diff --git a/configs/faster_rcnn/faster_rcnn_r34_fpn_multiscaletest_1x_coco.yml b/configs/faster_rcnn/faster_rcnn_r34_fpn_multiscaletest_1x_coco.yml deleted file mode 100644 index 559d5f1fe9fdcbf42189383a69f9d1a056792cda..0000000000000000000000000000000000000000 --- a/configs/faster_rcnn/faster_rcnn_r34_fpn_multiscaletest_1x_coco.yml +++ /dev/null @@ -1,22 +0,0 @@ -_BASE_: [ - 'faster_rcnn_r34_fpn_1x_coco.yml', -] - -pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet34_pretrained.pdparams -weights: output/faster_rcnn_r34_fpn_multiscaletest_1x_coco/model_final - -EvalReader: - sample_transforms: - - Decode: {} -# - Resize: {interp: 2, target_size: [800, 1333], keep_ratio: True} - - MultiscaleTestResize: {origin_target_size: [800, 1333], target_size: [700 , 900], use_flip: False} - - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]} - - Permute: {} - -TestReader: - sample_transforms: - - Decode: {} -# - Resize: {interp: 2, target_size: [800, 1333], keep_ratio: True} - - MultiscaleTestResize: {origin_target_size: [800, 1333], target_size: [700 , 900], use_flip: False} - - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]} - - Permute: {} \ No newline at end of file diff --git a/docs/tutorials/config_annotation/multi_scale_test_config.md b/docs/tutorials/config_annotation/multi_scale_test_config.md deleted file mode 100644 index 5d553ca0da92aa404fab72c889699a49a7583bdd..0000000000000000000000000000000000000000 --- a/docs/tutorials/config_annotation/multi_scale_test_config.md +++ /dev/null @@ -1,45 +0,0 @@ -# Multi Scale Test Configuration - -Tags: Configuration - ---- -```yaml - -##################################### Multi scale test configuration ##################################### - -EvalReader: - sample_transforms: - - Decode: {} - - MultiscaleTestResize: {origin_target_size: [800, 1333], target_size: [700 , 900]} - - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]} - - Permute: {} - -TestReader: - sample_transforms: - - Decode: {} - - MultiscaleTestResize: {origin_target_size: [800, 1333], target_size: [700 , 900]} - - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]} - - Permute: {} -``` - ---- - -Multi Scale Test is a TTA (Test Time Augmentation) method, it can improve object detection performance. - -The input image will be scaled into different scales, then model generated predictions (bboxes) at different scales, finally all the predictions will be combined to generate final prediction. (Here **NMS** is used to aggregate the predictions.) - -## _MultiscaleTestResize_ option - -`MultiscaleTestResize` option is used to enable multi scale test prediction. - -`origin_target_size: [800, 1333]` means the input image will be scaled to 800 (for short edge) and 1333 (max edge length cannot be greater than 1333) at first - -`target_size: [700 , 900]` property is used to specify different scales. - -It can be plugged into evaluation process or test (inference) process, by adding `MultiscaleTestResize` entry to `EvalReader.sample_transforms` or `TestReader.sample_transforms` - ---- - -###Note - -Now only CascadeRCNN, FasterRCNN and MaskRCNN are supported for multi scale testing. And batch size must be 1. \ No newline at end of file diff --git a/docs/tutorials/config_annotation/multi_scale_test_config_cn.md b/docs/tutorials/config_annotation/multi_scale_test_config_cn.md deleted file mode 100644 index acf942c35ebf7c8eeb41304258759e0163d3dcf9..0000000000000000000000000000000000000000 --- a/docs/tutorials/config_annotation/multi_scale_test_config_cn.md +++ /dev/null @@ -1,45 +0,0 @@ -# 多尺度测试的配置 - -标签: 配置 - ---- -```yaml - -##################################### 多尺度测试的配置 ##################################### - -EvalReader: - sample_transforms: - - Decode: {} - - MultiscaleTestResize: {origin_target_size: [800, 1333], target_size: [700 , 900]} - - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]} - - Permute: {} - -TestReader: - sample_transforms: - - Decode: {} - - MultiscaleTestResize: {origin_target_size: [800, 1333], target_size: [700 , 900]} - - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]} - - Permute: {} -``` - ---- - -多尺度测试是一种TTA方法（测试时增强），可以用于提高目标检测的准确率 - -输入图像首先被缩放为不同尺度的图像，然后模型对这些不同尺度的图像进行预测，最后将这些不同尺度上的预测结果整合为最终预测结果。