@misc{CV2018,
author = {Donny You (youansheng@gmail.com)},
howpublished = {\url{https://github.com/youansheng/pytorch-cv}},
year = {2018}
}
This repository provides source code for some cv problems. We do our best to keep this repository up to date. If you do find a problem about this repository, please raise this as an issue. We will fix it immediately.
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- Convolutional Pose Machines
- Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
- Associative Embedding: End-to-End Learning for Joint Detection and Grouping
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- SSD: Single Shot MultiBox Detector
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- Efficient ConvNet for Real-time Semantic Segmentation
- Train the openpose model
python main.py --hypes hypes/pose/coco/op_coco_pose.json \
--base_lr 0.001 \
--phase train- Finetune the openpose model
python main.py --hypes hypes/pose/coco/op_coco_pose.json \
--base_lr 0.001 \
--phase train \
--resume checkpoints/pose/coco/coco_open_pose_65000.pth- Test the openpose model(test_img):
python main.py --hypes hypes/pose/coco/op_coco_pose.json \
--phase test \
--resume checkpoints/pose/coco/coco_open_pose_65000.pth \
--test_img val/samples/ski.jpg- Test the openpose model(test_dir):
python main.py --hypes hypes/pose/coco/op_coco_pose.json \
--phase test \
--resume checkpoints/pose/coco/coco_open_pose_65000.pth \
--test_dir val/samples- Create the submission:
python main.py --hypes hypes/pose/coco/op_coco_pose.json \
--phase submission \
--resume checkpoints/pose/coco/coco_open_pose_65000.pth \
--test_dir coco_test_dir- Attention: Other command line parameters are showed in main file. You can refer & use them.