(ignore) return batch_reader(is_test, drop_last) @@ -299,10 +305,12 @@ class LaneNetDataset(): img, grt = aug.rand_crop(img, grt, mode=mode) elif ModelPhase.is_eval(mode): - img, grt, grt_instance = aug.resize(img, grt, grt_instance, mode=mode) + img, grt, grt_instance = aug.resize( + img, grt, grt_instance, mode=mode) elif ModelPhase.is_visual(mode): ori_img = img.copy() - img, grt, grt_instance = aug.resize(img, grt, grt_instance, mode=mode) + img, grt, grt_instance = aug.resize( + img, grt, grt_instance, mode=mode) valid_shape = [img.shape[0], img.shape[1]] else: raise ValueError("Dataset mode={} Error!".format(mode)) diff --git a/contrib/LaneNet/train.py b/contrib/LaneNet/train.py index d9d22ba999cbbc3a9252f258e973612c68fe4ee4..0fb251c3cf63f27652240e902b0ebe9bb25ddf72 100644 --- a/contrib/LaneNet/train.py +++ b/contrib/LaneNet/train.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -40,10 +40,10 @@ from pdseg.utils.timer import Timer, calculate_eta from reader import LaneNetDataset from models.model_builder import build_model from models.model_builder import ModelPhase -from models.model_builder import parse_shape_from_file from eval import evaluate from vis import visualize from utils import dist_utils +from utils.load_model_utils import load_pretrained_weights def parse_args(): @@ -101,37 +101,6 @@ def parse_args(): return parser.parse_args() -def save_vars(executor, dirname, program=None, vars=None): - """ - Temporary resolution for Win save variables compatability. - Will fix in PaddlePaddle v1.5.2 - """ - - save_program = fluid.Program() - save_block = save_program.global_block() - - for each_var in vars: - # NOTE: don't save the variable which type is RAW - if each_var.type == fluid.core.VarDesc.VarType.RAW: - continue - new_var = save_block.create_var( - name=each_var.name, - shape=each_var.shape, - dtype=each_var.dtype, - type=each_var.type, - lod_level=each_var.lod_level, - persistable=True) - file_path = os.path.join(dirname, new_var.name) - file_path = os.path.normpath(file_path) - save_block.append_op( - type='save', - inputs={'X': [new_var]}, - outputs={}, - attrs={'file_path': file_path}) - - executor.run(save_program) - - def save_checkpoint(exe, program, ckpt_name): """ Save checkpoint for evaluation or resume training @@ -141,29 +110,22 @@ def save_checkpoint(exe, program, ckpt_name): if not os.path.isdir(ckpt_dir): os.makedirs(ckpt_dir) - save_vars( - exe, - ckpt_dir, - program, - vars=list(filter(fluid.io.is_persistable, program.list_vars()))) + fluid.save(program, os.path.join(ckpt_dir, 'model')) return ckpt_dir def load_checkpoint(exe, program): """ - Load checkpoiont from pretrained model directory for resume training + Load checkpoiont for resuming training """ - - print('Resume model training from:', cfg.TRAIN.RESUME_MODEL_DIR) - if not os.path.exists(cfg.TRAIN.RESUME_MODEL_DIR): - raise ValueError("TRAIN.PRETRAIN_MODEL {} not exist!".format( - cfg.TRAIN.RESUME_MODEL_DIR)) - - fluid.io.load_persistables( - exe, cfg.TRAIN.RESUME_MODEL_DIR, main_program=program) - model_path = cfg.TRAIN.RESUME_MODEL_DIR + print('Resume model training from:', model_path) + if not os.path.exists(model_path): + raise ValueError( + "TRAIN.PRETRAIN_MODEL {} not exist!".format(model_path)) + fluid.load(program, os.path.join(model_path, 'model'), exe) + # Check is path ended by path spearator if model_path[-1] == os.sep: model_path = model_path[0:-1] @@ -178,7 +140,6 @@ def load_checkpoint(exe, program): else: raise ValueError("Resume model path is not valid!") print("Model checkpoint loaded successfully!") - return begin_epoch @@ -271,44 +232,7 @@ def train(cfg): begin_epoch = load_checkpoint(exe, train_prog) # Load pretrained model elif os.path.exists(cfg.TRAIN.PRETRAINED_MODEL_DIR): - print_info('Pretrained model dir: ', cfg.TRAIN.PRETRAINED_MODEL_DIR) - load_vars = [] - load_fail_vars = [] - - def var_shape_matched(var, shape): - """ - Check whehter persitable variable shape is match with current network - """ - var_exist = os.path.exists( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - if var_exist: - var_shape = parse_shape_from_file( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - if var_shape != shape: - print(var.name, var_shape, shape) - return var_shape == shape - return False - - for x in train_prog.list_vars(): - if isinstance(x, fluid.framework.Parameter): - shape = tuple(fluid.global_scope().find_var( - x.name).get_tensor().shape()) - if var_shape_matched(x, shape): - load_vars.append(x) - else: - load_fail_vars.append(x) - - fluid.io.load_vars( - exe, dirname=cfg.TRAIN.PRETRAINED_MODEL_DIR, vars=load_vars) - for var in load_vars: - print_info("Parameter[{}] loaded sucessfully!".format(var.name)) - for var in load_fail_vars: - print_info( - "Parameter[{}] don't exist or shape does not match current network, skip" - " to load it.".format(var.name)) - print_info("{}/{} pretrained parameters loaded successfully!".format( - len(load_vars), - len(load_vars) + len(load_fail_vars))) + load_pretrained_weights(exe, train_prog, cfg.TRAIN.PRETRAINED_MODEL_DIR) else: print_info( 'Pretrained model dir {} not exists, training from scratch...'. @@ -393,8 +317,7 @@ def train(cfg): avg_emb_loss, avg_acc, avg_fp, avg_fn, speed, calculate_eta(all_step - step, speed))) if args.use_vdl: - log_writer.add_scalar('Train/loss', avg_loss, - step) + log_writer.add_scalar('Train/loss', avg_loss, step) log_writer.add_scalar('Train/lr', lr[0], step) log_writer.add_scalar('Train/speed', speed, step) sys.stdout.flush() @@ -423,8 +346,7 @@ def train(cfg): use_gpu=args.use_gpu, use_mpio=args.use_mpio) if args.use_vdl: - log_writer.add_scalar('Evaluate/accuracy', accuracy, - step) + log_writer.add_scalar('Evaluate/accuracy', accuracy, step) log_writer.add_scalar('Evaluate/fp', fp, step) log_writer.add_scalar('Evaluate/fn', fn, step) diff --git a/contrib/LaneNet/utils/__init__.py b/contrib/LaneNet/utils/__init__.py index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0e7c9f39543584630fdaedf13d2879a663a789f0 100644 --- a/contrib/LaneNet/utils/__init__.py +++ b/contrib/LaneNet/utils/__init__.py @@ -0,0 +1,14 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/contrib/LaneNet/utils/config.py b/contrib/LaneNet/utils/config.py index 7c2019d44a100b033520138632fc0e7b56d65676..4915b7b78eb5ed2eda03b72c305c566017d81e2c 100644 --- a/contrib/LaneNet/utils/config.py +++ b/contrib/LaneNet/utils/config.py @@ -1,11 +1,11 @@ -# -*- coding: utf-8 -*- -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, @@ -80,8 +80,8 @@ cfg.DATASET.DATA_DIM = 3 cfg.DATASET.SEPARATOR = ' ' # 忽略的像素标签值, 默认为255，一般无需改动 cfg.DATASET.IGNORE_INDEX = 255 -# 数据增强是图像的padding值 -cfg.DATASET.PADDING_VALUE = [127.5,127.5,127.5] +# 数据增强是图像的padding值 +cfg.DATASET.PADDING_VALUE = [127.5, 127.5, 127.5] ########################### 数据增强配置 ###################################### # 图像镜像左右翻转 diff --git a/contrib/LaneNet/utils/dist_utils.py b/contrib/LaneNet/utils/dist_utils.py index 64c8800fd2010d4e1e5def6cc4ea2e1ad673b4a3..1189f75def7e706110df0efd8edb62b0940ba9de 100755 --- a/contrib/LaneNet/utils/dist_utils.py +++ b/contrib/LaneNet/utils/dist_utils.py @@ -1,16 +1,17 @@ -#copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -#Licensed under the Apache License, Version 2.0 (the "License"); -#you may not use this file except in compliance with the License. -#You may obtain a copy of the License at +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # -#Unless required by applicable law or agreed to in writing, software -#distributed under the License is distributed on an "AS IS" BASIS, -#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -#See the License for the specific language governing permissions and -#limitations under the License. +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. from __future__ import absolute_import from __future__ import division diff --git a/contrib/LaneNet/utils/generate_tusimple_dataset.py b/contrib/LaneNet/utils/generate_tusimple_dataset.py index ea2a89584b6aa3eab45e0fb8516d935f13afe644..ad83c275f7748643b01ce067157d56f465fa7534 100644 --- a/contrib/LaneNet/utils/generate_tusimple_dataset.py +++ b/contrib/LaneNet/utils/generate_tusimple_dataset.py @@ -1,3 +1,17 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. """ generate tusimple training dataset """ @@ -14,12 +28,16 @@ import numpy as np def init_args(): parser = argparse.ArgumentParser() - parser.add_argument('--src_dir', type=str, help='The origin path of unzipped tusimple dataset') + parser.add_argument( + '--src_dir', + type=str, + help='The origin path of unzipped tusimple dataset') return parser.parse_args() -def process_json_file(json_file_path, src_dir, ori_dst_dir, binary_dst_dir, instance_dst_dir): +def process_json_file(json_file_path, src_dir, ori_dst_dir, binary_dst_dir, + instance_dst_dir): assert ops.exists(json_file_path), '{:s} not exist'.format(json_file_path) @@ -39,11 +57,14 @@ def process_json_file(json_file_path, src_dir, ori_dst_dir, binary_dst_dir, inst h_samples = info_dict['h_samples'] lanes = info_dict['lanes'] - image_name_new = '{:s}.png'.format('{:d}'.format(line_index + image_nums).zfill(4)) + image_name_new = '{:s}.png'.format( + '{:d}'.format(line_index + image_nums).zfill(4)) src_image = cv2.imread(image_path, cv2.IMREAD_COLOR) - dst_binary_image = np.zeros([src_image.shape[0], src_image.shape[1]], np.uint8) - dst_instance_image = np.zeros([src_image.shape[0], src_image.shape[1]], np.uint8) + dst_binary_image = np.zeros( + [src_image.shape[0], src_image.shape[1]], np.uint8) + dst_instance_image = np.zeros( + [src_image.shape[0], src_image.shape[1]], np.uint8) for lane_index, lane in enumerate(lanes): assert len(h_samples) == len(lane) @@ -62,13 +83,23 @@ def process_json_file(json_file_path, src_dir, ori_dst_dir, binary_dst_dir, inst lane_pts = np.vstack((lane_x, lane_y)).transpose() lane_pts = np.array([lane_pts], np.int64) - cv2.polylines(dst_binary_image, lane_pts, isClosed=False, - color=255, thickness=5) - cv2.polylines(dst_instance_image, lane_pts, isClosed=False, - color=lane_index * 50 + 20, thickness=5) - - dst_binary_image_path = ops.join(src_dir, binary_dst_dir, image_name_new) - dst_instance_image_path = ops.join(src_dir, instance_dst_dir, image_name_new) + cv2.polylines( + dst_binary_image, + lane_pts, + isClosed=False, + color=255, + thickness=5) + cv2.polylines( + dst_instance_image, + lane_pts, + isClosed=False, + color=lane_index * 50 + 20, + thickness=5) + + dst_binary_image_path = ops.join(src_dir, binary_dst_dir, + image_name_new) + dst_instance_image_path = ops.join(src_dir, instance_dst_dir, + image_name_new) dst_rgb_image_path = ops.join(src_dir, ori_dst_dir, image_name_new) cv2.imwrite(dst_binary_image_path, dst_binary_image) @@ -78,7 +109,12 @@ def process_json_file(json_file_path, src_dir, ori_dst_dir, binary_dst_dir, inst print('Process {:s} success'.format(image_name)) -def gen_sample(src_dir, b_gt_image_dir, i_gt_image_dir, image_dir, phase='train', split=False): +def gen_sample(src_dir, + b_gt_image_dir, + i_gt_image_dir, + image_dir, + phase='train', + split=False): label_list = [] with open('{:s}/{}ing/{}.txt'.format(src_dir, phase, phase), 'w') as file: @@ -92,7 +128,8 @@ def gen_sample(src_dir, b_gt_image_dir, i_gt_image_dir, image_dir, phase='train' image_path = ops.join(image_dir, image_name) assert ops.exists(image_path), '{:s} not exist'.format(image_path) - assert ops.exists(instance_gt_image_path), '{:s} not exist'.format(instance_gt_image_path) + assert ops.exists(instance_gt_image_path), '{:s} not exist'.format( + instance_gt_image_path) b_gt_image = cv2.imread(binary_gt_image_path, cv2.IMREAD_COLOR) i_gt_image = cv2.imread(instance_gt_image_path, cv2.IMREAD_COLOR) @@ -102,7 +139,8 @@ def gen_sample(src_dir, b_gt_image_dir, i_gt_image_dir, image_dir, phase='train' print('image: {:s} corrupt'.format(image_name)) continue else: - info = '{:s} {:s} {:s}'.format(image_path, binary_gt_image_path, instance_gt_image_path) + info = '{:s} {:s} {:s}'.format(image_path, binary_gt_image_path, + instance_gt_image_path) file.write(info + '\n') label_list.append(info) if phase == 'train' and split: @@ -110,10 +148,12 @@ def gen_sample(src_dir, b_gt_image_dir, i_gt_image_dir, image_dir, phase='train' val_list_len = len(label_list) // 10 val_label_list = label_list[:val_list_len] train_label_list = label_list[val_list_len:] - with open('{:s}/{}ing/train_part.txt'.format(src_dir, phase, phase), 'w') as file: + with open('{:s}/{}ing/train_part.txt'.format(src_dir, phase, phase), + 'w') as file: for info in train_label_list: file.write(info + '\n') - with open('{:s}/{}ing/val_part.txt'.format(src_dir, phase, phase), 'w') as file: + with open('{:s}/{}ing/val_part.txt'.format(src_dir, phase, phase), + 'w') as file: for info in val_label_list: file.write(info + '\n') return @@ -130,12 +170,14 @@ def process_tusimple_dataset(src_dir): for json_label_path in glob.glob('{:s}/label*.json'.format(src_dir)): json_label_name = ops.split(json_label_path)[1] - shutil.copyfile(json_label_path, ops.join(traing_folder_path, json_label_name)) + shutil.copyfile(json_label_path, + ops.join(traing_folder_path, json_label_name)) for json_label_path in glob.glob('{:s}/test_label.json'.format(src_dir)): json_label_name = ops.split(json_label_path)[1] - shutil.copyfile(json_label_path, ops.join(testing_folder_path, json_label_name)) + shutil.copyfile(json_label_path, + ops.join(testing_folder_path, json_label_name)) train_gt_image_dir = ops.join('training', 'gt_image') train_gt_binary_dir = ops.join('training', 'gt_binary_image') @@ -154,9 +196,11 @@ def process_tusimple_dataset(src_dir): os.makedirs(os.path.join(src_dir, test_gt_instance_dir), exist_ok=True) for json_label_path in glob.glob('{:s}/*.json'.format(traing_folder_path)): - process_json_file(json_label_path, src_dir, train_gt_image_dir, train_gt_binary_dir, train_gt_instance_dir) + process_json_file(json_label_path, src_dir, train_gt_image_dir, + train_gt_binary_dir, train_gt_instance_dir) - gen_sample(src_dir, train_gt_binary_dir, train_gt_instance_dir, train_gt_image_dir, 'train', True) + gen_sample(src_dir, train_gt_binary_dir, train_gt_instance_dir, + train_gt_image_dir, 'train', True) if __name__ == '__main__': diff --git a/contrib/LaneNet/utils/lanenet_postprocess.py b/contrib/LaneNet/utils/lanenet_postprocess.py index 21230279f7c4b4e1042e51f7583a3a13d4ebc5d7..172fc1c3f054cdb39cf68b242336cab165fe1e24 100644 --- a/contrib/LaneNet/utils/lanenet_postprocess.py +++ b/contrib/LaneNet/utils/lanenet_postprocess.py @@ -1,5 +1,18 @@ -#!