From c3d2e6c9d8e34d3d85d2c4c9df4136bae4df4577 Mon Sep 17 00:00:00 2001 From: qingqing01 Date: Mon, 21 Oct 2019 14:04:49 +0800 Subject: [PATCH] Fix testing in pose model for COCO (#3682) --- PaddleCV/human_pose_estimation/README.md | 3 ++ PaddleCV/human_pose_estimation/README_cn.md | 3 ++ PaddleCV/human_pose_estimation/test.py | 38 ++++++++++----------- 3 files changed, 25 insertions(+), 19 deletions(-) diff --git a/PaddleCV/human_pose_estimation/README.md b/PaddleCV/human_pose_estimation/README.md index 37c5d81e..9f73af3d 100644 --- a/PaddleCV/human_pose_estimation/README.md +++ b/PaddleCV/human_pose_estimation/README.md @@ -108,9 +108,12 @@ We also support to apply pre-trained models on customized images. Put the images into the folder `test` under the directory root of this repo. Then run ```bash +# default is MPII dataset python test.py --checkpoint checkpoints/pose-resnet-50-384x384-mpii ``` +`python test.py --help` for more usage. + If there are multiple persons in images, detectors such as [Faster R-CNN](https://github.com/PaddlePaddle/models/tree/develop/fluid/PaddleCV/rcnn), [SSD](https://github.com/PaddlePaddle/models/tree/develop/fluid/PaddleCV/object_detection) or others should be used first to crop them out. Because the simple baseline for human pose estimation is a top-down method. ## Reference diff --git a/PaddleCV/human_pose_estimation/README_cn.md b/PaddleCV/human_pose_estimation/README_cn.md index 474fe1e6..ce8c976d 100644 --- a/PaddleCV/human_pose_estimation/README_cn.md +++ b/PaddleCV/human_pose_estimation/README_cn.md @@ -107,9 +107,12 @@ python train.py --dataset 'mpii' 将测试图片放入根目录下的'test'文件夹中，执行 ```bash +# 默认是MPII数据集 python test.py --checkpoint 'checkpoints/pose-resnet-50-384x384-mpii' ``` +`python test.py --help`获取更多的用法。 + ## 引用 - Simple Baselines for Human Pose Estimation and Tracking in PyTorch [`code`](https://github.com/Microsoft/human-pose-estimation.pytorch#data-preparation) diff --git a/PaddleCV/human_pose_estimation/test.py b/PaddleCV/human_pose_estimation/test.py index ba015a4e..6e39cc77 100644 --- a/PaddleCV/human_pose_estimation/test.py +++ b/PaddleCV/human_pose_estimation/test.py @@ -12,7 +12,6 @@ # See the License for the specific language governing permissions and # limitations under the License. ############################################################################## - """Functions for inference.""" import sys @@ -46,23 +45,27 @@ def print_immediately(s): def test(args): - import lib.mpii_reader as reader if args.dataset == 'coco': + import lib.coco_reader as reader IMAGE_SIZE = [288, 384] - FLIP_PAIRS = [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10], [11, 12], [13, 14], [15, 16]] + FLIP_PAIRS = [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10], [11, 12], + [13, 14], [15, 16]] args.kp_dim = 17 elif args.dataset == 'mpii': + import lib.mpii_reader as reader IMAGE_SIZE = [384, 384] FLIP_PAIRS = [[0, 5], [1, 4], [2, 3], [10, 15], [11, 14], [12, 13]] args.kp_dim = 16 else: - raise ValueError('The dataset {} is not supported yet.'.format(args.dataset)) + raise ValueError('The dataset {} is not supported yet.'.format( + args.dataset)) print_arguments(args) # Image and target - image = layers.data(name='image', shape=[3, IMAGE_SIZE[1], IMAGE_SIZE[0]], dtype='float32') - file_id = layers.data(name='file_id', shape=[1,], dtype='int') + image = layers.data( + name='image', shape=[3, IMAGE_SIZE[1], IMAGE_SIZE[0]], dtype='float32') + file_id = layers.data(name='file_id', shape=[1, ], dtype='int') # Build model model = pose_resnet.ResNet(layers=50, kps_num=args.kp_dim, test_mode=True) @@ -82,9 +85,9 @@ def test(args): feeder = fluid.DataFeeder(place=place, feed_list=[image, file_id]) test_exe = fluid.ParallelExecutor( - use_cuda=True if args.use_gpu else False, - main_program=fluid.default_main_program().clone(for_test=True), - loss_name=None) + use_cuda=True if args.use_gpu else False, + main_program=fluid.default_main_program().clone(for_test=True), + loss_name=None) fetch_list = [image.name, output.name] @@ -96,22 +99,18 @@ def test(args): for i in range(num_images): file_ids.append(data[i][1]) - input_image, out_heatmaps = test_exe.run( - fetch_list=fetch_list, - feed=feeder.feed(data)) + input_image, out_heatmaps = test_exe.run(fetch_list=fetch_list, + feed=feeder.feed(data)) if args.flip_test: # Flip all the images in a same batch data_fliped = [] for i in range(num_images): - data_fliped.append(( - data[i][0][:, :, ::-1], - data[i][1])) + data_fliped.append((data[i][0][:, :, ::-1], data[i][1])) # Inference again - _, output_flipped = test_exe.run( - fetch_list=fetch_list, - feed=feeder.feed(data_fliped)) + _, output_flipped = test_exe.run(fetch_list=fetch_list, + feed=feeder.feed(data_fliped)) # Flip back output_flipped = flip_back(output_flipped, FLIP_PAIRS) @@ -123,7 +122,8 @@ def test(args): # Aggregate out_heatmaps = (out_heatmaps + output_flipped) * 0.5 - save_predict_results(input_image, out_heatmaps, file_ids, fold_name='results') + save_predict_results( + input_image, out_heatmaps, file_ids, fold_name='results') if __name__ == '__main__': -- GitLab