（这里使用了**NMS**来整合不同尺度的预测结果） - -## _MultiscaleTestResize_ 选项 - -`MultiscaleTestResize` 选项用于开启多尺度测试. - -`origin_target_size: [800, 1333]` 项代表输入图像首先缩放为短边为800，最长边不超过1333. - -`target_size: [700 , 900]` 项设置不同的预测尺度。 - -通过在`EvalReader.sample_transforms`或`TestReader.sample_transforms`中设置`MultiscaleTestResize`项，可以在评估过程或预测过程中开启多尺度测试。 - ---- - -###注意 - -目前多尺度测试只支持CascadeRCNN, FasterRCNN and MaskRCNN网络, 并且batch size需要是1. \ No newline at end of file diff --git a/ppdet/data/transform/batch_operators.py b/ppdet/data/transform/batch_operators.py index e988e720108ea0c09b56bf3d642b3f795b540275..bacd53b75421bce4f2e95ba96ec56704ae4bd4be 100644 --- a/ppdet/data/transform/batch_operators.py +++ b/ppdet/data/transform/batch_operators.py @@ -16,8 +16,6 @@ from __future__ import absolute_import from __future__ import division from __future__ import print_function -import typing - try: from collections.abc import Sequence except Exception: @@ -60,13 +58,7 @@ class PadBatch(BaseOperator): """ coarsest_stride = self.pad_to_stride - # multi scale input is nested list - if isinstance(samples, typing.Sequence) and len(samples) > 0 and isinstance(samples[0], typing.Sequence): - inner_samples = samples[0] - else: - inner_samples = samples - - max_shape = np.array([data['image'].shape for data in inner_samples]).max( + max_shape = np.array([data['image'].shape for data in samples]).max( axis=0) if coarsest_stride > 0: max_shape[1] = int( @@ -74,7 +66,7 @@ class PadBatch(BaseOperator): max_shape[2] = int( np.ceil(max_shape[2] / coarsest_stride) * coarsest_stride) - for data in inner_samples: + for data in samples: im = data['image'] im_c, im_h, im_w = im.shape[:] padding_im = np.zeros( diff --git a/ppdet/engine/trainer.py b/ppdet/engine/trainer.py index 353797309913c09244197e7b345de5c9b20b50df..edb02709ba3f7587a030c5ada3726a5ccb0325b0 100644 --- a/ppdet/engine/trainer.py +++ b/ppdet/engine/trainer.py @@ -22,7 +22,6 @@ import copy import time import numpy as np -import typing from PIL import Image import paddle @@ -429,11 +428,7 @@ class Trainer(object): for metric in self._metrics: metric.update(data, outs) - # multi-scale inputs: all inputs have same im_id - if isinstance(data, typing.Sequence): - sample_num += data[0]['im_id'].numpy().shape[0] - else: - sample_num += data['im_id'].numpy().shape[0] + sample_num += data['im_id'].numpy().shape[0] self._compose_callback.on_step_end(self.status) self.status['sample_num'] = sample_num @@ -476,10 +471,7 @@ class Trainer(object): outs = self.model(data) for key in ['im_shape', 'scale_factor', 'im_id']: - if isinstance(data, typing.Sequence): - outs[key] = data[0][key] - else: - outs[key] = data[key] + outs[key] = data[key] for key, value in outs.items(): if hasattr(value, 'numpy'): outs[key] = value.numpy() diff --git a/ppdet/metrics/metrics.py b/ppdet/metrics/metrics.py index ea9861319f17767e8aa5f914c15d95ceb53638d0..65b18efd82eb6f47fa9e7c2da550663693b00e59 100644 --- a/ppdet/metrics/metrics.py +++ b/ppdet/metrics/metrics.py @@ -21,7 +21,6 @@ import sys import json import paddle import numpy as np -import typing from .map_utils import prune_zero_padding, DetectionMAP from .coco_utils import get_infer_results, cocoapi_eval @@ -98,11 +97,7 @@ class COCOMetric(Metric): for k, v in outputs.items(): outs[k] = v.numpy() if isinstance(v, paddle.Tensor) else v - # multi-scale inputs: all inputs have same im_id - if isinstance(inputs, typing.Sequence): - im_id = inputs[0]['im_id'] - else: - im_id = inputs['im_id'] + im_id = inputs['im_id'] outs['im_id'] = im_id.numpy() if isinstance(im_id, paddle.Tensor) else im_id diff --git a/ppdet/modeling/architectures/meta_arch.py b/ppdet/modeling/architectures/meta_arch.py index d914b4e98dc4f4a3aeed4cbce757694e1fb6de33..00085428d75bfc8d99533a22a08060354713e637 100644 --- a/ppdet/modeling/architectures/meta_arch.py +++ b/ppdet/modeling/architectures/meta_arch.py @@ -2,13 +2,9 @@ from __future__ import absolute_import from __future__ import division from __future__ import print_function -import numpy as np import paddle