/usr/bin/env python3 -# -*- coding: utf-8 -*- +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + # this code heavily base on https://github.com/MaybeShewill-CV/lanenet-lane-detection/blob/master/lanenet_model/lanenet_postprocess.py """ LaneNet model post process @@ -22,12 +35,14 @@ def _morphological_process(image, kernel_size=5): :return: """ if len(image.shape) == 3: - raise ValueError('Binary segmentation result image should be a single channel image') + raise ValueError( + 'Binary segmentation result image should be a single channel image') if image.dtype is not np.uint8: image = np.array(image, np.uint8) - kernel = cv2.getStructuringElement(shape=cv2.MORPH_ELLIPSE, ksize=(kernel_size, kernel_size)) + kernel = cv2.getStructuringElement( + shape=cv2.MORPH_ELLIPSE, ksize=(kernel_size, kernel_size)) # close operation fille hole closing = cv2.morphologyEx(image, cv2.MORPH_CLOSE, kernel, iterations=1) @@ -46,13 +61,15 @@ def _connect_components_analysis(image): else: gray_image = image - return cv2.connectedComponentsWithStats(gray_image, connectivity=8, ltype=cv2.CV_32S) + return cv2.connectedComponentsWithStats( + gray_image, connectivity=8, ltype=cv2.CV_32S) class _LaneFeat(object): """ """ + def __init__(self, feat, coord, class_id=-1): """ lane feat object @@ -108,18 +125,21 @@ class _LaneNetCluster(object): """ Instance segmentation result cluster """ + def __init__(self): """ """ - self._color_map = [np.array([255, 0, 0]), - np.array([0, 255, 0]), - np.array([0, 0, 255]), - np.array([125, 125, 0]), - np.array([0, 125, 125]), - np.array([125, 0, 125]), - np.array([50, 100, 50]), - np.array([100, 50, 100])] + self._color_map = [ + np.array([255, 0, 0]), + np.array([0, 255, 0]), + np.array([0, 0, 255]), + np.array([125, 125, 0]), + np.array([0, 125, 125]), + np.array([125, 0, 125]), + np.array([50, 100, 50]), + np.array([100, 50, 100]) + ] @staticmethod def _embedding_feats_dbscan_cluster(embedding_image_feats): @@ -186,15 +206,16 @@ class _LaneNetCluster(object): # get embedding feats and coords get_lane_embedding_feats_result = self._get_lane_embedding_feats( binary_seg_ret=binary_seg_result, - instance_seg_ret=instance_seg_result - ) + instance_seg_ret=instance_seg_result) # dbscan cluster dbscan_cluster_result = self._embedding_feats_dbscan_cluster( - embedding_image_feats=get_lane_embedding_feats_result['lane_embedding_feats'] - ) + embedding_image_feats=get_lane_embedding_feats_result[ + 'lane_embedding_feats']) - mask = np.zeros(shape=[binary_seg_result.shape[0], binary_seg_result.shape[1], 3], dtype=np.uint8) + mask = np.zeros( + shape=[binary_seg_result.shape[0], binary_seg_result.shape[1], 3], + dtype=np.uint8) db_labels = dbscan_cluster_result['db_labels'] unique_labels = dbscan_cluster_result['unique_labels'] coord = get_lane_embedding_feats_result['lane_coordinates'] @@ -219,11 +240,13 @@ class LaneNetPostProcessor(object): """ lanenet post process for lane generation """ + def __init__(self, ipm_remap_file_path='./utils/tusimple_ipm_remap.yml'): """ convert front car view to bird view """ - assert ops.exists(ipm_remap_file_path), '{:s} not exist'.format(ipm_remap_file_path) + assert ops.exists(ipm_remap_file_path), '{:s} not exist'.format( + ipm_remap_file_path) self._cluster = _LaneNetCluster() self._ipm_remap_file_path = ipm_remap_file_path @@ -232,14 +255,16 @@ class LaneNetPostProcessor(object): self._remap_to_ipm_x = remap_file_load_ret['remap_to_ipm_x'] self._remap_to_ipm_y = remap_file_load_ret['remap_to_ipm_y'] - self._color_map = [np.array([255, 0, 0]), - np.array([0, 255, 0]), - np.array([0, 0, 255]), - np.array([125, 125, 0]), - np.array([0, 125, 125]), - np.array([125, 0, 125]), - np.array([50, 100, 50]), - np.array([100, 50, 100])] + self._color_map = [ + np.array([255, 0, 0]), + np.array([0, 255, 0]), + np.array([0, 0, 255]), + np.array([125, 125, 0]), + np.array([0, 125, 125]), + np.array([125, 0, 125]), + np.array([50, 100, 50]), + np.array([100, 50, 100]) + ] def _load_remap_matrix(self): fs = cv2.FileStorage(self._ipm_remap_file_path, cv2.FILE_STORAGE_READ) @@ -256,15 +281,20 @@ class LaneNetPostProcessor(object): return ret - def postprocess(self, binary_seg_result, instance_seg_result=None, - min_area_threshold=100, source_image=None, + def postprocess(self, + binary_seg_result, + instance_seg_result=None, + min_area_threshold=100, + source_image=None, data_source='tusimple'): # convert binary_seg_result binary_seg_result = np.array(binary_seg_result * 255, dtype=np.uint8) # apply image morphology operation to fill in the hold and reduce the small area - morphological_ret = _morphological_process(binary_seg_result, kernel_size=5) - connect_components_analysis_ret = _connect_components_analysis(image=morphological_ret) + morphological_ret = _morphological_process( + binary_seg_result, kernel_size=5) + connect_components_analysis_ret = _connect_components_analysis( + image=morphological_ret) labels = connect_components_analysis_ret[1] stats = connect_components_analysis_ret[2] @@ -276,8 +306,7 @@ class LaneNetPostProcessor(object): # apply embedding features cluster mask_image, lane_coords = self._cluster.apply_lane_feats_cluster( binary_seg_result=morphological_ret, - instance_seg_result=instance_seg_result - ) + instance_seg_result=instance_seg_result) if mask_image is None: return { @@ -292,15 +321,15 @@ class LaneNetPostProcessor(object): for lane_index, coords in enumerate(lane_coords): if data_source == 'tusimple': tmp_mask = np.zeros(shape=(720, 1280), dtype=np.uint8) - tmp_mask[tuple((np.int_(coords[:, 1] * 720 / 256), np.int_(coords[:, 0] * 1280 / 512)))] = 255 + tmp_mask[tuple((np.int_(coords[:, 1] * 720 / 256), + np.int_(coords[:, 0] * 1280 / 512)))] = 255 else: raise ValueError('Wrong data source now only support tusimple') tmp_ipm_mask = cv2.remap( tmp_mask, self._remap_to_ipm_x, self._remap_to_ipm_y, - interpolation=cv2.INTER_NEAREST - ) + interpolation=cv2.INTER_NEAREST) nonzero_y = np.array(tmp_ipm_mask.nonzero()[0]) nonzero_x = np.array(tmp_ipm_mask.nonzero()[1]) @@ -309,16 +338,19 @@ class LaneNetPostProcessor(object): [ipm_image_height, ipm_image_width] = tmp_ipm_mask.shape plot_y = np.linspace(10, ipm_image_height, ipm_image_height - 10) - fit_x = fit_param[0] * plot_y ** 2 + fit_param[1] * plot_y + fit_param[2] + fit_x = fit_param[0] * plot_y**2 + fit_param[ + 1] * plot_y + fit_param[2] lane_pts = [] for index in range(0, plot_y.shape[0], 5): src_x = self._remap_to_ipm_x[ - int(plot_y[index]), int(np.clip(fit_x[index], 0, ipm_image_width - 1))] + int(plot_y[index]), + int(np.clip(fit_x[index], 0, ipm_image_width - 1))] if src_x <= 0: continue src_y = self._remap_to_ipm_y[ - int(plot_y[index]), int(np.clip(fit_x[index], 0, ipm_image_width - 1))] + int(plot_y[index]), + int(np.clip(fit_x[index], 0, ipm_image_width - 1))] src_y = src_y if src_y > 0 else 0 lane_pts.append([src_x, src_y]) @@ -366,8 +398,10 @@ class LaneNetPostProcessor(object): continue lane_color = self._color_map[index].tolist() - cv2.circle(source_image, (int(interpolation_src_pt_x), - int(interpolation_src_pt_y)), 5, lane_color, -1) + cv2.circle( + source_image, + (int(interpolation_src_pt_x), int(interpolation_src_pt_y)), + 5, lane_color, -1) ret = { 'mask_image': mask_image, 'fit_params': fit_params, diff --git a/contrib/LaneNet/utils/load_model_utils.py b/contrib/LaneNet/utils/load_model_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..012cc680e9e4db49b29e1a74835ac1c9a62ff103 --- /dev/null +++ b/contrib/LaneNet/utils/load_model_utils.py @@ -0,0 +1,126 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +import os.path as osp + +import six +import numpy as np + + +def parse_param_file(param_file, return_shape=True): + from paddle.fluid.proto.framework_pb2 import VarType + f = open(param_file, 'rb') + version = np.fromstring(f.read(4), dtype='int32') + lod_level = np.fromstring(f.read(8), dtype='int64') + for i in range(int(lod_level)): + _size = np.fromstring(f.read(8), dtype='int64') + _ = f.read(_size) + version = np.fromstring(f.read(4), dtype='int32') + tensor_desc = VarType.TensorDesc() + tensor_desc_size = np.fromstring(f.read(4), dtype='int32') + tensor_desc.ParseFromString(f.read(int(tensor_desc_size))) + tensor_shape = tuple(tensor_desc.dims) + if return_shape: + f.close() + return tuple(tensor_desc.dims) + if tensor_desc.data_type != 5: + raise Exception( + "Unexpected data type while parse {}".format(param_file)) + data_size = 4 + for i in range(len(tensor_shape)): + data_size *= tensor_shape[i] + weight = np.fromstring(f.read(data_size), dtype='float32') + f.close() + return np.reshape(weight, tensor_shape) + + +def load_pdparams(exe, main_prog, model_dir): + import paddle.fluid as fluid + from paddle.fluid.proto.framework_pb2 import VarType + from paddle.fluid.framework import Program + + vars_to_load = list() + vars_not_load = list() + import pickle + with open(osp.join(model_dir, 'model.pdparams'), 'rb') as f: + params_dict = pickle.load(f) if six.PY2 else pickle.load( + f, encoding='latin1') + unused_vars = list() + for var in main_prog.list_vars(): + if not isinstance(var, fluid.framework.Parameter): + continue + if var.name not in params_dict: + print("{} is not in saved model".format(var.name)) + vars_not_load.append(var.name) + continue + if var.shape != params_dict[var.name].shape: + unused_vars.append(var.name) + vars_not_load.append(var.name) + print( + "[SKIP] Shape of pretrained weight {} doesn't match.(Pretrained: {}, Actual: {})" + .format(var.name, params_dict[var.name].shape, var.shape)) + continue + vars_to_load.append(var) + for var_name in unused_vars: + del params_dict[var_name] + fluid.io.set_program_state(main_prog, params_dict) + + if len(vars_to_load) == 0: + print( + "There is no pretrain weights loaded, maybe you should check you pretrain model!" + ) + else: + print("There are {}/{} varaibles in {} are loaded.".format( + len(vars_to_load), + len(vars_to_load) + len(vars_not_load), model_dir)) + + +def load_pretrained_weights(exe, main_prog, weights_dir): + if not osp.exists(weights_dir): + raise Exception("Path {} not exists.".format(weights_dir)) + if osp.exists(osp.join(weights_dir, "model.pdparams")): + return load_pdparams(exe, main_prog, weights_dir) + import paddle.fluid as fluid + vars_to_load = list() + vars_not_load = list() + for var in main_prog.list_vars(): + if not isinstance(var, fluid.framework.Parameter): + continue + if not osp.exists(osp.join(weights_dir, var.name)): + print("[SKIP] Pretrained weight {}/{} doesn't exist".format( + weights_dir, var.name)) + vars_not_load.append(var) + continue + pretrained_shape = parse_param_file(osp.join(weights_dir, var.name)) + actual_shape = tuple(var.shape) + if pretrained_shape != actual_shape: + print( + "[SKIP] Shape of pretrained weight {}/{} doesn't match.(Pretrained: {}, Actual: {})" + .format(weights_dir, var.name, pretrained_shape, actual_shape)) + vars_not_load.append(var) + continue + vars_to_load.append(var) + params_dict = fluid.io.load_program_state( + weights_dir, var_list=vars_to_load) + fluid.io.set_program_state(main_prog, params_dict) + if len(vars_to_load) == 0: + print( + "There is no pretrain weights loaded, maybe you should check you pretrain model!" + ) + else: + print("There are {}/{} varaibles in {} are loaded.".format( + len(vars_to_load), + len(vars_to_load) + len(vars_not_load), weights_dir)) diff --git a/contrib/LaneNet/vis.py b/contrib/LaneNet/vis.py index 594258758316cb8945463962c71a52b42314faa6..a037e8451ac86695d4c17d947d14d8753bf96259 100644 --- a/contrib/LaneNet/vis.py +++ b/contrib/LaneNet/vis.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -45,6 +45,7 @@ from models.model_builder import ModelPhase from utils import lanenet_postprocess import matplotlib.pyplot as plt + def parse_args(): parser = argparse.ArgumentParser(description='PaddeSeg visualization tools') parser.add_argument( @@ -106,7 +107,6 @@ def minmax_scale(input_arr): return output_arr - def visualize(cfg, vis_file_list=None, use_gpu=False, @@ -119,7 +119,6 @@ def visualize(cfg, if vis_file_list is None: vis_file_list = cfg.DATASET.TEST_FILE_LIST - dataset = LaneNetDataset( file_list=vis_file_list, mode=ModelPhase.VISUAL, @@ -139,7 +138,12 @@ def visualize(cfg, ckpt_dir = cfg.TEST.TEST_MODEL if not ckpt_dir else ckpt_dir - fluid.io.load_params(exe, ckpt_dir, main_program=test_prog) + if ckpt_dir is not None: + print('load test model:', ckpt_dir) + try: + fluid.load(test_prog, os.path.join(ckpt_dir, 'model'), exe) + except: + fluid.io.load_params(exe, ckpt_dir, main_program=test_prog) save_dir = os.path.join(vis_dir, 'visual_results') makedirs(save_dir) @@ -161,22 +165,26 @@ def visualize(cfg, for i in range(num_imgs): gt_image = org_imgs[i] - binary_seg_image, instance_seg_image = segLogits[i].squeeze(-1), emLogits[i].transpose((1,2,0)) + binary_seg_image, instance_seg_image = segLogits[i].squeeze( + -1), emLogits[i].transpose((1, 2, 0)) postprocess_result = postprocessor.postprocess( binary_seg_result=binary_seg_image, instance_seg_result=instance_seg_image, - source_image=gt_image - ) - pred_binary_fn = os.path.join(save_dir, to_png_fn(img_names[i], name='_pred_binary')) - pred_lane_fn = os.path.join(save_dir, to_png_fn(img_names[i], name='_pred_lane')) - pred_instance_fn = os.path.join(save_dir, to_png_fn(img_names[i], name='_pred_instance')) + source_image=gt_image) + pred_binary_fn = os.path.join( + save_dir, to_png_fn(img_names[i], name='_pred_binary')) + pred_lane_fn = os.path.join( + save_dir, to_png_fn(img_names[i], name='_pred_lane')) + pred_instance_fn = os.path.join( + save_dir, to_png_fn(img_names[i], name='_pred_instance')) dirname = os.path.dirname(pred_binary_fn) makedirs(dirname) mask_image = postprocess_result['mask_image'] for i in range(4): - instance_seg_image[:, :, i] = minmax_scale(instance_seg_image[:, :, i]) + instance_seg_image[:, :, i] = minmax_scale( + instance_seg_image[:, :, i]) embedding_image = np.array(instance_seg_image).astype(np.uint8) plt.figure('mask_image') @@ -189,13 +197,13 @@ def visualize(cfg, plt.imshow(binary_seg_image * 255, cmap='gray') plt.show() - cv2.imwrite(pred_binary_fn, np.array(binary_seg_image * 255).astype(np.uint8)) + cv2.imwrite(pred_binary_fn, + np.array(binary_seg_image * 255).astype(np.uint8)) cv2.imwrite(pred_lane_fn, postprocess_result['source_image']) cv2.imwrite(pred_instance_fn, mask_image) print(pred_lane_fn, 'saved!') - if __name__ == '__main__': args = parse_args() if args.cfg_file is not None: diff --git a/contrib/MechanicalIndustryMeter/download_mini_mechanical_industry_meter.py b/contrib/MechanicalIndustryMeter/download_mini_mechanical_industry_meter.py index f0409581ea9454417c545aa616b98ee8ece4dc53..fb98fdf9c4e08f2254392a528d7f2d1c386b3565 100644 --- a/contrib/MechanicalIndustryMeter/download_mini_mechanical_industry_meter.py +++ b/contrib/MechanicalIndustryMeter/download_mini_mechanical_industry_meter.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/MechanicalIndustryMeter/download_unet_mechanical_industry_meter.py b/contrib/MechanicalIndustryMeter/download_unet_mechanical_industry_meter.py index aa55bf5e03b8dcf31e52043fd5dc87086c03c32f..32b2a8aea34343add34ab082e35c55188171a313 100644 --- a/contrib/MechanicalIndustryMeter/download_unet_mechanical_industry_meter.py +++ b/contrib/MechanicalIndustryMeter/download_unet_mechanical_industry_meter.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, @@ -23,7 +24,8 @@ from test_utils import download_file_and_uncompress if __name__ == "__main__": download_file_and_uncompress( - url='https://paddleseg.bj.bcebos.com/models/unet_mechanical_industry_meter.tar', + url= + 'https://paddleseg.bj.bcebos.com/models/unet_mechanical_industry_meter.tar', savepath=LOCAL_PATH, extrapath=LOCAL_PATH) diff --git a/contrib/RemoteSensing/__init__.py b/contrib/RemoteSensing/__init__.py index ea9751219a9eda9e50a80e9dff2a8b3d7cba0066..8e5bc0b3793094246da001295ae154941bc803b0 100644 --- a/contrib/RemoteSensing/__init__.py +++ b/contrib/RemoteSensing/__init__.py @@ -1,10 +1,11 @@ -# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/RemoteSensing/models/__init__.py b/contrib/RemoteSensing/models/__init__.py index b88424493bd31ef0c794d21febb784724e6ebff4..08e8fd5a583c85af0c0a5691f771874a65cb9a80 100644 --- a/contrib/RemoteSensing/models/__init__.py +++ b/contrib/RemoteSensing/models/__init__.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from .load_model import * from .unet import * from .hrnet import * diff --git a/contrib/RemoteSensing/models/base.py b/contrib/RemoteSensing/models/base.py index 3d42fa46d9776dc7e43d73e7b27266c1704ebf1c..06a6bc6df5ea5a7147e1071109f7a978e88c3541 100644 --- a/contrib/RemoteSensing/models/base.py +++ b/contrib/RemoteSensing/models/base.py @@ -1,16 +1,17 @@ -#copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -#Licensed under the Apache License, Version 2.0 (the "License"); -#you may not use this file except in compliance with the License. -#You may obtain a copy of the License at +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # -#Unless required by applicable law or agreed to in writing, software -#distributed under the License is distributed on an "AS IS" BASIS, -#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -#See the License for the specific language governing permissions and -#limitations under the License. +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. from __future__ import absolute_import import paddle.fluid as fluid diff --git a/contrib/RemoteSensing/models/load_model.py b/contrib/RemoteSensing/models/load_model.py index 6b765c81a242d2dc4aaedef08d63ac6f92073297..53a61a01c97f0ccce8356b8480ab95195bae1742 100644 --- a/contrib/RemoteSensing/models/load_model.py +++ b/contrib/RemoteSensing/models/load_model.