Applications -> examples

Applications/HumanSeg/utils/__init__.py

-# Copyright (c) 2020 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 . import humanseg_postprocess

Applications/HumanSeg/README.md → examples/human_segmentation/README.md

@@ -7,8 +7,6 @@
 **前置依赖**
 * paddlepaddle >= 1.8.0
 * python >= 3.5
-* cython
-* pycocotools
 
 ```
 pip install paddlex -i https://mirror.baidu.com/pypi/simple
@@ -95,6 +93,10 @@ python bg_replace.py --model_dir pretrain_weights/humanseg_mobile_inference --im
 ## 训练
 使用下述命令基于与训练模型进行Fine-tuning，请确保选用的模型结构`model_type`与模型参数`pretrain_weights`匹配。
 ```bash
+# 指定GPU卡号（以0号卡为例）
+export CUDA_VISIBLE_DEVICES=0
+# 若不使用GPU，则将CUDA_VISIBLE_DEVICES指定为空
+# export CUDA_VISIBLE_DEVICES=
 python train.py --model_type HumanSegMobile \
 --save_dir output/ \
 --data_dir data/mini_supervisely \
@@ -177,7 +179,3 @@ python quant_offline.py --model_dir output/best_model \
 * `--quant_list`: 量化数据集列表路径，一般直接选择训练集或验证集
 * `--save_dir`: 量化模型保存路径
 * `--image_shape`: 网络输入图像大小（w, h）
-
-## AIStudio在线教程
-
-我们在AI Studio平台上提供了人像分割在线体验的教程，[点击体验](https://aistudio.baidu.com/aistudio/projectdetail/475345)

Applications/HumanSeg/utils/humanseg_postprocess.py → examples/human_segmentation/postprocess.py

@@ -16,7 +16,8 @@
 import numpy as np
 
 
-def human_seg_tracking(pre_gray, cur_gray, prev_cfd, dl_weights, disflow):
+def cal_optical_flow_tracking(pre_gray, cur_gray, prev_cfd, dl_weights,
+                              disflow):
     """计算光流跟踪匹配点和光流图
     输入参数:
         pre_gray: 上一帧灰度图
@@ -59,7 +60,7 @@ def human_seg_tracking(pre_gray, cur_gray, prev_cfd, dl_weights, disflow):
     return track_cfd, is_track, dl_weights
 
 
-def human_seg_track_fuse(track_cfd, dl_cfd, dl_weights, is_track):
+def fuse_optical_flow_tracking(track_cfd, dl_cfd, dl_weights, is_track):
     """光流追踪图和人像分割结构融合
     输入参数:
         track_cfd: 光流追踪图
@@ -116,9 +117,9 @@ def postprocess(cur_gray, scoremap, prev_gray, pre_cfd, disflow, is_init):
         fusion_cfd = cur_cfd
     else:
         weights = np.ones((h, w), np.float32) * 0.3
-        track_cfd, is_track, weights = human_seg_tracking(
+        track_cfd, is_track, weights = cal_optical_flow_tracking(
             prev_gray, cur_gray, pre_cfd, weights, disflow)
-        fusion_cfd = human_seg_track_fuse(track_cfd, cur_cfd, weights,
-                                          is_track)
+        fusion_cfd = fuse_optical_flow_tracking(track_cfd, cur_cfd, weights,
+                                                is_track)
 
     return fusion_cfd

Applications/HumanSeg/train.py → examples/human_segmentation/train.py

@@ -13,11 +13,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import os
-# 选择使用0号卡
-os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# 使用CPU
-#os.environ['CUDA_VISIBLE_DEVICES'] = ''
 import argparse
 
 import paddlex as pdx

Applications/HumanSeg/video_infer.py → examples/human_segmentation/video_infer.py

@@ -19,7 +19,7 @@ import os.path as osp
 import cv2
 import numpy as np
 
-from utils.humanseg_postprocess import postprocess, threshold_mask
+from postprocess import postprocess, threshold_mask
 import paddlex as pdx
 import paddlex.utils.logging as logging
 from paddlex.seg import transforms