import paddle.nn as nn -import typing - from ppdet.core.workspace import register -from static.ppdet.utils.post_process import nms __all__ = ['BaseArch'] @@ -29,53 +25,7 @@ class BaseArch(nn.Layer): if self.training: out = self.get_loss() else: - inputs_list = [] - # multi-scale input - if not isinstance(inputs, typing.Sequence): - inputs_list.append(inputs) - else: - inputs_list.extend(inputs) - - outs = [] - for inp in inputs_list: - self.inputs = inp - outs.append(self.get_pred()) - - # multi-scale test - if len(outs)>1: - out = self.merge_multi_scale_predictions(outs) - else: - out = outs[0] - return out - - def merge_multi_scale_predictions(self, outs): - # default values for architectures not included in following list - num_classes = 80 - nms_threshold = 0.5 - keep_top_k = 100 - - if self.__class__.__name__ in ('CascadeRCNN', 'FasterRCNN', 'MaskRCNN'): - num_classes = self.bbox_head.num_classes - keep_top_k = self.bbox_post_process.nms.keep_top_k - nms_threshold = self.bbox_post_process.nms.nms_threshold - else: - raise Exception("Multi scale test only supports CascadeRCNN, FasterRCNN and MaskRCNN for now") - - final_boxes = [] - all_scale_outs = paddle.concat([o['bbox'] for o in outs]).numpy() - for c in range(num_classes): - idxs = all_scale_outs[:, 0] == c - if np.count_nonzero(idxs) == 0: - continue - r = nms(all_scale_outs[idxs, 1:], nms_threshold) - final_boxes.append(np.concatenate([np.full((r.shape[0], 1), c), r], 1)) - out = np.concatenate(final_boxes) - out = np.concatenate(sorted(out, key=lambda e: e[1])[-keep_top_k:]).reshape((-1, 6)) - out = { - 'bbox': paddle.to_tensor(out), - 'bbox_num': paddle.to_tensor(np.array([out.shape[0], ])) - } - + out = self.get_pred() return out def build_inputs(self, data, input_def): diff --git a/ppdet/modeling/tests/imgs/coco2017_val2017_000000000139.jpg b/ppdet/modeling/tests/imgs/coco2017_val2017_000000000139.jpg deleted file mode 100644 index 19023f718333c56c70776c79201dc03d742c1ed3..0000000000000000000000000000000000000000 Binary files a/ppdet/modeling/tests/imgs/coco2017_val2017_000000000139.jpg and /dev/null differ diff --git a/ppdet/modeling/tests/imgs/coco2017_val2017_000000000724.jpg b/ppdet/modeling/tests/imgs/coco2017_val2017_000000000724.jpg deleted file mode 100644 index 2a17e0c6ee400dcba762c4d56dea03d7e124b9c5..0000000000000000000000000000000000000000 Binary files a/ppdet/modeling/tests/imgs/coco2017_val2017_000000000724.jpg and /dev/null differ diff --git a/ppdet/modeling/tests/test_mstest.py b/ppdet/modeling/tests/test_mstest.py deleted file mode 100644 index 57d1d169fecbf235227aa388ae0d2e3d92330d0c..0000000000000000000000000000000000000000 --- a/ppdet/modeling/tests/test_mstest.py +++ /dev/null @@ -1,60 +0,0 @@ -# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. -# -# 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 - -import os -import unittest -from ppdet.core.workspace import load_config -from ppdet.engine import Trainer - -class TestMultiScaleInference(unittest.TestCase): - def setUp(self): - self.set_config() - - def set_config(self): - self.mstest_cfg_file = 'configs/faster_rcnn/faster_rcnn_r34_fpn_multiscaletest_1x_coco.yml' - - # test evaluation with multi scale test - def test_eval_mstest(self): - cfg = load_config(self.mstest_cfg_file) - trainer = Trainer(cfg, mode='eval') - - cfg.weights = 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_1x_coco.pdparams' - trainer.load_weights(cfg.weights) - - trainer.evaluate() - - # test inference with multi scale test - def test_infer_mstest(self): - cfg = load_config(self.mstest_cfg_file) - trainer = Trainer(cfg, mode='test') - - cfg.weights = 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_1x_coco.pdparams' - trainer.load_weights(cfg.weights) - tests_img_root = os.path.join(os.path.dirname(__file__), 'imgs') - - # input images to predict - imgs = ['coco2017_val2017_000000000139.jpg', 'coco2017_val2017_000000000724.jpg'] - imgs = [os.path.join(tests_img_root, img) for img in imgs] - trainer.predict(imgs, - draw_threshold=0.5, - output_dir='output', - save_txt=True) - - -if __name__ == '__main__': - unittest.main()