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/models/unet.py b/contrib/RemoteSensing/models/unet.py index 243af3339c2bacbb37b2777edceb6b610b8feaf4..732c83741428509518426e306191cc8f1091cf87 100644 --- a/contrib/RemoteSensing/models/unet.py +++ b/contrib/RemoteSensing/models/unet.py @@ -1,16 +1,17 @@ -#copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -#Licensed under the Apache License, Version 2.0 (the "License"); -#you may not use this file except in compliance with the License. -#You may obtain a copy of the License at +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # -#Unless required by applicable law or agreed to in writing, software -#distributed under the License is distributed on an "AS IS" BASIS, -#WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -#See the License for the specific language governing permissions and -#limitations under the License. +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. from __future__ import absolute_import import numpy as np diff --git a/contrib/RemoteSensing/nets/__init__.py b/contrib/RemoteSensing/nets/__init__.py index 7ca925549e29148b929ad06d77ead49d22cfd7e4..7e56e96112081538641b03ae1c8462eae3af7cef 100644 --- a/contrib/RemoteSensing/nets/__init__.py +++ b/contrib/RemoteSensing/nets/__init__.py @@ -1,2 +1,17 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from .unet import UNet from .hrnet import HRNet diff --git a/contrib/RemoteSensing/nets/libs.py b/contrib/RemoteSensing/nets/libs.py index 01fdad2cec6ce4b13cea2b7c957fb648edb4aeb2..f74c93fc3f4203663c1f8844aa8b87716d8ecd91 100644 --- a/contrib/RemoteSensing/nets/libs.py +++ b/contrib/RemoteSensing/nets/libs.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/nets/loss.py b/contrib/RemoteSensing/nets/loss.py index 902c903fcc426e68de483ee249af16d21788a86c..a0794474a89a9a0ecf9befcc69c06ba4dee3b178 100644 --- a/contrib/RemoteSensing/nets/loss.py +++ b/contrib/RemoteSensing/nets/loss.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/nets/unet.py b/contrib/RemoteSensing/nets/unet.py index fef193ec72190ef5c08a54b8444e21ac6a901e6f..79669c9d13b6fd9192c0fdf15a2a907a699e8c96 100644 --- a/contrib/RemoteSensing/nets/unet.py +++ b/contrib/RemoteSensing/nets/unet.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/predict_demo.py b/contrib/RemoteSensing/predict_demo.py index fb167c30d227d662e71c8af9e85d80fae7dc9d3e..eb09cc29aae600ced76ac9ebf7acc380c1f43c1f 100644 --- a/contrib/RemoteSensing/predict_demo.py +++ b/contrib/RemoteSensing/predict_demo.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import os import os.path as osp import sys diff --git a/contrib/RemoteSensing/readers/__init__.py b/contrib/RemoteSensing/readers/__init__.py index babbe0866c625fc81f810a2cff82b8d138b9aa94..42eafa218c1c1638ea91c76ca3b1d8623193f813 100644 --- a/contrib/RemoteSensing/readers/__init__.py +++ b/contrib/RemoteSensing/readers/__init__.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/readers/base.py b/contrib/RemoteSensing/readers/base.py index 1427bd60ad4637a3f13c8a08f59291f15fe5ac82..2ce42564aac081d4c78b0b88d0a8014034327521 100644 --- a/contrib/RemoteSensing/readers/base.py +++ b/contrib/RemoteSensing/readers/base.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/readers/reader.py b/contrib/RemoteSensing/readers/reader.py index 343d25b15034e1905a1e55ae926fbdfa62916cf1..a86a22e9069ee31054e83de70e98f5048d8096ba 100644 --- a/contrib/RemoteSensing/readers/reader.py +++ b/contrib/RemoteSensing/readers/reader.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/tools/create_dataset_list.py b/contrib/RemoteSensing/tools/create_dataset_list.py index 430eea5e75f4dc8e1ed4babff6baa6d2fbdeb7f7..78a6c9b34f9a3486e09f0cbee4f014e3666df2de 100644 --- a/contrib/RemoteSensing/tools/create_dataset_list.py +++ b/contrib/RemoteSensing/tools/create_dataset_list.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/tools/split_dataset_list.py b/contrib/RemoteSensing/tools/split_dataset_list.py index ff15987aee2b6a30c961cbad28ebc4e7cb8f6f1d..143618a3734964238b2dd52c2ed1f602cae9889f 100644 --- a/contrib/RemoteSensing/tools/split_dataset_list.py +++ b/contrib/RemoteSensing/tools/split_dataset_list.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/train_demo.py b/contrib/RemoteSensing/train_demo.py index b6ff0905dd1d4a4888c3c63414e0c9c1d84d9915..18cb99492b20a7b3d5ef1cfef8b53de9da6b83e2 100644 --- a/contrib/RemoteSensing/train_demo.py +++ b/contrib/RemoteSensing/train_demo.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import os.path as osp import argparse import transforms.transforms as T diff --git a/contrib/RemoteSensing/transforms/__init__.py b/contrib/RemoteSensing/transforms/__init__.py index 8eba87ecc700db36f930be3a39c2ece981e00572..625b2bcc5c9561f00213a23f2bde64dd00c7af0f 100644 --- a/contrib/RemoteSensing/transforms/__init__.py +++ b/contrib/RemoteSensing/transforms/__init__.py @@ -1,10 +1,11 @@ -# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/RemoteSensing/transforms/ops.py b/contrib/RemoteSensing/transforms/ops.py index e04e695410e5f1e089de838526889c02cadd7da1..0efca13aa35466d71369b2c58949a15cd8476752 100644 --- a/contrib/RemoteSensing/transforms/ops.py +++ b/contrib/RemoteSensing/transforms/ops.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/transforms/transforms.py b/contrib/RemoteSensing/transforms/transforms.py index abac1746e09e8e95d4149e8243d6ea4258f347ef..00faca4ee98470ba8c5adc88ef89d0fd1139156e 100644 --- a/contrib/RemoteSensing/transforms/transforms.py +++ b/contrib/RemoteSensing/transforms/transforms.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/utils/__init__.py b/contrib/RemoteSensing/utils/__init__.py index f27f5ea79417cdfd65da5744527cc6f7869dcc02..d839dbcc9d42f84403c598c7a6e83a93d4c86fc3 100644 --- a/contrib/RemoteSensing/utils/__init__.py +++ b/contrib/RemoteSensing/utils/__init__.py @@ -1,10 +1,11 @@ -# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/RemoteSensing/utils/logging.py b/contrib/RemoteSensing/utils/logging.py index 6d14b1a5df23827c2ddea2a0959801fab6e70552..8c850f618faedcfe97d370941e5d2ec84da1f437 100644 --- a/contrib/RemoteSensing/utils/logging.py +++ b/contrib/RemoteSensing/utils/logging.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/utils/metrics.py b/contrib/RemoteSensing/utils/metrics.py index 7dc09977843eae1af6d98be589954a849f6550aa..71dacd9b9354e42f76af11da2d096de0746c7a31 100644 --- a/contrib/RemoteSensing/utils/metrics.py +++ b/contrib/RemoteSensing/utils/metrics.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/contrib/RemoteSensing/utils/pretrain_weights.py b/contrib/RemoteSensing/utils/pretrain_weights.py index e23686406897bc84e705640640bd7ee17d9d95ec..241e7632229b2c27e91fd6aa9b8c6a240365de2a 100644 --- a/contrib/RemoteSensing/utils/pretrain_weights.py +++ b/contrib/RemoteSensing/utils/pretrain_weights.py @@ -1,3 +1,18 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import os.path as osp diff --git a/contrib/RemoteSensing/utils/utils.py b/contrib/RemoteSensing/utils/utils.py index d9715192b0cd68608e91485d665a62349c24bdfb..c97a76eca2d33d064a882e1190d0bca81fb9acb3 100644 --- a/contrib/RemoteSensing/utils/utils.py +++ b/contrib/RemoteSensing/utils/utils.py @@ -1,4 +1,5 @@ -# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -201,11 +202,9 @@ def load_pretrain_weights(exe, main_prog, weights_dir, fuse_bn=False): vars_to_load.append(var) logging.debug("Weight {} will be load".format(var.name)) - fluid.io.load_vars( - executor=exe, - dirname=weights_dir, - main_program=main_prog, - vars=vars_to_load) + params_dict = fluid.io.load_program_state( + weights_dir, var_list=vars_to_load) + fluid.io.set_program_state(main_prog, params_dict) if len(vars_to_load) == 0: logging.warning( "There is no pretrain weights loaded, maybe you should check you pretrain model!" diff --git a/contrib/RoadLine/__init__.py b/contrib/RoadLine/__init__.py index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0e7c9f39543584630fdaedf13d2879a663a789f0 100644 --- a/contrib/RoadLine/__init__.py +++ b/contrib/RoadLine/__init__.py @@ -0,0 +1,14 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/contrib/RoadLine/config.py b/contrib/RoadLine/config.py index b2e4e5f962ec5d148a59e94d6306271550178246..ce6276ae4c715e4b805f34a3807bbb45b2bc7335 100644 --- a/contrib/RoadLine/config.py +++ b/contrib/RoadLine/config.py @@ -1,4 +1,18 @@ -# -*- coding: utf-8 -*- +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from utils.util import AttrDict, merge_cfg_from_args, get_arguments import os @@ -6,20 +20,20 @@ args = get_arguments() cfg = AttrDict() # 待预测图像所在路径 -cfg.data_dir = os.path.join(args.example , "data", "test_images") +cfg.data_dir = os.path.join(args.example, "data", "test_images") # 待预测图像名称列表 -cfg.data_list_file = os.path.join(args.example , "data", "test.txt") +cfg.data_list_file = os.path.join(args.example, "data", "test.txt") # 模型加载路径 -cfg.model_path = os.path.join(args.example , "model") +cfg.model_path = os.path.join(args.example, "model") # 预测结果保存路径 -cfg.vis_dir = os.path.join(args.example , "result") +cfg.vis_dir = os.path.join(args.example, "result") # 预测类别数 cfg.class_num = 2 # 均值, 图像预处理减去的均值 cfg.MEAN = 127.5, 127.5, 127.5 # 标准差，图像预处理除以标准差 -cfg.STD = 127.5, 127.5, 127.5 +cfg.STD = 127.5, 127.5, 127.5 # 待预测图像输入尺寸 cfg.input_size = 1536, 576 diff --git a/contrib/RoadLine/download_RoadLine.py b/contrib/RoadLine/download_RoadLine.py index 86b631784edadcff6d575c59e67ee23a1775216d..1daff3aad1d1f6241f69b31a0e1444c9fbe71441 100644 --- a/contrib/RoadLine/download_RoadLine.py +++ b/contrib/RoadLine/download_RoadLine.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/contrib/RoadLine/infer.py b/contrib/RoadLine/infer.py index 971476933c431977ce80c73e1d939fe079e1af19..8ffa3766084e95fcf759ae66528ae3ea0eb0d7cf 100644 --- a/contrib/RoadLine/infer.py +++ b/contrib/RoadLine/infer.py @@ -1,4 +1,18 @@ -# -*- coding: utf-8 -*- +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import os import cv2 import numpy as np @@ -12,18 +26,19 @@ config = importlib.import_module('config') cfg = getattr(config, 'cfg') # paddle垃圾回收策略FLAG，ACE2P模型较大，当显存不够时建议开启 -os.environ['FLAGS_eager_delete_tensor_gb']='0.0' +os.environ['FLAGS_eager_delete_tensor_gb'] = '0.0' import paddle.fluid as fluid + # 预测数据集类 class TestDataSet(): def __init__(self): - self.data_dir = cfg.data_dir + self.data_dir = cfg.data_dir self.data_list_file = cfg.data_list_file self.data_list = self.get_data_list() self.data_num = len(self.data_list) - + def get_data_list(self): # 获取预测图像路径列表 data_list = [] @@ -40,7 +55,7 @@ class TestDataSet(): def preprocess(self, img): # 图像预处理 if cfg.example == 'ACE2P': - reader = importlib.import_module(args.example+'.reader') + reader = importlib.import_module(args.example + '.reader') ACE2P_preprocess = getattr(reader, 'preprocess') img = ACE2P_preprocess(img) else: @@ -56,10 +71,10 @@ class TestDataSet(): img_path = self.data_list[index] img = cv2.imread(img_path, cv2.IMREAD_COLOR) if img is None: - return img, img,img_path, None + return img, img, img_path, None img_name = img_path.split(os.sep)[-1] - name_prefix = img_name.replace('.'+img_name.split('.')[-1],'') + name_prefix = img_name.replace('.' + img_name.split('.')[-1], '') img_shape = img.shape[:2] img_process = self.preprocess(img) @@ -90,39 +105,44 @@ def infer(): if image is None: print(im_name, 'is None') continue - + # 预测 if cfg.example == 'ACE2P': # ACE2P模型使用多尺度预测 - reader = importlib.import_module(args.example+'.reader') + reader = importlib.import_module(args.example + '.reader') multi_scale_test = getattr(reader, 'multi_scale_test') - parsing, logits = multi_scale_test(exe, test_prog, feed_name, fetch_list, image, im_shape) + parsing, logits = multi_scale_test(exe, test_prog, feed_name, + fetch_list, image, im_shape) else: # HumanSeg,RoadLine模型单尺度预测 - result = exe.run(program=test_prog, feed={feed_name[0]: image}, fetch_list=fetch_list) + result = exe.run( + program=test_prog, + feed={feed_name[0]: image}, + fetch_list=fetch_list) parsing = np.argmax(result[0][0], axis=0) parsing = cv2.resize(parsing.astype(np.uint8), im_shape[::-1]) - + # 预测结果保存 result_path = os.path.join(cfg.vis_dir, im_name + '.png') if cfg.example == 'HumanSeg': - logits = result[0][0][1]*255 + logits = result[0][0][1] * 255 logits = cv2.resize(logits, im_shape[::-1]) ret, logits = cv2.threshold(logits, thresh, 0, cv2.THRESH_TOZERO) - logits = 255 *(logits - thresh)/(255 - thresh) + logits = 255 * (logits - thresh) / (255 - thresh) # 将分割结果添加到alpha通道 - rgba = np.concatenate((ori_img, np.expand_dims(logits, axis=2)), axis=2) + rgba = np.concatenate((ori_img, np.expand_dims(logits, axis=2)), + axis=2) cv2.imwrite(result_path, rgba) - else: + else: output_im = PILImage.fromarray(np.asarray(parsing, dtype=np.uint8)) output_im.putpalette(palette) output_im.save(result_path) if (idx + 1) % 100 == 0: print('%d processd' % (idx + 1)) - - print('%d processd done' % (idx + 1)) - + + print('%d processd done' % (idx + 1)) + return 0 diff --git a/contrib/RoadLine/utils/__init__.py b/contrib/RoadLine/utils/__init__.py index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0e7c9f39543584630fdaedf13d2879a663a789f0 100644 --- a/contrib/RoadLine/utils/__init__.py +++ b/contrib/RoadLine/utils/__init__.py @@ -0,0 +1,14 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/contrib/RoadLine/utils/palette.py b/contrib/RoadLine/utils/palette.py index 2186203cbc2789f6eff70dfd92f724b4fe16cdb7..6c851497e7156cc76aa37f93c992b358f1aff31b 100644 --- a/contrib/RoadLine/utils/palette.py +++ b/contrib/RoadLine/utils/palette.py @@ -1,12 +1,18 @@ -##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -## Created by: RainbowSecret -## Microsoft Research -## yuyua@microsoft.com -## Copyright (c) 2018 -## -## This source code is licensed under the MIT-style license found in the -## LICENSE file in the root directory of this source tree -##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from __future__ import absolute_import from __future__ import division from __future__ import print_function diff --git a/contrib/RoadLine/utils/util.py b/contrib/RoadLine/utils/util.py index 7394870e7c94c1fb16169e314696b931eecdc3b2..955eb02b63298d0d36ebd23a92cec06b00a34a58 100644 --- a/contrib/RoadLine/utils/util.py +++ b/contrib/RoadLine/utils/util.py @@ -1,18 +1,32 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from __future__ import division from __future__ import print_function from __future__ import unicode_literals import argparse import os + def get_arguments(): parser = argparse.ArgumentParser() - parser.add_argument("--use_gpu", - action="store_true", - help="Use gpu or cpu to test.") - parser.add_argument('--example', - type=str, - help='RoadLine, HumanSeg or ACE2P') - + parser.add_argument( + "--use_gpu", action="store_true", help="Use gpu or cpu to test.") + parser.add_argument( + '--example', type=str, help='RoadLine, HumanSeg or ACE2P') + return parser.parse_args() @@ -34,6 +48,7 @@ class AttrDict(dict): else: self[name] = value + def merge_cfg_from_args(args, cfg): """Merge config keys, values in args into the global config.""" for k, v in vars(args).items(): @@ -44,4 +59,3 @@ def merge_cfg_from_args(args, cfg): value = v if value is not None: cfg[k] = value - diff --git a/dataset/convert_voc2012.py b/dataset/convert_voc2012.py index 1b7de80fb2131a6b6814870c2bc13fc4af1167ca..cce8aef6013d535004a05e2d1254fae74170628d 100644 --- a/dataset/convert_voc2012.py +++ b/dataset/convert_voc2012.