This page includes various examples on visualization.
For tasks like classification and pose estimation, which need only one image as input, you should modify your test image in imgs/single.json
.
To visualize the result of attribute recognition model,
python3 launch.py --config configs/attr_deepmar/deepmar_rapv2_r50v1.py --task visualize --image imgs/single.json
To visualize the result of pose estimation model,
python3 launch.py --config configs/pose_simple_baseline/simple_pose_r50v1.py --task visualize --image imgs/single.json
To visualize the result of densepose model,
python3 launch.py --config configs/densepose_baseline/dense_pose_r50v1.py --task visualize --image imgs/single.json
For person re-identification, you should input two images. The input setting is formatted in imgs/pair.json
.
To visualize the result of re-identification model,
python3 launch.py --config configs/reid_strong_baseline/strong_baseline_market1501_r50v1_xent_tri_cent.py --task visualize --image imgs/pair.json