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, @@ -20,6 +21,8 @@ from PIL import Image import glob LOCAL_PATH = os.path.dirname(os.path.abspath(__file__)) + + def remove_colormap(filename): gray_anno = np.array(Image.open(filename)) return gray_anno @@ -30,6 +33,7 @@ def save_annotation(annotation, filename): annotation = Image.fromarray(annotation) annotation.save(filename) + def convert_list(origin_file, seg_file, output_folder): with open(seg_file, 'w') as fid_seg: with open(origin_file) as fid_ori: @@ -43,6 +47,7 @@ def convert_list(origin_file, seg_file, output_folder): new_line = ' '.join([img_name, anno_name]) fid_seg.write(new_line + "\n") + if __name__ == "__main__": pascal_root = "./VOCtrainval_11-May-2012/VOC2012" pascal_root = os.path.join(LOCAL_PATH, pascal_root) @@ -54,7 +59,7 @@ if __name__ == "__main__": # 标注图转换后存储目录 output_folder = os.path.join(pascal_root, "SegmentationClassAug") - + print("annotation convert and file list convert") if not os.path.exists(os.path.join(LOCAL_PATH, output_folder)): os.mkdir(os.path.join(LOCAL_PATH, output_folder)) @@ -67,5 +72,5 @@ if __name__ == "__main__": convert_list(train_path, train_path.replace('txt', 'list'), output_folder) convert_list(val_path, val_path.replace('txt', 'list'), output_folder) - convert_list(trainval_path, trainval_path.replace('txt', 'list'), output_folder) - + convert_list(trainval_path, trainval_path.replace('txt', 'list'), + output_folder) diff --git a/dataset/download_and_convert_voc2012.py b/dataset/download_and_convert_voc2012.py index eef2e5de9eb68e131d03e7ec1dca4050281888fc..fd71f54e4d528138ee985b8051101ba679e5eaa9 100644 --- a/dataset/download_and_convert_voc2012.py +++ b/dataset/download_and_convert_voc2012.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, @@ -28,12 +29,12 @@ from convert_voc2012 import remove_colormap from convert_voc2012 import save_annotation - def download_VOC_dataset(savepath, extrapath): url = "https://paddleseg.bj.bcebos.com/dataset/VOCtrainval_11-May-2012.tar" download_file_and_uncompress( url=url, savepath=savepath, extrapath=extrapath) + if __name__ == "__main__": download_VOC_dataset(LOCAL_PATH, LOCAL_PATH) print("Dataset download finish!") @@ -45,10 +46,10 @@ if __name__ == "__main__": train_path = os.path.join(txt_folder, "train.txt") val_path = os.path.join(txt_folder, "val.txt") trainval_path = os.path.join(txt_folder, "trainval.txt") - + # 标注图转换后存储目录 output_folder = os.path.join(pascal_root, "SegmentationClassAug") - + print("annotation convert and file list convert") if not os.path.exists(output_folder): os.mkdir(output_folder) @@ -61,5 +62,5 @@ if __name__ == "__main__": convert_list(train_path, train_path.replace('txt', 'list'), output_folder) convert_list(val_path, val_path.replace('txt', 'list'), output_folder) - convert_list(trainval_path, trainval_path.replace('txt', 'list'), output_folder) - + convert_list(trainval_path, trainval_path.replace('txt', 'list'), + output_folder) diff --git a/dataset/download_cityscapes.py b/dataset/download_cityscapes.py index ee25359e106ff634d28fe77f17f51f975168c228..df88c4d17a3ceeeedac98d58f2b9f60559db4a93 100644 --- a/dataset/download_cityscapes.py +++ b/dataset/download_cityscapes.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/dataset/download_mini_deepglobe_road_extraction.py b/dataset/download_mini_deepglobe_road_extraction.py index 13312407434b7186a782a99d38c9281c5c006c32..6efbba37fbdd2f97346b0bda9c7eec2802a9ed7f 100644 --- a/dataset/download_mini_deepglobe_road_extraction.py +++ b/dataset/download_mini_deepglobe_road_extraction.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/dataset/download_optic.py b/dataset/download_optic.py index 2fd66be11ef2e0bca483ecf6d7bcec2b01bebd7a..d71e743c6cdcdd156d9cf504b76adea9b95ec9b0 100644 --- a/dataset/download_optic.py +++ b/dataset/download_optic.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/dataset/download_pet.py b/dataset/download_pet.py index e0473527e6de19c1841a0f5c1590ea576acbafaa..7214d5b387a472362b0a38cdda0f3164562ff615 100644 --- a/dataset/download_pet.py +++ b/dataset/download_pet.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/deploy/python/infer.py b/deploy/python/infer.py index 19a21a3f33917631c7a20858a2c7067b5e2e02be..05e84eb1012e1ba276fbb03fbc657e12e16fe31e 100644 --- a/deploy/python/infer.py +++ b/deploy/python/infer.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -29,9 +29,9 @@ from concurrent.futures import ThreadPoolExecutor, as_completed gflags.DEFINE_string("conf", default="", help="Configuration File Path") gflags.DEFINE_string("input_dir", default="", help="Directory of Input Images") -gflags.DEFINE_boolean("use_pr", default=False, help="Use optimized model") gflags.DEFINE_string("trt_mode", default="", help="Use optimized model") -gflags.DEFINE_string("ext", default=".jpeg|.jpg", help="Input Image File Extensions") +gflags.DEFINE_string( + "ext", default=".jpeg|.jpg", help="Input Image File Extensions") gflags.FLAGS = gflags.FLAGS @@ -103,6 +103,9 @@ class DeployConfig: self.batch_size = deploy_conf["BATCH_SIZE"] # 9. channels self.channels = deploy_conf["CHANNELS"] + # 10. use_pr + self.use_pr = deploy_conf["USE_PR"] + class ImageReader: @@ -257,23 +260,24 @@ class Predictor: # record starting time point total_start = time.time() batch_size = self.config.batch_size + use_pr = self.config.use_pr for i in range(0, len(images), batch_size): real_batch_size = batch_size if i + batch_size >= len(images): real_batch_size = len(images) - i reader_start = time.time() img_datas = self.image_reader.process(images[i:i + real_batch_size], - gflags.FLAGS.use_pr) + use_pr) input_data = np.concatenate([item[1] for item in img_datas]) input_data = self.create_tensor( - input_data, real_batch_size, use_pr=gflags.FLAGS.use_pr) + input_data, real_batch_size, use_pr=use_pr) reader_end = time.time() infer_start = time.time() output_data = self.predictor.run(input_data)[0] infer_end = time.time() output_data = output_data.as_ndarray() post_start = time.time() - self.output_result(img_datas, output_data, gflags.FLAGS.use_pr) + self.output_result(img_datas, output_data, use_pr) post_end = time.time() reader_time += (reader_end - reader_start) infer_time += (infer_end - infer_start) diff --git a/pdseg/__init__.py b/pdseg/__init__.py index e1cb8ed082023155b95e6b6778b797a571b20ca8..b5932a9046b93599e7fbbbdeb735e494f626c8e8 100644 --- a/pdseg/__init__.py +++ b/pdseg/__init__.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -14,4 +14,4 @@ # limitations under the License. import models import utils -from . import tools \ No newline at end of file +from . import tools diff --git a/pdseg/check.py b/pdseg/check.py index 78080306efad0dc6ab8589b64bd996ef207dfee1..5ff340f85d4947bba439a79049b3aa2131f6f8f0 100644 --- a/pdseg/check.py +++ b/pdseg/check.py @@ -1,4 +1,17 @@ # coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. from __future__ import absolute_import from __future__ import division @@ -427,12 +440,17 @@ def max_img_size_statistics(): logger.info("max width and max height of images are ({},{})".format( max_width, max_height)) + def num_classes_loss_matching_check(): loss_type = cfg.SOLVER.LOSS num_classes = cfg.DATASET.NUM_CLASSES - if num_classes > 2 and (("dice_loss" in loss_type) or ("bce_loss" in loss_type)): - logger.info(error_print("loss check." - " Dice loss and bce loss is only applicable to binary classfication")) + if num_classes > 2 and (("dice_loss" in loss_type) or + ("bce_loss" in loss_type)): + logger.info( + error_print( + "loss check." + " Dice loss and bce loss is only applicable to binary classfication" + )) else: logger.info(correct_print("loss check")) diff --git a/pdseg/data_aug.py b/pdseg/data_aug.py index ae976bf7e4bb6751ba6ec4186a137cbf5644ce84..f3d89edfdf277fdba8c61763683160a30b7e8b6e 100644 --- a/pdseg/data_aug.py +++ b/pdseg/data_aug.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -362,7 +362,7 @@ def hsv_color_jitter(crop_img, saturation_jitter_ratio > 0 or \ contrast_jitter_ratio > 0: crop_img = random_jitter(crop_img, saturation_jitter_ratio, - brightness_jitter_ratio, contrast_jitter_ratio) + brightness_jitter_ratio, contrast_jitter_ratio) return crop_img @@ -391,7 +391,7 @@ def rand_crop(crop_img, crop_seg, mode=ModelPhase.TRAIN): crop_width = cfg.EVAL_CROP_SIZE[0] crop_height = cfg.EVAL_CROP_SIZE[1] - if not ModelPhase.is_train(mode): + if not ModelPhase.is_train(mode): if (crop_height < img_height or crop_width < img_width): raise Exception( "Crop size({},{}) must large than img size({},{}) when in EvalPhase." diff --git a/pdseg/data_utils.py b/pdseg/data_utils.py index 65bea35f1ade62289e704271a6a37af27c8c2c7c..b45db8f41f68bd51af5e52cd811606c8027a36c1 100644 --- a/pdseg/data_utils.py +++ b/pdseg/data_utils.py @@ -1,3 +1,17 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. """ This code is based on https://github.com/fchollet/keras/blob/master/keras/utils/data_utils.py """ @@ -14,10 +28,10 @@ except ImportError: class GeneratorEnqueuer(object): """ - Multiple generators + Multiple generators Args: - generators: + generators: wait_time (float): time to sleep in-between calls to `put()`. """ diff --git a/pdseg/eval.py b/pdseg/eval.py index 426e52f9287bbdb5e4b2e2a4bb617ee910aeff5e..f39764f7d5acc3ad7932b9e9683bbb178b8940b1 100644 --- a/pdseg/eval.py +++ b/pdseg/eval.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -22,13 +22,9 @@ import os os.environ['FLAGS_eager_delete_tensor_gb'] = "0.0" import sys -import time import argparse -import functools import pprint -import cv2 import numpy as np -import paddle import paddle.fluid as fluid from utils.config import cfg @@ -116,7 +112,10 @@ def evaluate(cfg, ckpt_dir=None, use_gpu=False, use_mpio=False, **kwargs): if ckpt_dir is not None: print('load test model:', ckpt_dir) - fluid.io.load_params(exe, ckpt_dir, main_program=test_prog) + try: + fluid.load(test_prog, os.path.join(ckpt_dir, 'model'), exe) + except: + fluid.io.load_params(exe, ckpt_dir, main_program=test_prog) # Use streaming confusion matrix to calculate mean_iou np.set_printoptions( diff --git a/pdseg/export_model.py b/pdseg/export_model.py index 93e4b4949fa3f18c934844edbad4693813e67f15..ae71d43bade325b5c3f5fda66f8e26eecf0e9e09 100644 --- a/pdseg/export_model.py +++ b/pdseg/export_model.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -49,6 +49,7 @@ def parse_args(): sys.exit(1) return parser.parse_args() + def export_inference_config(): deploy_cfg = '''DEPLOY: USE_GPU : 1 @@ -66,9 +67,8 @@ def export_inference_config(): PREDICTOR_MODE : "ANALYSIS" BATCH_SIZE : 1 ''' % (cfg.FREEZE.SAVE_DIR, cfg.FREEZE.MODEL_FILENAME, - cfg.FREEZE.PARAMS_FILENAME, cfg.EVAL_CROP_SIZE, - cfg.MEAN, cfg.STD, cfg.DATASET.IMAGE_TYPE, - cfg.DATASET.NUM_CLASSES, len(cfg.STD)) + cfg.FREEZE.PARAMS_FILENAME, cfg.EVAL_CROP_SIZE, cfg.MEAN, cfg.STD, + cfg.DATASET.IMAGE_TYPE, cfg.DATASET.NUM_CLASSES, len(cfg.STD)) if not os.path.exists(cfg.FREEZE.SAVE_DIR): os.mkdir(cfg.FREEZE.SAVE_DIR) yaml_path = os.path.join(cfg.FREEZE.SAVE_DIR, 'deploy.yaml') @@ -94,7 +94,13 @@ def export_inference_model(args): infer_prog = infer_prog.clone(for_test=True) if os.path.exists(cfg.TEST.TEST_MODEL): - fluid.io.load_params(exe, cfg.TEST.TEST_MODEL, main_program=infer_prog) + print('load test model:', cfg.TEST.TEST_MODEL) + try: + fluid.load(infer_prog, os.path.join(cfg.TEST.TEST_MODEL, 'model'), + exe) + except: + fluid.io.load_params( + exe, cfg.TEST.TEST_MODEL, main_program=infer_prog) else: print("TEST.TEST_MODEL diretory is empty!") exit(-1) diff --git a/pdseg/loss.py b/pdseg/loss.py index bfd1c83f0a4673cc627c5296d586d9a6f2f31c40..bd8406102a0b942bf4b3d2bd48caba3f57b153bf 100644 --- a/pdseg/loss.py +++ b/pdseg/loss.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/lovasz_losses.py b/pdseg/lovasz_losses.py index 5f2283583972945ca3d70233a684833ed8902d6c..c6ffe66aaf4eaa2880ba2b8c6bfb70d200cb09c7 100755 --- a/pdseg/lovasz_losses.py +++ b/pdseg/lovasz_losses.py @@ -1,4 +1,4 @@ -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/metrics.py b/pdseg/metrics.py index 2898be028f3dfa03ad9892310da89f7695829542..f7bab020ab44131f5d46643cf0522dd6acf483ee 100644 --- a/pdseg/metrics.py +++ b/pdseg/metrics.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/models/__init__.py b/pdseg/models/__init__.py index f1465913991c5aaffefff26c1f5a5d668edd1596..2bff3261bd329ffa4352106c36e290cc4718c2ca 100644 --- a/pdseg/models/__init__.py +++ b/pdseg/models/__init__.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/models/backbone/__init__.py b/pdseg/models/backbone/__init__.py index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0e7c9f39543584630fdaedf13d2879a663a789f0 100644 --- a/pdseg/models/backbone/__init__.py +++ b/pdseg/models/backbone/__init__.py @@ -0,0 +1,14 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/pdseg/models/backbone/mobilenet_v2.py b/pdseg/models/backbone/mobilenet_v2.py index 740284b319bd836d9c27682c1c22d556d2b98aa1..eefeba8d156e1553eb79c231e4d9302b452679ee 100644 --- a/pdseg/models/backbone/mobilenet_v2.py +++ b/pdseg/models/backbone/mobilenet_v2.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/models/backbone/resnet.py b/pdseg/models/backbone/resnet.py index 6eb9f12bc33c97f42664327ada3712c8283943b1..60a7bc5dcc9f76a8f4af78ae0c795e7aa72711c8 100644 --- a/pdseg/models/backbone/resnet.py +++ b/pdseg/models/backbone/resnet.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -141,7 +141,7 @@ class ResNet(): else: conv_name = "res" + str(block + 2) + chr(97 + i) dilation_rate = get_dilated_rate(dilation_dict, block) - + conv = self.bottleneck_block( input=conv, num_filters=int(num_filters[block] * self.scale), @@ -215,11 +215,11 @@ class ResNet(): groups=1, act=None, name=None): - + if self.stem == 'pspnet': - bias_attr=ParamAttr(name=name + "_biases") + bias_attr = ParamAttr(name=name + "_biases") else: - bias_attr=False + bias_attr = False conv = fluid.layers.conv2d( input=input, @@ -238,13 +238,15 @@ class ResNet(): bn_name = "bn_" + name else: bn_name = "bn" + name[3:] - return fluid.layers.batch_norm(input=conv, - act=act, - name=bn_name + '.output.1', - param_attr=ParamAttr(name=bn_name + '_scale'), - bias_attr=ParamAttr(bn_name + '_offset'), - moving_mean_name=bn_name + '_mean', - moving_variance_name=bn_name + '_variance', ) + return fluid.layers.batch_norm( + input=conv, + act=act, + name=bn_name + '.output.1', + param_attr=ParamAttr(name=bn_name + '_scale'), + bias_attr=ParamAttr(bn_name + '_offset'), + moving_mean_name=bn_name + '_mean', + moving_variance_name=bn_name + '_variance', + ) def shortcut(self, input, ch_out, stride, is_first, name): ch_in = input.shape[1] @@ -258,7 +260,7 @@ class ResNet(): strides = [1, stride] else: strides = [stride, 1] - + conv0 = self.conv_bn_layer( input=input, num_filters=num_filters, diff --git a/pdseg/models/backbone/vgg.py b/pdseg/models/backbone/vgg.py index 7e9df0a66cd85b291aad8846eed30c9bb7b4e947..443fa43556a22187dad291e0c664caa180e595c8 100644 --- a/pdseg/models/backbone/vgg.py +++ b/pdseg/models/backbone/vgg.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -55,7 +55,8 @@ class VGGNet(): channels = [64, 128, 256, 512, 512] conv = input for i in range(len(nums)): - conv = self.conv_block(conv, channels[i], nums[i], name="conv" + str(i + 1) + "_") + conv = self.conv_block( + conv, channels[i], nums[i], name="conv" + str(i + 1) + "_") layers_count += nums[i] if check_points(layers_count, decode_points): short_cuts[layers_count] = conv diff --git a/pdseg/models/backbone/xception.py b/pdseg/models/backbone/xception.py index 5c07f240625744356c5df4644342cff6c81af687..d45adc21af495729a94aa0694e660090f4ade34d 100644 --- a/pdseg/models/backbone/xception.py +++ b/pdseg/models/backbone/xception.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/models/libs/__init__.py b/pdseg/models/libs/__init__.py index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0e7c9f39543584630fdaedf13d2879a663a789f0 100644 --- a/pdseg/models/libs/__init__.py +++ b/pdseg/models/libs/__init__.py @@ -0,0 +1,14 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/pdseg/models/libs/model_libs.py b/pdseg/models/libs/model_libs.py index 84494a9dd892105c799119c7a467b584c23f4241..dbd04dea9eaebcfcadc4c3a86c3bac6371d37479 100644 --- a/pdseg/models/libs/model_libs.py +++ b/pdseg/models/libs/model_libs.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -197,4 +197,4 @@ def conv_bn_layer(input, if if_act: return fluid.layers.relu6(bn) else: - return bn \ No newline at end of file + return bn diff --git a/pdseg/models/model_builder.py b/pdseg/models/model_builder.py index 74f2216baca2629a23b752742afdf70dbb0ece12..67b78c1a01cef4f5741058cf567682d8f6f3768d 100644 --- a/pdseg/models/model_builder.py +++ b/pdseg/models/model_builder.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/models/modeling/__init__.py b/pdseg/models/modeling/__init__.py index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0e7c9f39543584630fdaedf13d2879a663a789f0 100644 --- a/pdseg/models/modeling/__init__.py +++ b/pdseg/models/modeling/__init__.py @@ -0,0 +1,14 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/pdseg/models/modeling/deeplab.py b/pdseg/models/modeling/deeplab.py index 186e2406d90d291de43133550875072d790a805f..0d2ed92deb206deece072c7cf9a8a28842ee4bd1 100644 --- a/pdseg/models/modeling/deeplab.py +++ b/pdseg/models/modeling/deeplab.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/models/modeling/fast_scnn.py b/pdseg/models/modeling/fast_scnn.py index 3d8301cd7933f01c1ace7ff1e538d1736d7e79d6..99019dc6e07eecb30e9f467d567d7270f6b3ec72 100644 --- a/pdseg/models/modeling/fast_scnn.py +++ b/pdseg/models/modeling/fast_scnn.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/models/modeling/hrnet.py b/pdseg/models/modeling/hrnet.py index 4b95461a1adf5c96cd8737540b3509944ea7900e..19d687ab02a46666f2efcd74e72c7a6f307c2c92 100644 --- a/pdseg/models/modeling/hrnet.py +++ b/pdseg/models/modeling/hrnet.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -25,7 +25,14 @@ from paddle.fluid.param_attr import ParamAttr from utils.config import cfg -def conv_bn_layer(input, filter_size, num_filters, stride=1, padding=1, num_groups=1, if_act=True, name=None): +def conv_bn_layer(input, + filter_size, + num_filters, + stride=1, + padding=1, + num_groups=1, + if_act=True, + name=None): conv = fluid.layers.conv2d( input=input, num_filters=num_filters, @@ -37,37 +44,74 @@ def conv_bn_layer(input, filter_size, num_filters, stride=1, padding=1, num_grou param_attr=ParamAttr(initializer=MSRA(), name=name + '_weights'), bias_attr=False) bn_name = name + '_bn' - bn = fluid.layers.batch_norm(input=conv, - param_attr=ParamAttr(name=bn_name + "_scale", - initializer=fluid.initializer.Constant(1.0)), - bias_attr=ParamAttr(name=bn_name + "_offset", - initializer=fluid.initializer.Constant(0.0)), - moving_mean_name=bn_name + '_mean', - moving_variance_name=bn_name + '_variance') + bn = fluid.layers.batch_norm( + input=conv, + param_attr=ParamAttr( + name=bn_name + "_scale", + initializer=fluid.initializer.Constant(1.0)), + bias_attr=ParamAttr( + name=bn_name + "_offset", + initializer=fluid.initializer.Constant(0.0)), + moving_mean_name=bn_name + '_mean', + moving_variance_name=bn_name + '_variance') if if_act: bn = fluid.layers.relu(bn) return bn + def basic_block(input, num_filters, stride=1, downsample=False, name=None): residual = input - conv = conv_bn_layer(input=input, filter_size=3, num_filters=num_filters, stride=stride, name=name + '_conv1') - conv = conv_bn_layer(input=conv, filter_size=3, num_filters=num_filters, if_act=False, name=name + '_conv2') + conv = conv_bn_layer( + input=input, + filter_size=3, + num_filters=num_filters, + stride=stride, + name=name + '_conv1') + conv = conv_bn_layer( + input=conv, + filter_size=3, + num_filters=num_filters, + if_act=False, + name=name + '_conv2') if downsample: - residual = conv_bn_layer(input=input, filter_size=1, num_filters=num_filters, if_act=False, - name=name + '_downsample') + residual = conv_bn_layer( + input=input, + filter_size=1, + num_filters=num_filters, + if_act=False, + name=name + '_downsample') return fluid.layers.elementwise_add(x=residual, y=conv, act='relu') + def bottleneck_block(input, num_filters, stride=1, downsample=False, name=None): residual = input - conv = conv_bn_layer(input=input, filter_size=1, num_filters=num_filters, name=name + '_conv1') - conv = conv_bn_layer(input=conv, filter_size=3, num_filters=num_filters, stride=stride, name=name + '_conv2') - conv = conv_bn_layer(input=conv, filter_size=1, num_filters=num_filters * 4, if_act=False, - name=name + '_conv3') + conv = conv_bn_layer( + input=input, + filter_size=1, + num_filters=num_filters, + name=name + '_conv1') + conv = conv_bn_layer( + input=conv, + filter_size=3, + num_filters=num_filters, + stride=stride, + name=name + '_conv2') + conv = conv_bn_layer( + input=conv, + filter_size=1, + num_filters=num_filters * 4, + if_act=False, + name=name + '_conv3') if downsample: - residual = conv_bn_layer(input=input, filter_size=1, num_filters=num_filters * 4, if_act=False, - name=name + '_downsample') + residual = conv_bn_layer( + input=input, + filter_size=1, + num_filters=num_filters * 4, + if_act=False, + name=name + '_downsample') return fluid.layers.elementwise_add(x=residual, y=conv, act='relu') + def fuse_layers(x, channels, multi_scale_output=True, name=None): out = [] for i in range(len(channels) if multi_scale_output else 1): @@ -77,40 +121,64 @@ def fuse_layers(x, channels, multi_scale_output=True, name=None): height = shape[-2] for j in range(len(channels)): if j > i: - y = conv_bn_layer(x[j], filter_size=1, num_filters=channels[i], if_act=False, - name=name + '_layer_' + str(i + 1) + '_' + str(j + 1)) - y = fluid.layers.resize_bilinear(input=y, out_shape=[height, width]) - residual = fluid.layers.elementwise_add(x=residual, y=y, act=None) + y = conv_bn_layer( + x[j], + filter_size=1, + num_filters=channels[i], + if_act=False, + name=name + '_layer_' + str(i + 1) + '_' + str(j + 1)) + y = fluid.layers.resize_bilinear( + input=y, out_shape=[height, width]) + residual = fluid.layers.elementwise_add( + x=residual, y=y, act=None) elif j < i: y = x[j] for k in range(i - j): if k == i - j - 1: - y = conv_bn_layer(y, filter_size=3, num_filters=channels[i], stride=2, if_act=False, - name=name + '_layer_' + str(i + 1) + '_' + str(j + 1) + '_' + str(k + 1)) + y = conv_bn_layer( + y, + filter_size=3, + num_filters=channels[i], + stride=2, + if_act=False, + name=name + '_layer_' + str(i + 1) + '_' + + str(j + 1) + '_' + str(k + 1)) else: - y = conv_bn_layer(y, filter_size=3, num_filters=channels[j], stride=2, - name=name + '_layer_' + str(i + 1) + '_' + str(j + 1) + '_' + str(k + 1)) - residual = fluid.layers.elementwise_add(x=residual, y=y, act=None) + y = conv_bn_layer( + y, + filter_size=3, + num_filters=channels[j], + stride=2, + name=name + '_layer_' + str(i + 1) + '_' + + str(j + 1) + '_' + str(k + 1)) + residual = fluid.layers.elementwise_add( + x=residual, y=y, act=None) residual = fluid.layers.relu(residual) out.append(residual) return out + def branches(x, block_num, channels, name=None): out = [] for i in range(len(channels)): residual = x[i] for j in range(block_num): - residual = basic_block(residual, channels[i], - name=name + '_branch_layer_' + str(i + 1) + '_' + str(j + 1)) + residual = basic_block( + residual, + channels[i], + name=name + '_branch_layer_' + str(i + 1) + '_' + str(j + 1)) out.append(residual) return out + def high_resolution_module(x, channels, multi_scale_output=True, name=None): residual = branches(x, 4, channels, name=name) - out = fuse_layers(residual, channels, multi_scale_output=multi_scale_output, name=name) + out = fuse_layers( + residual, channels, multi_scale_output=multi_scale_output, name=name) return out + def transition_layer(x, in_channels, out_channels, name=None): num_in = len(in_channels) num_out = len(out_channels) @@ -118,46 +186,76 @@ def transition_layer(x, in_channels, out_channels, name=None): for i in range(num_out): if i < num_in: if in_channels[i] != out_channels[i]: - residual = conv_bn_layer(x[i], filter_size=3, num_filters=out_channels[i], - name=name + '_layer_' + str(i + 1)) + residual = conv_bn_layer( + x[i], + filter_size=3, + num_filters=out_channels[i], + name=name + '_layer_' + str(i + 1)) out.append(residual) else: out.append(x[i]) else: - residual = conv_bn_layer(x[-1], filter_size=3, num_filters=out_channels[i], stride=2, - name=name + '_layer_' + str(i + 1)) + residual = conv_bn_layer( + x[-1], + filter_size=3, + num_filters=out_channels[i], + stride=2, + name=name + '_layer_' + str(i + 1)) out.append(residual) return out + def stage(x, num_modules, channels, multi_scale_output=True, name=None): out = x for i in range(num_modules): if i == num_modules - 1 and multi_scale_output == False: - out = high_resolution_module(out, channels, multi_scale_output=False, name=name + '_' + str(i + 1)) + out = high_resolution_module( + out, + channels, + multi_scale_output=False, + name=name + '_' + str(i + 1)) else: - out = high_resolution_module(out, channels, name=name + '_' + str(i + 1)) + out = high_resolution_module( + out, channels, name=name + '_' + str(i + 1)) return out + def layer1(input, name=None): conv = input for i in range(4): - conv = bottleneck_block(conv, num_filters=64, downsample=True if i == 0 else False, - name=name + '_' + str(i + 1)) + conv = bottleneck_block( + conv, + num_filters=64, + downsample=True if i == 0 else False, + name=name + '_' + str(i + 1)) return conv + def high_resolution_net(input, num_classes): - + channels_2 = cfg.MODEL.HRNET.STAGE2.NUM_CHANNELS channels_3 = cfg.MODEL.HRNET.STAGE3.NUM_CHANNELS channels_4 = cfg.MODEL.HRNET.STAGE4.NUM_CHANNELS - + num_modules_2 = cfg.MODEL.HRNET.STAGE2.NUM_MODULES num_modules_3 = cfg.MODEL.HRNET.STAGE3.NUM_MODULES num_modules_4 = cfg.MODEL.HRNET.STAGE4.NUM_MODULES - x = conv_bn_layer(input=input, filter_size=3, num_filters=64, stride=2, if_act=True, name='layer1_1') - x = conv_bn_layer(input=x, filter_size=3, num_filters=64, stride=2, if_act=True, name='layer1_2') + x = conv_bn_layer( + input=input, + filter_size=3, + num_filters=64, + stride=2, + if_act=True, + name='layer1_1') + x = conv_bn_layer( + input=x, + filter_size=3, + num_filters=64, + stride=2, + if_act=True, + name='layer1_2') la1 = layer1(x, name='layer2') tr1 = transition_layer([la1], [256], channels_2, name='tr1') @@ -170,18 +268,21 @@ def high_resolution_net(input, num_classes): # upsample shape = st4[0].shape height, width = shape[-2], shape[-1] - st4[1] = fluid.layers.resize_bilinear( - st4[1], out_shape=[height, width]) - st4[2] = fluid.layers.resize_bilinear( - st4[2], out_shape=[height, width]) - st4[3] = fluid.layers.resize_bilinear( - st4[3], out_shape=[height, width]) + st4[1] = fluid.layers.resize_bilinear(st4[1], out_shape=[height, width]) + st4[2] = fluid.layers.resize_bilinear(st4[2], out_shape=[height, width]) + st4[3] = fluid.layers.resize_bilinear(st4[3], out_shape=[height, width]) out = fluid.layers.concat(st4, axis=1) last_channels = sum(channels_4) - out = conv_bn_layer(input=out, filter_size=1, num_filters=last_channels, stride=1, if_act=True, name='conv-2') - out= fluid.layers.conv2d( + out = conv_bn_layer( + input=out, + filter_size=1, + num_filters=last_channels, + stride=1, + if_act=True, + name='conv-2') + out = fluid.layers.conv2d( input=out, num_filters=num_classes, filter_size=1, @@ -193,7 +294,6 @@ def high_resolution_net(input, num_classes): out = fluid.layers.resize_bilinear(out, input.shape[2:]) - return out @@ -201,6 +301,7 @@ def hrnet(input, num_classes): logit = high_resolution_net(input, num_classes) return logit + if __name__ == '__main__': image_shape = [-1, 3, 769, 769] image = fluid.data(name='image', shape=image_shape, dtype='float32') diff --git a/pdseg/models/modeling/icnet.py b/pdseg/models/modeling/icnet.py index f6364ff282b3feea2b2bebe796d34434f59b18ca..aee0461459ac0b79624a53eb1c96070cb6abe042 100644 --- a/pdseg/models/modeling/icnet.py +++ b/pdseg/models/modeling/icnet.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/models/modeling/pspnet.py b/pdseg/models/modeling/pspnet.py index 8c322b44011f90ac6b29716a51d3e89483bdb3e4..f8c2943af4e08478177f6b1e947d219e7bb1f073 100644 --- a/pdseg/models/modeling/pspnet.py +++ b/pdseg/models/modeling/pspnet.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -24,6 +24,7 @@ from models.libs.model_libs import avg_pool, conv, bn from models.backbone.resnet import ResNet as resnet_backbone from utils.config import cfg + def get_logit_interp(input, num_classes, out_shape, name="logit"): # 根据类别数决定最后一层卷积输出, 并插值回原始尺寸 param_attr = fluid.ParamAttr( @@ -33,16 +34,15 @@ def get_logit_interp(input, num_classes, out_shape, name="logit"): initializer=fluid.initializer.TruncatedNormal(loc=0.0, scale=0.01)) with scope(name): - logit = conv(input, - num_classes, - filter_size=1, - param_attr=param_attr, - bias_attr=True, - name=name+'_conv') + logit = conv( + input, + num_classes, + filter_size=1, + param_attr=param_attr, + bias_attr=True, + name=name + '_conv') logit_interp = fluid.layers.resize_bilinear( - logit, - out_shape=out_shape, - name=name+'_interp') + logit, out_shape=out_shape, name=name + '_interp') return logit_interp @@ -51,40 +51,44 @@ def psp_module(input, out_features): # 输入：backbone输出的特征 # 输出：对输入进行不同尺度pooling, 卷积操作后插值回原始尺寸，并concat # 最后进行一个卷积及BN操作 - + cat_layers = [] - sizes = (1,2,3,6) + sizes = (1, 2, 3, 6) for size in sizes: psp_name = "psp" + str(size) with scope(psp_name): - pool = fluid.layers.adaptive_pool2d(input, - pool_size=[size, size], - pool_type='avg', - name=psp_name+'_adapool') - data = conv(pool, out_features, - filter_size=1, - bias_attr=True, - name= psp_name + '_conv') + pool = fluid.layers.adaptive_pool2d( + input, + pool_size=[size, size], + pool_type='avg', + name=psp_name + '_adapool') + data = conv( + pool, + out_features, + filter_size=1, + bias_attr=True, + name=psp_name + '_conv') data_bn = bn(data, act='relu') - interp = fluid.layers.resize_bilinear(data_bn, - out_shape=input.shape[2:], - name=psp_name+'_interp') + interp = fluid.layers.resize_bilinear( + data_bn, out_shape=input.shape[2:], name=psp_name + '_interp') cat_layers.append(interp) cat_layers = [input] + cat_layers[::-1] cat = fluid.layers.concat(cat_layers, axis=1, name='psp_cat') psp_end_name = "psp_end" with scope(psp_end_name): - data = conv(cat, - out_features, - filter_size=3, - padding=1, - bias_attr=True, - name=psp_end_name) + data = conv( + cat, + out_features, + filter_size=3, + padding=1, + bias_attr=True, + name=psp_end_name) out = bn(data, act='relu') return out + def resnet(input): # PSPNET backbone: resnet, 默认resnet50 # end_points: resnet终止层数 @@ -92,14 +96,14 @@ def resnet(input): scale = cfg.MODEL.PSPNET.DEPTH_MULTIPLIER layers = cfg.MODEL.PSPNET.LAYERS end_points = layers - 1 - dilation_dict = {2:2, 3:4} + dilation_dict = {2: 2, 3: 4} model = resnet_backbone(layers, scale, stem='pspnet') - data, _ = model.net(input, - end_points=end_points, - dilation_dict=dilation_dict) + data, _ = model.net( + input, end_points=end_points, dilation_dict=dilation_dict) return data + def pspnet(input, num_classes): # Backbone: ResNet res = resnet(input) @@ -109,4 +113,3 @@ def pspnet(input, num_classes): # 根据类别数决定最后一层卷积输出, 并插值回原始尺寸 logit = get_logit_interp(dropout, num_classes, input.shape[2:]) return logit - diff --git a/pdseg/models/modeling/unet.py b/pdseg/models/modeling/unet.py index 215737aa658bcd4046ecaa77bb04fd11a329be24..be9b8e5bb2d8a9c36a876e302e8a565971cc15ee 100644 --- a/pdseg/models/modeling/unet.py +++ b/pdseg/models/modeling/unet.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/reader.py b/pdseg/reader.py index 7f1fd6fbbe25f1199c9247aa9e42ae7cb682c03d..6fe395d5a003b2aeeffb7eaafc088c03c1802c1d 100644 --- a/pdseg/reader.py +++ b/pdseg/reader.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -71,7 +71,8 @@ class SegDataset(object): if self.shuffle and cfg.NUM_TRAINERS > 1: np.random.RandomState(self.shuffle_seed).shuffle(self.all_lines) num_lines = len(self.all_lines) // cfg.NUM_TRAINERS - self.lines = self.all_lines[num_lines * cfg.TRAINER_ID: num_lines * (cfg.TRAINER_ID + 1)] + self.lines = self.all_lines[num_lines * cfg.TRAINER_ID:num_lines * + (cfg.TRAINER_ID + 1)] self.shuffle_seed += 1 elif self.shuffle: np.random.shuffle(self.lines) @@ -99,7 +100,8 @@ class SegDataset(object): if self.shuffle and cfg.NUM_TRAINERS > 1: np.random.RandomState(self.shuffle_seed).shuffle(self.all_lines) num_lines = len(self.all_lines) // cfg.NUM_TRAINERS - self.lines = self.all_lines[num_lines * cfg.TRAINER_ID: num_lines * (cfg.TRAINER_ID + 1)] + self.lines = self.all_lines[num_lines * cfg.TRAINER_ID:num_lines * + (cfg.TRAINER_ID + 1)] self.shuffle_seed += 1 elif self.shuffle: np.random.shuffle(self.lines) diff --git a/pdseg/solver.py b/pdseg/solver.py index baec69be06c4c2eb6d5e78480d5ffe9e1c737434..43efcd5b64c50b8021ae6b411099d296e5e8aef7 100644 --- a/pdseg/solver.py +++ b/pdseg/solver.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/tools/__init__.py b/pdseg/tools/__init__.py index a5914a21f76a81bf8589b609b2dac8f0548aace4..0e7c9f39543584630fdaedf13d2879a663a789f0 100644 --- a/pdseg/tools/__init__.py +++ b/pdseg/tools/__init__.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/pdseg/tools/create_dataset_list.py b/pdseg/tools/create_dataset_list.py index 6c7d7c943c9baf916533621d353d5f2700388a01..8dd4c7e9a39163893de2ec4386403cf321cb46e1 100644 --- a/pdseg/tools/create_dataset_list.py +++ b/pdseg/tools/create_dataset_list.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -21,55 +21,48 @@ import warnings def parse_args(): parser = argparse.ArgumentParser( - description='PaddleSeg generate file list on cityscapes or your customized dataset.') - parser.add_argument( - 'dataset_root', - help='dataset root directory', - type=str + description= + 'PaddleSeg generate file list on cityscapes or your customized dataset.' ) + parser.add_argument('dataset_root', help='dataset root directory', type=str) parser.add_argument( '--type', help='dataset type: \n' - '- cityscapes \n' - '- custom(default)', + '- cityscapes \n' + '- custom(default)', default="custom", - type=str - ) + type=str) parser.add_argument( '--separator', dest='separator', help='file list separator', default="|", - type=str - ) + type=str) parser.add_argument( '--folder', help='the folder names of images and labels', type=str, nargs=2, - default=['images', 'annotations'] - ) + default=['images', 'annotations']) parser.add_argument( '--second_folder', - help='the second-level folder names of train set, validation set, test set', + help= + 'the second-level folder names of train set, validation set, test set', type=str, nargs='*', - default=['train', 'val', 'test'] - ) + default=['train', 'val', 'test']) parser.add_argument( '--format', help='data format of images and labels, e.g. jpg or png.', type=str, nargs=2, - default=['jpg', 'png'] - ) + default=['jpg', 'png']) parser.add_argument( '--postfix', help='postfix of images or labels', type=str, nargs=2, - default=['', ''] - ) + default=['', '']) return parser.parse_args() @@ -120,15 +113,17 @@ def generate_list(args): num_images = len(image_files) if not label_files: - label_dir = os.path.join(dataset_root, args.folder[1], dataset_split) + label_dir = os.path.join(dataset_root, args.folder[1], + dataset_split) warnings.warn("No labels in {} !!!".format(label_dir)) num_label = len(label_files) if num_images != num_label and num_label > 0: - raise Exception("Number of images = {} number of labels = {} \n" - "Either number of images is equal to number of labels, " - "or number of labels is equal to 0.\n" - "Please check your dataset!".format(num_images, num_label)) + raise Exception( + "Number of images = {} number of labels = {} \n" + "Either number of images is equal to number of labels, " + "or number of labels is equal to 0.\n" + "Please check your dataset!".format(num_images, num_label)) file_list = os.path.join(dataset_root, dataset_split + '.txt') with open(file_list, "w") as f: diff --git a/pdseg/tools/gray2pseudo_color.py b/pdseg/tools/gray2pseudo_color.py index 3627db0b216175b04a50d9012999d441f4df69fb..a17cd7c2f0b006ff2548b3c1a41c54e5e7647ef9 100644 --- a/pdseg/tools/gray2pseudo_color.py +++ b/pdseg/tools/gray2pseudo_color.py @@ -1,4 +1,18 @@ -# -*- coding: utf-8 -*- +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + from __future__ import print_function import argparse @@ -11,16 +25,12 @@ from PIL import Image def parse_args(): parser = argparse.ArgumentParser( - formatter_class=argparse.ArgumentDefaultsHelpFormatter - ) - parser.add_argument('dir_or_file', - help='input gray label directory or file list path') - parser.add_argument('output_dir', - help='output colorful label directory') - parser.add_argument('--dataset_dir', - help='dataset directory') - parser.add_argument('--file_separator', - help='file list separator') + formatter_class=argparse.ArgumentDefaultsHelpFormatter) + parser.add_argument( + 'dir_or_file', help='input gray label directory or file list path') + parser.add_argument('output_dir', help='output colorful label directory') + parser.add_argument('--dataset_dir', help='dataset directory') + parser.add_argument('--file_separator', help='file list separator') return parser.parse_args() diff --git a/pdseg/tools/jingling2seg.py b/pdseg/tools/jingling2seg.py index 5f031823a14894bdf5244b4d42b4a7dd216b0619..3f1e245d19adae9790005ee748a9e76c99cb3009 100644 --- a/pdseg/tools/jingling2seg.py +++ b/pdseg/tools/jingling2seg.py @@ -1,4 +1,17 @@ -#!/usr/bin/env python +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. from __future__ import print_function diff --git a/pdseg/tools/labelme2seg.py b/pdseg/tools/labelme2seg.py index 3f06e977e9a91418c4eeb060d50f4bd021a6f8ab..9a3ec662f18eb0e49045f2449907ea867cccb816 100755 --- a/pdseg/tools/labelme2seg.py +++ b/pdseg/tools/labelme2seg.py @@ -1,4 +1,17 @@ -#!/usr/bin/env python +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. from __future__ import print_function diff --git a/pdseg/train.py b/pdseg/train.py index e1c498a4355950af155efc79e69a6788ad86e0ba..7021ed9d6ae137c204e05e00d5a165f9859b056e 100644 --- a/pdseg/train.py +++ b/pdseg/train.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -26,9 +26,7 @@ import argparse import pprint import random import shutil -import functools -import paddle import numpy as np import paddle.fluid as fluid from paddle.fluid import profiler @@ -39,10 +37,10 @@ from metrics import ConfusionMatrix from reader import SegDataset from models.model_builder import build_model from models.model_builder import ModelPhase -from models.model_builder import parse_shape_from_file from eval import evaluate from vis import visualize from utils import dist_utils +from utils.load_model_utils import load_pretrained_weights def parse_args(): @@ -118,38 +116,7 @@ def parse_args(): return parser.parse_args() -def save_vars(executor, dirname, program=None, vars=None): - """ - Temporary resolution for Win save variables compatability. - Will fix in PaddlePaddle v1.5.2 - """ - - save_program = fluid.Program() - save_block = save_program.global_block() - - for each_var in vars: - # NOTE: don't save the variable which type is RAW - if each_var.type == fluid.core.VarDesc.VarType.RAW: - continue - new_var = save_block.create_var( - name=each_var.name, - shape=each_var.shape, - dtype=each_var.dtype, - type=each_var.type, - lod_level=each_var.lod_level, - persistable=True) - file_path = os.path.join(dirname, new_var.name) - file_path = os.path.normpath(file_path) - save_block.append_op( - type='save', - inputs={'X': [new_var]}, - outputs={}, - attrs={'file_path': file_path}) - - executor.run(save_program) - - -def save_checkpoint(exe, program, ckpt_name): +def save_checkpoint(program, ckpt_name): """ Save checkpoint for evaluation or resume training """ @@ -158,29 +125,22 @@ def save_checkpoint(exe, program, ckpt_name): if not os.path.isdir(ckpt_dir): os.makedirs(ckpt_dir) - save_vars( - exe, - ckpt_dir, - program, - vars=list(filter(fluid.io.is_persistable, program.list_vars()))) + fluid.save(program, os.path.join(ckpt_dir, 'model')) return ckpt_dir def load_checkpoint(exe, program): """ - Load checkpoiont from pretrained model directory for resume training + Load checkpoiont for resuming training """ - - print('Resume model training from:', cfg.TRAIN.RESUME_MODEL_DIR) - if not os.path.exists(cfg.TRAIN.RESUME_MODEL_DIR): - raise ValueError("TRAIN.PRETRAIN_MODEL {} not exist!".format( - cfg.TRAIN.RESUME_MODEL_DIR)) - - fluid.io.load_persistables( - exe, cfg.TRAIN.RESUME_MODEL_DIR, main_program=program) - model_path = cfg.TRAIN.RESUME_MODEL_DIR + print('Resume model training from:', model_path) + if not os.path.exists(model_path): + raise ValueError( + "TRAIN.PRETRAIN_MODEL {} not exist!".format(model_path)) + fluid.load(program, os.path.join(model_path, 'model'), exe) + # Check is path ended by path spearator if model_path[-1] == os.sep: model_path = model_path[0:-1] @@ -195,7 +155,6 @@ def load_checkpoint(exe, program): else: raise ValueError("Resume model path is not valid!") print("Model checkpoint loaded successfully!") - return begin_epoch @@ -247,8 +206,6 @@ def train(cfg): yield item[0], item[1], item[2] # Get device environment - # places = fluid.cuda_places() if args.use_gpu else fluid.cpu_places() - # place = places[0] gpu_id = int(os.environ.get('FLAGS_selected_gpus', 0)) place = fluid.CUDAPlace(gpu_id) if args.use_gpu else fluid.CPUPlace() places = fluid.cuda_places() if args.use_gpu else fluid.cpu_places() @@ -304,42 +261,7 @@ def train(cfg): begin_epoch = load_checkpoint(exe, train_prog) # Load pretrained model elif os.path.exists(cfg.TRAIN.PRETRAINED_MODEL_DIR): - print_info('Pretrained model dir: ', cfg.TRAIN.PRETRAINED_MODEL_DIR) - load_vars = [] - load_fail_vars = [] - - def var_shape_matched(var, shape): - """ - Check whehter persitable variable shape is match with current network - """ - var_exist = os.path.exists( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - if var_exist: - var_shape = parse_shape_from_file( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - return var_shape == shape - return False - - for x in train_prog.list_vars(): - if isinstance(x, fluid.framework.Parameter): - shape = tuple(fluid.global_scope().find_var( - x.name).get_tensor().shape()) - if var_shape_matched(x, shape): - load_vars.append(x) - else: - load_fail_vars.append(x) - - fluid.io.load_vars( - exe, dirname=cfg.TRAIN.PRETRAINED_MODEL_DIR, vars=load_vars) - for var in load_vars: - print_info("Parameter[{}] loaded sucessfully!".format(var.name)) - for var in load_fail_vars: - print_info( - "Parameter[{}] don't exist or shape does not match current network, skip" - " to load it.".format(var.name)) - print_info("{}/{} pretrained parameters loaded successfully!".format( - len(load_vars), - len(load_vars) + len(load_fail_vars))) + load_pretrained_weights(exe, train_prog, cfg.TRAIN.PRETRAINED_MODEL_DIR) else: print_info( 'Pretrained model dir {} not exists, training from scratch...'. @@ -418,12 +340,9 @@ def train(cfg): step) log_writer.add_scalar('Train/mean_acc', mean_acc, step) - log_writer.add_scalar('Train/loss', avg_loss, - step) - log_writer.add_scalar('Train/lr', lr[0], - step) - log_writer.add_scalar('Train/step/sec', speed, - step) + log_writer.add_scalar('Train/loss', avg_loss, step) + log_writer.add_scalar('Train/lr', lr[0], step) + log_writer.add_scalar('Train/step/sec', speed, step) sys.stdout.flush() avg_loss = 0.0 cm.zero_matrix() @@ -445,12 +364,9 @@ def train(cfg): ).format(epoch, step, lr[0], avg_loss, speed, calculate_eta(all_step - step, speed))) if args.use_vdl: - log_writer.add_scalar('Train/loss', avg_loss, - step) - log_writer.add_scalar('Train/lr', lr[0], - step) - log_writer.add_scalar('Train/speed', speed, - step) + log_writer.add_scalar('Train/loss', avg_loss, step) + log_writer.add_scalar('Train/lr', lr[0], step) + log_writer.add_scalar('Train/speed', speed, step) sys.stdout.flush() avg_loss = 0.0 timer.restart() @@ -470,7 +386,7 @@ def train(cfg): if (epoch % cfg.TRAIN.SNAPSHOT_EPOCH == 0 or epoch == cfg.SOLVER.NUM_EPOCHS) and cfg.TRAINER_ID == 0: - ckpt_dir = save_checkpoint(exe, train_prog, epoch) + ckpt_dir = save_checkpoint(train_prog, epoch) if args.do_eval: print("Evaluation start") @@ -480,10 +396,8 @@ def train(cfg): use_gpu=args.use_gpu, use_mpio=args.use_mpio) if args.use_vdl: - log_writer.add_scalar('Evaluate/mean_iou', mean_iou, - step) - log_writer.add_scalar('Evaluate/mean_acc', mean_acc, - step) + log_writer.add_scalar('Evaluate/mean_iou', mean_iou, step) + log_writer.add_scalar('Evaluate/mean_acc', mean_acc, step) if mean_iou > best_mIoU: best_mIoU = mean_iou @@ -505,7 +419,7 @@ def train(cfg): # save final model if cfg.TRAINER_ID == 0: - save_checkpoint(exe, train_prog, 'final') + save_checkpoint(train_prog, 'final') def main(args): diff --git a/pdseg/utils/__init__.py b/pdseg/utils/__init__.py index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..0e7c9f39543584630fdaedf13d2879a663a789f0 100644 --- a/pdseg/utils/__init__.py +++ b/pdseg/utils/__init__.py @@ -0,0 +1,14 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. diff --git a/pdseg/utils/collect.py b/pdseg/utils/collect.py index 3321ec121ce5698d83a53aeb40a56122bdcabdcf..1b85f1fd959d6e55cfcb62791ec9e2a5430e3f99 100644 --- a/pdseg/utils/collect.py +++ b/pdseg/utils/collect.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, @@ -98,7 +99,7 @@ class SegConfig(dict): 'DATASET.IMAGE_TYPE config error, only support `rgb`, `gray` and `rgba`' ) if self.MEAN is not None: - self.DATASET.PADDING_VALUE = [x*255.0 for x in self.MEAN] + self.DATASET.PADDING_VALUE = [x * 255.0 for x in self.MEAN] if not self.TRAIN_CROP_SIZE: raise ValueError( @@ -111,9 +112,12 @@ class SegConfig(dict): ) # Ensure file list is use UTF-8 encoding - train_sets = codecs.open(self.DATASET.TRAIN_FILE_LIST, 'r', 'utf-8').readlines() - val_sets = codecs.open(self.DATASET.VAL_FILE_LIST, 'r', 'utf-8').readlines() - test_sets = codecs.open(self.DATASET.TEST_FILE_LIST, 'r', 'utf-8').readlines() + train_sets = codecs.open(self.DATASET.TRAIN_FILE_LIST, 'r', + 'utf-8').readlines() + val_sets = codecs.open(self.DATASET.VAL_FILE_LIST, 'r', + 'utf-8').readlines() + test_sets = codecs.open(self.DATASET.TEST_FILE_LIST, 'r', + 'utf-8').readlines() self.DATASET.TRAIN_TOTAL_IMAGES = len(train_sets) self.DATASET.VAL_TOTAL_IMAGES = len(val_sets) self.DATASET.TEST_TOTAL_IMAGES = len(test_sets) @@ -122,12 +126,13 @@ class SegConfig(dict): len(self.MODEL.MULTI_LOSS_WEIGHT) != 3: self.MODEL.MULTI_LOSS_WEIGHT = [1.0, 0.4, 0.16] - if self.AUG.AUG_METHOD not in ['unpadding', 'stepscaling', 'rangescaling']: + if self.AUG.AUG_METHOD not in [ + 'unpadding', 'stepscaling', 'rangescaling' + ]: raise ValueError( 'AUG.AUG_METHOD config error, only support `unpadding`, `unpadding` and `rangescaling`' ) - def update_from_list(self, config_list): if len(config_list) % 2 != 0: raise ValueError( diff --git a/pdseg/utils/config.py b/pdseg/utils/config.py index e58bc39695f62c733c39dde9270d1d7fdd96a677..15da0d0af75ef1077197dab3e374835814b78f88 100644 --- a/pdseg/utils/config.py +++ b/pdseg/utils/config.py @@ -1,11 +1,11 @@ -# -*- coding: utf-8 -*- -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/pdseg/utils/dist_utils.py b/pdseg/utils/dist_utils.py index 64c8800fd2010d4e1e5def6cc4ea2e1ad673b4a3..9954e1a1b93a4faf8b71d1648e88de345b0ac236 100755 --- a/pdseg/utils/dist_utils.py +++ b/pdseg/utils/dist_utils.py @@ -1,4 +1,4 @@ -#copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +#Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # #Licensed under the Apache License, Version 2.0 (the "License"); #you may not use this file except in compliance with the License. diff --git a/pdseg/utils/fp16_utils.py b/pdseg/utils/fp16_utils.py index 38edda500c17aefba4f8c9c59284a40c03c99843..9d2d159dfb38f481fdc0f83cfcc23ff1cba19763 100644 --- a/pdseg/utils/fp16_utils.py +++ b/pdseg/utils/fp16_utils.py @@ -1,6 +1,22 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + import os from paddle import fluid + def load_fp16_vars(executor, dirname, program): load_dirname = os.path.normpath(dirname) @@ -28,4 +44,4 @@ def load_fp16_vars(executor, dirname, program): 'load_as_fp16': var.dtype == fluid.core.VarDesc.VarType.FP16 }) - executor.run(load_prog) \ No newline at end of file + executor.run(load_prog) diff --git a/pdseg/utils/load_model_utils.py b/pdseg/utils/load_model_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..4970593ce10bc2c4998e8c2fed5ce36d9c8679e7 --- /dev/null +++ b/pdseg/utils/load_model_utils.py @@ -0,0 +1,128 @@ +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +import os.path as osp + +import six +import numpy as np + + +def parse_param_file(param_file, return_shape=True): + from paddle.fluid.proto.framework_pb2 import VarType + f = open(param_file, 'rb') + version = np.fromstring(f.read(4), dtype='int32') + lod_level = np.fromstring(f.read(8), dtype='int64') + for i in range(int(lod_level)): + _size = np.fromstring(f.read(8), dtype='int64') + _ = f.read(_size) + version = np.fromstring(f.read(4), dtype='int32') + tensor_desc = VarType.TensorDesc() + tensor_desc_size = np.fromstring(f.read(4), dtype='int32') + tensor_desc.ParseFromString(f.read(int(tensor_desc_size))) + tensor_shape = tuple(tensor_desc.dims) + if return_shape: + f.close() + return tuple(tensor_desc.dims) + if tensor_desc.data_type != 5: + raise Exception( + "Unexpected data type while parse {}".format(param_file)) + data_size = 4 + for i in range(len(tensor_shape)): + data_size *= tensor_shape[i] + weight = np.fromstring(f.read(data_size), dtype='float32') + f.close() + return np.reshape(weight, tensor_shape) + + +def load_pdparams(exe, main_prog, model_dir): + import paddle.fluid as fluid + from paddle.fluid.proto.framework_pb2 import VarType + from paddle.fluid.framework import Program + + vars_to_load = list() + vars_not_load = list() + import pickle + with open(osp.join(model_dir, 'model.pdparams'), 'rb') as f: + params_dict = pickle.load(f) if six.PY2 else pickle.load( + f, encoding='latin1') + unused_vars = list() + for var in main_prog.list_vars(): + if not isinstance(var, fluid.framework.Parameter): + continue + if var.name not in params_dict: + print("{} is not in saved model".format(var.name)) + vars_not_load.append(var.name) + continue + if var.shape != params_dict[var.name].shape: + unused_vars.append(var.name) + vars_not_load.append(var.name) + print( + "[SKIP] Shape of pretrained weight {} doesn't match.(Pretrained: {}, Actual: {})" + .format(var.name, params_dict[var.name].shape, var.shape)) + continue + vars_to_load.append(var) + for var_name in unused_vars: + del params_dict[var_name] + fluid.io.set_program_state(main_prog, params_dict) + + if len(vars_to_load) == 0: + print( + "There is no pretrain weights loaded, maybe you should check you pretrain model!" + ) + else: + print("There are {}/{} varaibles in {} are loaded.".format( + len(vars_to_load), + len(vars_to_load) + len(vars_not_load), model_dir)) + + +def load_pretrained_weights(exe, main_prog, weights_dir): + if not osp.exists(weights_dir): + raise Exception("Path {} not exists.".format(weights_dir)) + if osp.exists(osp.join(weights_dir, "model.pdparams")): + return load_pdparams(exe, main_prog, weights_dir) + import paddle.fluid as fluid + vars_to_load = list() + vars_not_load = list() + for var in main_prog.list_vars(): + if not isinstance(var, fluid.framework.Parameter): + continue + if not osp.exists(osp.join(weights_dir, var.name)): + print("[SKIP] Pretrained weight {}/{} doesn't exist".format( + weights_dir, var.name)) + vars_not_load.append(var) + continue + pretrained_shape = parse_param_file(osp.join(weights_dir, var.name)) + actual_shape = tuple(var.shape) + if pretrained_shape != actual_shape: + print( + "[SKIP] Shape of pretrained weight {}/{} doesn't match.(Pretrained: {}, Actual: {})" + .format(weights_dir, var.name, pretrained_shape, actual_shape)) + vars_not_load.append(var) + continue + vars_to_load.append(var) + + params_dict = fluid.io.load_program_state( + weights_dir, var_list=vars_to_load) + fluid.io.set_program_state(main_prog, params_dict) + + if len(vars_to_load) == 0: + print( + "There is no pretrain weights loaded, maybe you should check you pretrain model!" + ) + else: + print("There are {}/{} varaibles in {} are loaded.".format( + len(vars_to_load), + len(vars_to_load) + len(vars_not_load), weights_dir)) diff --git a/pdseg/utils/timer.py b/pdseg/utils/timer.py index 8e32c343def6e7cab81c6447a090b796d3ce00eb..ce58c367d1df696b01f5f696ef7888bff1c0994f 100644 --- a/pdseg/utils/timer.py +++ b/pdseg/utils/timer.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/pdseg/vis.py b/pdseg/vis.py index 0dc30273b8bf8e7c61ffeb09336959e09949ac8d..6d6a457646e545e3b879b5bc55ea4e2b2848949a 100644 --- a/pdseg/vis.py +++ b/pdseg/vis.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -115,7 +115,12 @@ def visualize(cfg, ckpt_dir = cfg.TEST.TEST_MODEL if not ckpt_dir else ckpt_dir - fluid.io.load_params(exe, ckpt_dir, main_program=test_prog) + if ckpt_dir is not None: + print('load test model:', ckpt_dir) + try: + fluid.load(test_prog, os.path.join(ckpt_dir, 'model'), exe) + except: + fluid.io.load_params(exe, ckpt_dir, main_program=test_prog) save_dir = vis_dir makedirs(save_dir) @@ -169,18 +174,13 @@ def visualize(cfg, print("VisualDL visualization epoch", epoch) pred_mask_np = np.array(pred_mask.convert("RGB")) - log_writer.add_image( - "Predict/{}".format(img_name), - pred_mask_np, - epoch) + log_writer.add_image("Predict/{}".format(img_name), + pred_mask_np, epoch) # Original image # BGR->RGB - img = cv2.imread( - os.path.join(cfg.DATASET.DATA_DIR, img_name))[..., ::-1] - log_writer.add_image( - "Images/{}".format(img_name), - img, - epoch) + img = cv2.imread(os.path.join(cfg.DATASET.DATA_DIR, + img_name))[..., ::-1] + log_writer.add_image("Images/{}".format(img_name), img, epoch) # add ground truth (label) images grt = grts[i] if grt is not None: @@ -189,10 +189,8 @@ def visualize(cfg, grt_pil.putpalette(color_map) grt_pil = grt_pil.resize((org_shape[1], org_shape[0])) grt = np.array(grt_pil.convert("RGB")) - log_writer.add_image( - "Label/{}".format(img_name), - grt, - epoch) + log_writer.add_image("Label/{}".format(img_name), grt, + epoch) # If in local_test mode, only visualize 5 images just for testing # procedure diff --git a/pretrained_model/download_model.py b/pretrained_model/download_model.py index 28b5ae421425a42e959fa6cf792c3e536e53c964..6ac0346cf745f2e00f77e1fdc78a869fd3d73ede 100644 --- a/pretrained_model/download_model.py +++ b/pretrained_model/download_model.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, @@ -42,7 +43,7 @@ model_urls = { "hrnet_w30_bn_imagenet": "https://paddleseg.bj.bcebos.com/models/hrnet_w30_imagenet.tar", "hrnet_w32_bn_imagenet": - "https://paddleseg.bj.bcebos.com/models/hrnet_w32_imagenet.tar" , + "https://paddleseg.bj.bcebos.com/models/hrnet_w32_imagenet.tar", "hrnet_w40_bn_imagenet": "https://paddleseg.bj.bcebos.com/models/hrnet_w40_imagenet.tar", "hrnet_w44_bn_imagenet": diff --git a/slim/distillation/model_builder.py b/slim/distillation/model_builder.py index 90f53992478e27c94fc8a7817931d3a46e0bb108..d12bfbf1a9c5b5dd231840aef0c6e4d6fe8f815b 100644 --- a/slim/distillation/model_builder.py +++ b/slim/distillation/model_builder.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/slim/distillation/train_distill.py b/slim/distillation/train_distill.py index 995cab1f11a8f6d88d19a7b10f9f768f4d6ccbf1..9b8f6785157d78f36a063318410ca5e994c5d830 100644 --- a/slim/distillation/train_distill.py +++ b/slim/distillation/train_distill.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -44,6 +44,7 @@ from model_builder import parse_shape_from_file from eval import evaluate from vis import visualize from utils import dist_utils +from utils.load_model_utils import load_pretrained_weights import solver from paddleslim.dist.single_distiller import merge, l2_loss @@ -116,38 +117,7 @@ def parse_args(): return parser.parse_args() -def save_vars(executor, dirname, program=None, vars=None): - """ - Temporary resolution for Win save variables compatability. - Will fix in PaddlePaddle v1.5.2 - """ - - save_program = fluid.Program() - save_block = save_program.global_block() - - for each_var in vars: - # NOTE: don't save the variable which type is RAW - if each_var.type == fluid.core.VarDesc.VarType.RAW: - continue - new_var = save_block.create_var( - name=each_var.name, - shape=each_var.shape, - dtype=each_var.dtype, - type=each_var.type, - lod_level=each_var.lod_level, - persistable=True) - file_path = os.path.join(dirname, new_var.name) - file_path = os.path.normpath(file_path) - save_block.append_op( - type='save', - inputs={'X': [new_var]}, - outputs={}, - attrs={'file_path': file_path}) - - executor.run(save_program) - - -def save_checkpoint(exe, program, ckpt_name): +def save_checkpoint(program, ckpt_name): """ Save checkpoint for evaluation or resume training """ @@ -156,29 +126,22 @@ def save_checkpoint(exe, program, ckpt_name): if not os.path.isdir(ckpt_dir): os.makedirs(ckpt_dir) - save_vars( - exe, - ckpt_dir, - program, - vars=list(filter(fluid.io.is_persistable, program.list_vars()))) + fluid.save(program, os.path.join(ckpt_dir, 'model')) return ckpt_dir def load_checkpoint(exe, program): """ - Load checkpoiont from pretrained model directory for resume training + Load checkpoiont for resuming training """ - - print('Resume model training from:', cfg.TRAIN.RESUME_MODEL_DIR) - if not os.path.exists(cfg.TRAIN.RESUME_MODEL_DIR): - raise ValueError("TRAIN.PRETRAIN_MODEL {} not exist!".format( - cfg.TRAIN.RESUME_MODEL_DIR)) - - fluid.io.load_persistables( - exe, cfg.TRAIN.RESUME_MODEL_DIR, main_program=program) - model_path = cfg.TRAIN.RESUME_MODEL_DIR + print('Resume model training from:', model_path) + if not os.path.exists(model_path): + raise ValueError( + "TRAIN.PRETRAIN_MODEL {} not exist!".format(model_path)) + fluid.load(program, os.path.join(model_path, 'model'), exe) + # Check is path ended by path spearator if model_path[-1] == os.sep: model_path = model_path[0:-1] @@ -193,7 +156,6 @@ def load_checkpoint(exe, program): else: raise ValueError("Resume model path is not valid!") print("Model checkpoint loaded successfully!") - return begin_epoch @@ -289,7 +251,11 @@ def train(cfg): ckpt_dir = cfg.SLIM.KNOWLEDGE_DISTILL_TEACHER_MODEL_DIR assert ckpt_dir is not None print('load teacher model:', ckpt_dir) - fluid.io.load_params(exe, ckpt_dir, main_program=teacher_program) + if os.path.exists(ckpt_dir): + try: + fluid.load(teacher_program, os.path.join(ckpt_dir, 'model'), exe) + except: + fluid.io.load_params(exe, ckpt_dir, main_program=teacher_program) # cfg = load_config(FLAGS.config) cfg.update_from_file(args.cfg_file) @@ -355,42 +321,8 @@ def train(cfg): begin_epoch = load_checkpoint(exe, fluid.default_main_program()) # Load pretrained model elif os.path.exists(cfg.TRAIN.PRETRAINED_MODEL_DIR): - print_info('Pretrained model dir: ', cfg.TRAIN.PRETRAINED_MODEL_DIR) - load_vars = [] - load_fail_vars = [] - - def var_shape_matched(var, shape): - """ - Check whehter persitable variable shape is match with current network - """ - var_exist = os.path.exists( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - if var_exist: - var_shape = parse_shape_from_file( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - return var_shape == shape - return False - - for x in fluid.default_main_program().list_vars(): - if isinstance(x, fluid.framework.Parameter): - shape = tuple(fluid.global_scope().find_var( - x.name).get_tensor().shape()) - if var_shape_matched(x, shape): - load_vars.append(x) - else: - load_fail_vars.append(x) - - fluid.io.load_vars( - exe, dirname=cfg.TRAIN.PRETRAINED_MODEL_DIR, vars=load_vars) - for var in load_vars: - print_info("Parameter[{}] loaded sucessfully!".format(var.name)) - for var in load_fail_vars: - print_info( - "Parameter[{}] don't exist or shape does not match current network, skip" - " to load it.".format(var.name)) - print_info("{}/{} pretrained parameters loaded successfully!".format( - len(load_vars), - len(load_vars) + len(load_fail_vars))) + load_pretrained_weights(exe, fluid.default_main_program(), + cfg.TRAIN.PRETRAINED_MODEL_DIR) else: print_info( 'Pretrained model dir {} not exists, training from scratch...'. @@ -475,12 +407,9 @@ def train(cfg): step) log_writer.add_scalar('Train/mean_acc', mean_acc, step) - log_writer.add_scalar('Train/loss', avg_loss, - step) - log_writer.add_scalar('Train/lr', lr[0], - step) - log_writer.add_scalar('Train/step/sec', speed, - step) + log_writer.add_scalar('Train/loss', avg_loss, step) + log_writer.add_scalar('Train/lr', lr[0], step) + log_writer.add_scalar('Train/step/sec', speed, step) sys.stdout.flush() avg_loss = 0.0 cm.zero_matrix() @@ -503,16 +432,13 @@ def train(cfg): speed = args.log_steps / timer.elapsed_time() print(( "epoch={} step={} lr={:.5f} loss={:.4f} teacher loss={:.4f} distill loss={:.4f} step/sec={:.3f} | ETA {}" - ).format(epoch, step, lr[0], avg_loss, - avg_t_loss, avg_d_loss, speed, + ).format(epoch, step, lr[0], avg_loss, avg_t_loss, + avg_d_loss, speed, calculate_eta(all_step - step, speed))) if args.use_vdl: - log_writer.add_scalar('Train/loss', avg_loss, - step) - log_writer.add_scalar('Train/lr', lr[0], - step) - log_writer.add_scalar('Train/speed', speed, - step) + log_writer.add_scalar('Train/loss', avg_loss, step) + log_writer.add_scalar('Train/lr', lr[0], step) + log_writer.add_scalar('Train/speed', speed, step) sys.stdout.flush() avg_loss = 0.0 avg_t_loss = 0.0 @@ -527,7 +453,7 @@ def train(cfg): if (epoch % cfg.TRAIN.SNAPSHOT_EPOCH == 0 or epoch == cfg.SOLVER.NUM_EPOCHS) and cfg.TRAINER_ID == 0: - ckpt_dir = save_checkpoint(exe, fluid.default_main_program(), epoch) + ckpt_dir = save_checkpoint(fluid.default_main_program(), epoch) if args.do_eval: print("Evaluation start") @@ -537,10 +463,8 @@ def train(cfg): use_gpu=args.use_gpu, use_mpio=args.use_mpio) if args.use_vdl: - log_writer.add_scalar('Evaluate/mean_iou', mean_iou, - step) - log_writer.add_scalar('Evaluate/mean_acc', mean_acc, - step) + log_writer.add_scalar('Evaluate/mean_iou', mean_iou, step) + log_writer.add_scalar('Evaluate/mean_acc', mean_acc, step) if mean_iou > best_mIoU: best_mIoU = mean_iou @@ -560,11 +484,11 @@ def train(cfg): ckpt_dir=ckpt_dir, log_writer=log_writer) if cfg.TRAINER_ID == 0: - ckpt_dir = save_checkpoint(exe, fluid.default_main_program(), epoch) + ckpt_dir = save_checkpoint(fluid.default_main_program(), epoch) # save final model if cfg.TRAINER_ID == 0: - save_checkpoint(exe, fluid.default_main_program(), 'final') + save_checkpoint(fluid.default_main_program(), 'final') def main(args): diff --git a/slim/nas/deeplab.py b/slim/nas/deeplab.py index 6cbf840927b107a36273e9890f1ba4d076ddb417..08c3219f7fd8364c45492b3b86ad0536ba433062 100644 --- a/slim/nas/deeplab.py +++ b/slim/nas/deeplab.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -27,6 +27,7 @@ from models.libs.model_libs import separate_conv from models.backbone.mobilenet_v2 import MobileNetV2 as mobilenet_backbone from models.backbone.xception import Xception as xception_backbone + def encoder(input): # 编码器配置，采用ASPP架构，pooling + 1x1_conv + 三个不同尺度的空洞卷积并行, concat后1x1conv # ASPP_WITH_SEP_CONV：默认为真，使用depthwise可分离卷积，否则使用普通卷积 @@ -47,8 +48,7 @@ def encoder(input): with scope('encoder'): channel = 256 with scope("image_pool"): - image_avg = fluid.layers.reduce_mean( - input, [2, 3], keep_dim=True) + image_avg = fluid.layers.reduce_mean(input, [2, 3], keep_dim=True) image_avg = bn_relu( conv( image_avg, @@ -191,7 +191,10 @@ def nas_backbone(input, arch): end_points = 8 decode_point = 3 data, decode_shortcuts = arch( - input, end_points=end_points, return_block=decode_point, output_stride=16) + input, + end_points=end_points, + return_block=decode_point, + output_stride=16) decode_shortcut = decode_shortcuts[decode_point] return data, decode_shortcut diff --git a/slim/nas/eval_nas.py b/slim/nas/eval_nas.py index 7f8663dffafb49d7c372f3eeaf0d3ed074f7ce9b..9e05fd7bdb71ac2e78615443d7fe2325d826e78c 100644 --- a/slim/nas/eval_nas.py +++ b/slim/nas/eval_nas.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -123,7 +123,10 @@ def evaluate(cfg, ckpt_dir=None, use_gpu=False, use_mpio=False, **kwargs): if ckpt_dir is not None: print('load test model:', ckpt_dir) - fluid.io.load_params(exe, ckpt_dir, main_program=test_prog) + try: + fluid.load(test_prog, os.path.join(ckpt_dir, 'model'), exe) + except: + fluid.io.load_params(exe, ckpt_dir, main_program=test_prog) # Use streaming confusion matrix to calculate mean_iou np.set_printoptions( diff --git a/slim/nas/mobilenetv2_search_space.py b/slim/nas/mobilenetv2_search_space.py index 2703e161f02e9659040b827fff8d345db5bf5946..9b5c33bcc108efff7f55d622a73d0b51b8b8a92f 100644 --- a/slim/nas/mobilenetv2_search_space.py +++ b/slim/nas/mobilenetv2_search_space.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, @@ -31,7 +32,7 @@ __all__ = ["MobileNetV2SpaceSeg"] class MobileNetV2SpaceSeg(SearchSpaceBase): def __init__(self, input_size, output_size, block_num, block_mask=None): super(MobileNetV2SpaceSeg, self).__init__(input_size, output_size, - block_num, block_mask) + block_num, block_mask) # self.head_num means the first convolution channel self.head_num = np.array([3, 4, 8, 12, 16, 24, 32]) #7 # self.filter_num1 ~ self.filter_num6 means following convlution channel @@ -48,7 +49,7 @@ class MobileNetV2SpaceSeg(SearchSpaceBase): self.k_size = np.array([3, 5]) #2 # self.multiply means expansion_factor of each _inverted_residual_unit self.multiply = np.array([1, 2, 3, 4, 6]) #5 - # self.repeat means repeat_num _inverted_residual_unit in each _invresi_blocks + # self.repeat means repeat_num _inverted_residual_unit in each _invresi_blocks self.repeat = np.array([1, 2, 3, 4, 5, 6]) #6 def init_tokens(self): @@ -72,7 +73,7 @@ class MobileNetV2SpaceSeg(SearchSpaceBase): def range_table(self): """ - Get range table of current search space, constrains the range of tokens. + Get range table of current search space, constrains the range of tokens. """ # head_num + 6 * [multiple(expansion_factor), filter_num, repeat, kernel_size] # yapf: disable @@ -95,8 +96,8 @@ class MobileNetV2SpaceSeg(SearchSpaceBase): tokens = self.init_tokens() self.bottleneck_params_list = [] - self.bottleneck_params_list.append( - (1, self.head_num[tokens[0]], 1, 1, 3)) + self.bottleneck_params_list.append((1, self.head_num[tokens[0]], 1, 1, + 3)) self.bottleneck_params_list.append( (self.multiply[tokens[1]], self.filter_num1[tokens[2]], self.repeat[tokens[3]], 2, self.k_size[tokens[4]])) @@ -150,7 +151,7 @@ class MobileNetV2SpaceSeg(SearchSpaceBase): return (True if count == points else False) #conv1 - # all padding is 'SAME' in the conv2d, can compute the actual padding automatic. + # all padding is 'SAME' in the conv2d, can compute the actual padding automatic. input = conv_bn_layer( input, num_filters=int(32 * self.scale), diff --git a/slim/nas/model_builder.py b/slim/nas/model_builder.py index 27a14fa77970cad18e017dc825f1708ceb2c9c75..d300e5a4ea65b9c5424a6d0bccd64b60c5f23e0d 100644 --- a/slim/nas/model_builder.py +++ b/slim/nas/model_builder.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/slim/nas/train_nas.py b/slim/nas/train_nas.py index f4cd8f81b1f73b7d30ce948be700beba9932c314..7854bf0adce3e90a2df03e55ba09a07f37b03141 100644 --- a/slim/nas/train_nas.py +++ b/slim/nas/train_nas.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -47,6 +47,7 @@ from model_builder import parse_shape_from_file from eval_nas import evaluate from vis import visualize from utils import dist_utils +from utils.load_model_utils import load_pretrained_weights from mobilenetv2_search_space import MobileNetV2SpaceSeg from paddleslim.nas.search_space.search_space_factory import SearchSpaceFactory @@ -116,38 +117,7 @@ def parse_args(): return parser.parse_args() -def save_vars(executor, dirname, program=None, vars=None): - """ - Temporary resolution for Win save variables compatability. - Will fix in PaddlePaddle v1.5.2 - """ - - save_program = fluid.Program() - save_block = save_program.global_block() - - for each_var in vars: - # NOTE: don't save the variable which type is RAW - if each_var.type == fluid.core.VarDesc.VarType.RAW: - continue - new_var = save_block.create_var( - name=each_var.name, - shape=each_var.shape, - dtype=each_var.dtype, - type=each_var.type, - lod_level=each_var.lod_level, - persistable=True) - file_path = os.path.join(dirname, new_var.name) - file_path = os.path.normpath(file_path) - save_block.append_op( - type='save', - inputs={'X': [new_var]}, - outputs={}, - attrs={'file_path': file_path}) - - executor.run(save_program) - - -def save_checkpoint(exe, program, ckpt_name): +def save_checkpoint(program, ckpt_name): """ Save checkpoint for evaluation or resume training """ @@ -156,29 +126,22 @@ def save_checkpoint(exe, program, ckpt_name): if not os.path.isdir(ckpt_dir): os.makedirs(ckpt_dir) - save_vars( - exe, - ckpt_dir, - program, - vars=list(filter(fluid.io.is_persistable, program.list_vars()))) + fluid.save(program, os.path.join(ckpt_dir, 'model')) return ckpt_dir def load_checkpoint(exe, program): """ - Load checkpoiont from pretrained model directory for resume training + Load checkpoiont for resuming training """ - - print('Resume model training from:', cfg.TRAIN.RESUME_MODEL_DIR) - if not os.path.exists(cfg.TRAIN.RESUME_MODEL_DIR): - raise ValueError("TRAIN.PRETRAIN_MODEL {} not exist!".format( - cfg.TRAIN.RESUME_MODEL_DIR)) - - fluid.io.load_persistables( - exe, cfg.TRAIN.RESUME_MODEL_DIR, main_program=program) - model_path = cfg.TRAIN.RESUME_MODEL_DIR + print('Resume model training from:', model_path) + if not os.path.exists(model_path): + raise ValueError( + "TRAIN.PRETRAIN_MODEL {} not exist!".format(model_path)) + fluid.load(program, os.path.join(model_path, 'model'), exe) + # Check is path ended by path spearator if model_path[-1] == os.sep: model_path = model_path[0:-1] @@ -193,7 +156,6 @@ def load_checkpoint(exe, program): else: raise ValueError("Resume model path is not valid!") print("Model checkpoint loaded successfully!") - return begin_epoch @@ -245,8 +207,6 @@ def train(cfg): yield item[0], item[1], item[2] # Get device environment - # places = fluid.cuda_places() if args.use_gpu else fluid.cpu_places() - # place = places[0] gpu_id = int(os.environ.get('FLAGS_selected_gpus', 0)) place = fluid.CUDAPlace(gpu_id) if args.use_gpu else fluid.CPUPlace() places = fluid.cuda_places() if args.use_gpu else fluid.cpu_places() @@ -326,43 +286,8 @@ def train(cfg): begin_epoch = load_checkpoint(exe, train_prog) # Load pretrained model elif os.path.exists(cfg.TRAIN.PRETRAINED_MODEL_DIR): - print_info('Pretrained model dir: ', cfg.TRAIN.PRETRAINED_MODEL_DIR) - load_vars = [] - load_fail_vars = [] - - def var_shape_matched(var, shape): - """ - Check whehter persitable variable shape is match with current network - """ - var_exist = os.path.exists( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - if var_exist: - var_shape = parse_shape_from_file( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - return var_shape == shape - return False - - for x in train_prog.list_vars(): - if isinstance(x, fluid.framework.Parameter): - shape = tuple(fluid.global_scope().find_var( - x.name).get_tensor().shape()) - if var_shape_matched(x, shape): - load_vars.append(x) - else: - load_fail_vars.append(x) - - fluid.io.load_vars( - exe, dirname=cfg.TRAIN.PRETRAINED_MODEL_DIR, vars=load_vars) - for var in load_vars: - print_info("Parameter[{}] loaded sucessfully!".format(var.name)) - for var in load_fail_vars: - print_info( - "Parameter[{}] don't exist or shape does not match current network, skip" - " to load it.".format(var.name)) - print_info( - "{}/{} pretrained parameters loaded successfully!".format( - len(load_vars), - len(load_vars) + len(load_fail_vars))) + load_pretrained_weights(exe, train_prog, + cfg.TRAIN.PRETRAINED_MODEL_DIR) else: print_info( 'Pretrained model dir {} not exists, training from scratch...'. @@ -419,8 +344,7 @@ def train(cfg): except Exception as e: print(e) if epoch > cfg.SLIM.NAS_START_EVAL_EPOCH: - ckpt_dir = save_checkpoint(exe, train_prog, - '{}_tmp'.format(port)) + ckpt_dir = save_checkpoint(train_prog, '{}_tmp'.format(port)) _, mean_iou, _, mean_acc = evaluate( cfg=cfg, arch=arch, diff --git a/slim/prune/eval_prune.py b/slim/prune/eval_prune.py index 3bfb4f4cf2772da0e6122ec6f6660d90a23c71e2..1ce85b8442053d2d8229fe72e74695a53e02c811 100644 --- a/slim/prune/eval_prune.py +++ b/slim/prune/eval_prune.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/slim/prune/train_prune.py b/slim/prune/train_prune.py index 6c41e74beb62423354445b45d250bb0f2f75b2d3..d444f591e7b796d46cb11f986a54c6cd4348ad22 100644 --- a/slim/prune/train_prune.py +++ b/slim/prune/train_prune.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -46,6 +46,7 @@ from models.model_builder import parse_shape_from_file from eval_prune import evaluate from vis import visualize from utils import dist_utils +from utils.load_model_utils import load_pretrained_weights from paddleslim.prune import Pruner, save_model from paddleslim.analysis import flops @@ -285,42 +286,7 @@ def train(cfg): begin_epoch = load_checkpoint(exe, train_prog) # Load pretrained model elif os.path.exists(cfg.TRAIN.PRETRAINED_MODEL_DIR): - print_info('Pretrained model dir: ', cfg.TRAIN.PRETRAINED_MODEL_DIR) - load_vars = [] - load_fail_vars = [] - - def var_shape_matched(var, shape): - """ - Check whehter persitable variable shape is match with current network - """ - var_exist = os.path.exists( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - if var_exist: - var_shape = parse_shape_from_file( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - return var_shape == shape - return False - - for x in train_prog.list_vars(): - if isinstance(x, fluid.framework.Parameter): - shape = tuple(fluid.global_scope().find_var( - x.name).get_tensor().shape()) - if var_shape_matched(x, shape): - load_vars.append(x) - else: - load_fail_vars.append(x) - - fluid.io.load_vars( - exe, dirname=cfg.TRAIN.PRETRAINED_MODEL_DIR, vars=load_vars) - for var in load_vars: - print_info("Parameter[{}] loaded sucessfully!".format(var.name)) - for var in load_fail_vars: - print_info( - "Parameter[{}] don't exist or shape does not match current network, skip" - " to load it.".format(var.name)) - print_info("{}/{} pretrained parameters loaded successfully!".format( - len(load_vars), - len(load_vars) + len(load_fail_vars))) + load_pretrained_weights(exe, train_prog, cfg.TRAIN.PRETRAINED_MODEL_DIR) else: print_info( 'Pretrained model dir {} not exists, training from scratch...'. @@ -409,12 +375,9 @@ def train(cfg): step) log_writer.add_scalar('Train/mean_acc', mean_acc, step) - log_writer.add_scalar('Train/loss', avg_loss, - step) - log_writer.add_scalar('Train/lr', lr[0], - step) - log_writer.add_scalar('Train/step/sec', speed, - step) + log_writer.add_scalar('Train/loss', avg_loss, step) + log_writer.add_scalar('Train/lr', lr[0], step) + log_writer.add_scalar('Train/step/sec', speed, step) sys.stdout.flush() avg_loss = 0.0 cm.zero_matrix() @@ -436,12 +399,9 @@ def train(cfg): ).format(epoch, step, lr[0], avg_loss, speed, calculate_eta(all_step - step, speed))) if args.use_vdl: - log_writer.add_scalar('Train/loss', avg_loss, - step) - log_writer.add_scalar('Train/lr', lr[0], - step) - log_writer.add_scalar('Train/speed', speed, - step) + log_writer.add_scalar('Train/loss', avg_loss, step) + log_writer.add_scalar('Train/lr', lr[0], step) + log_writer.add_scalar('Train/speed', speed, step) sys.stdout.flush() avg_loss = 0.0 timer.restart() @@ -464,10 +424,8 @@ def train(cfg): use_gpu=args.use_gpu, use_mpio=args.use_mpio) if args.use_vdl: - log_writer.add_scalar('Evaluate/mean_iou', mean_iou, - step) - log_writer.add_scalar('Evaluate/mean_acc', mean_acc, - step) + log_writer.add_scalar('Evaluate/mean_iou', mean_iou, step) + log_writer.add_scalar('Evaluate/mean_acc', mean_acc, step) # Use VisualDL to visualize results if args.use_vdl and cfg.DATASET.VIS_FILE_LIST is not None: diff --git a/slim/quantization/eval_quant.py b/slim/quantization/eval_quant.py index fdf6f3ce18444f85c157a301334aabfdf47869e7..e309858f0deecc53783d6fcc58dfb94ef4014fd6 100644 --- a/slim/quantization/eval_quant.py +++ b/slim/quantization/eval_quant.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/slim/quantization/export_model.py b/slim/quantization/export_model.py index 3891254bd18470c2af94cb74fe8e06e942b86cb5..a80d1bb698ea66d06f9eeee1517eb0bc3609b944 100644 --- a/slim/quantization/export_model.py +++ b/slim/quantization/export_model.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. diff --git a/slim/quantization/train_quant.py b/slim/quantization/train_quant.py index 1034b7234d73f21c41085d5a04d74069b04de7ca..c83bfe94c5592a62b9affb5351ee2da4f316cea4 100644 --- a/slim/quantization/train_quant.py +++ b/slim/quantization/train_quant.py @@ -1,5 +1,5 @@ # coding: utf8 -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. @@ -40,7 +40,8 @@ from models.model_builder import parse_shape_from_file from eval_quant import evaluate from vis import visualize from utils import dist_utils -from train import save_vars, save_checkpoint, load_checkpoint, update_best_model, print_info +from utils.load_model_utils import load_pretrained_weights +from train import update_best_model, print_info from paddleslim.quant import quant_aware @@ -103,6 +104,55 @@ def parse_args(): return parser.parse_args() +def save_checkpoint(exe, program, ckpt_name): + """ + Save checkpoint for evaluation or resume training + """ + ckpt_dir = os.path.join(cfg.TRAIN.MODEL_SAVE_DIR, str(ckpt_name)) + print("Save model checkpoint to {}".format(ckpt_dir)) + if not os.path.isdir(ckpt_dir): + os.makedirs(ckpt_dir) + + fluid.io.save_vars( + exe, + ckpt_dir, + program, + vars=list(filter(fluid.io.is_persistable, program.list_vars()))) + return ckpt_dir + + +def load_checkpoint(exe, program): + """ + Load checkpoiont from pretrained model directory for resume training + """ + + print('Resume model training from:', cfg.TRAIN.RESUME_MODEL_DIR) + if not os.path.exists(cfg.TRAIN.RESUME_MODEL_DIR): + raise ValueError("TRAIN.PRETRAIN_MODEL {} not exist!".format( + cfg.TRAIN.RESUME_MODEL_DIR)) + + fluid.io.load_persistables( + exe, cfg.TRAIN.RESUME_MODEL_DIR, main_program=program) + + model_path = cfg.TRAIN.RESUME_MODEL_DIR + # Check is path ended by path spearator + if model_path[-1] == os.sep: + model_path = model_path[0:-1] + epoch_name = os.path.basename(model_path) + # If resume model is final model + if epoch_name == 'final': + begin_epoch = cfg.SOLVER.NUM_EPOCHS + # If resume model path is end of digit, restore epoch status + elif epoch_name.isdigit(): + epoch = int(epoch_name) + begin_epoch = epoch + 1 + else: + raise ValueError("Resume model path is not valid!") + print("Model checkpoint loaded successfully!") + + return begin_epoch + + def train_quant(cfg): startup_prog = fluid.Program() train_prog = fluid.Program() @@ -182,42 +232,7 @@ def train_quant(cfg): begin_epoch = load_checkpoint(exe, train_prog) # Load pretrained model elif os.path.exists(cfg.TRAIN.PRETRAINED_MODEL_DIR): - print_info('Pretrained model dir: ', cfg.TRAIN.PRETRAINED_MODEL_DIR) - load_vars = [] - load_fail_vars = [] - - def var_shape_matched(var, shape): - """ - Check whehter persitable variable shape is match with current network - """ - var_exist = os.path.exists( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - if var_exist: - var_shape = parse_shape_from_file( - os.path.join(cfg.TRAIN.PRETRAINED_MODEL_DIR, var.name)) - return var_shape == shape - return False - - for x in train_prog.list_vars(): - if isinstance(x, fluid.framework.Parameter): - shape = tuple(fluid.global_scope().find_var( - x.name).get_tensor().shape()) - if var_shape_matched(x, shape): - load_vars.append(x) - else: - load_fail_vars.append(x) - - fluid.io.load_vars( - exe, dirname=cfg.TRAIN.PRETRAINED_MODEL_DIR, vars=load_vars) - for var in load_vars: - print_info("Parameter[{}] loaded sucessfully!".format(var.name)) - for var in load_fail_vars: - print_info( - "Parameter[{}] don't exist or shape does not match current network, skip" - " to load it.".format(var.name)) - print_info("{}/{} pretrained parameters loaded successfully!".format( - len(load_vars), - len(load_vars) + len(load_fail_vars))) + load_pretrained_weights(exe, train_prog, cfg.TRAIN.PRETRAINED_MODEL_DIR) else: print_info( 'Pretrained model dir {} not exists, training from scratch...'. diff --git a/test/local_test_cityscapes.py b/test/local_test_cityscapes.py index cff6a993cf34499567398f4107171e66845b18ce..c6ec8da12d46176a12799f882eef41af89a231ec 100644 --- a/test/local_test_cityscapes.py +++ b/test/local_test_cityscapes.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/test/local_test_pet.py b/test/local_test_pet.py index 920aea654c6afc159e4ff1fab031b1c29ea69528..5132ac5ffcaab07e26fe9329a285a378e6c58292 100644 --- a/test/local_test_pet.py +++ b/test/local_test_pet.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, diff --git a/test/test_utils.py b/test/test_utils.py index ed1f8ed89f9ad5204a3534c1c7e2531ce839add0..32dd4aed6b6985ea92fa2691738573e0ec258365 100644 --- a/test/test_utils.py +++ b/test/test_utils.py @@ -1,10 +1,11 @@ -# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. +# coding: utf8 +# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. # -# Licensed under the Apache License, Version 2.0 (the "License" +# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # -# http://www.apache.org/licenses/LICENSE-2.0 +# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS,