add experiments and fix typo

This commit is contained in:
XingyiZhou 2019-04-17 09:53:59 -05:00
parent d74e0e9392
commit be7019023b
20 changed files with 170 additions and 2 deletions

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# Objects as Points
Object detection, 3D detection, and pose estimation using center point detection:
![](readme/fig2.png)
> [**Objects as Points**](https://arxiv.org/abs/xxxx.xxxxx),
> [**Objects as Points**](http://arxiv.org/abs/1904.07850),
> Xingyi Zhou, Dequan Wang, Philipp Krähenbühl,
> *arXiv technical report ([arXiv 1904.07850](http://arxiv.org/abs/1904.07850))*
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Similarly, for human pose estimation, run:
~~~
python demo.py multi_hp --demo /path/to/image/or/folder/or/video/or/webcam --load_model ../models/multi_pose_dla_3x.pth
python demo.py multi_pose --demo /path/to/image/or/folder/or/video/or/webcam --load_model ../models/multi_pose_dla_3x.pth
~~~
The result for the example images should look like:

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cd src
# train
python main.py ctdet --exp_id coco_dla_1x --batch_size 128 --master_batch 9 --lr 5e-4 --gpus 0,1,2,3,4,5,6,7 --num_workers 16
# test
python test.py ctdet --exp_id coco_dla_1x --keep_res --resume
# flip test
python test.py ctdet --exp_id coco_dla_1x --keep_res --resume --flip_test
# multi scale test
python test.py ctdet --exp_id coco_dla_1x --keep_res --resume --flip_test --test_scales 0.5,0.75,1,1.25,1.5
cd ..

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cd src
# train
python main.py ctdet --exp_id coco_dla_2x --batch_size 128 --master_batch 9 --lr 5e-4 --gpus 0,1,2,3,4,5,6,7 --num_workers 16 --num_epochs 230 lr_step 180,210
# or use the following command if your have coco_s2_dla_1x trained
# python main.py ctdet --exp_id coco_dla_2x --batch_size 128 --master_batch 9 --lr 5e-4 --gpus 0,1,2,3,4,5,6,7 --num_workers 16 --load_model ../exp/ctdet/coco_dla_1x/model_90.pth --resume
# test
python test.py ctdet --exp_id coco_dla_2x --keep_res --resume
# flip test
python test.py ctdet --exp_id coco_dla_2x --keep_res --resume --flip_test
# multi scale test
python test.py ctdet --exp_id coco_dla_2x --keep_res --resume --flip_test --test_scales 0.5,0.75,1,1.25,1.5
cd ..

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cd src
# train
python main.py ctdet --exp_id coco_hg --arch hourglass --batch_size 24 --master_batch 4 --lr 2.5e-4 --load_model ../models/ExtremeNet_500000.pth --gpus 0,1,2,3,4
# test
python test.py ctdet --exp_id coco_hg --arch hourglass --keep_res --resume
# flip test
python test.py ctdet --exp_id coco_hg --arch hourglass --keep_res --resume --flip_test
# multi scale test
python test.py ctdet --exp_id coco_hg --arch hourglass --keep_res --resume --flip_test --test_scales 0.5,0.75,1,1.25,1.5
cd ..

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cd src
# train
python main.py ctdet --exp_id coco_resdcn101 --arch resdcn_101 --batch_size 96 --master_batch 5 --lr 3.75e-4 --gpus 0,1,2,3,4,5,6,7 --num_workers 16
# test
python test.py ctdet --exp_id coco_resdcn101 --keep_res --resume
# flip test
python test.py ctdet --exp_id coco_resdcn101 --keep_res --resume --flip_test
# multi scale test
python test.py ctdet --exp_id coco_resdcn101 --keep_res --resume --flip_test --test_scales 0.5,0.75,1,1.25,1.5
cd ..

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cd src
# train
python main.py ctdet --exp_id coco_resdcn18 --arch resdcn_18 --batch_size 114 --master_batch 18 --lr 5e-4 --gpus 0,1,2,3 --num_workers 16
# test
python test.py ctdet --exp_id coco_resdcn18 --arch resdcn_18 --keep_res --resume
# flip test
python test.py ctdet --exp_id coco_resdcn18 --arch resdcn_18 --keep_res --resume --flip_test
# multi scale test
python test.py ctdet --exp_id coco_resdcn18 --arch resdcn_18 --keep_res --resume --flip_test --test_scales 0.5,0.75,1,1.25,1.5
cd ..

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cd src
# train
python main.py ctdet --exp_id pascal_dla_384 --dataset pascal --num_epochs 70 --lr_step 45,60
# test
python test.py ctdet --exp_id pascal_dla_384 --dataset pascal --resume
# flip test
python test.py ctdet --exp_id pascal_dla_384 --dataset pascal --resume --flip_test
cd ..

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cd src
# train
python main.py ctdet --exp_id pascal_dla_512 --dataset pascal --input_res 512 --num_epochs 70 --lr_step 45,60 --gpus 0,1
# test
python test.py ctdet --exp_id pascal_dla_512 --dataset pascal --input_res 512 --resume
# flip test
python test.py ctdet --exp_id pascal_dla_512 --dataset pascal --input_res 512 --resume --flip_test
cd ..

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cd src
# train
python main.py ctdet --exp_id pascal_resdcn101_384 --arch resdcn_101 --dataset pascal --num_epochs 70 --lr_step 45,60 --gpus 0,1
# test
python test.py ctdet --exp_id pascal_resdcn101_384 --arch resdcn_101 --dataset pascal --resume
# flip test
python test.py ctdet --exp_id pascal_resdcn101_384 --arch resdcn_101 --dataset pascal --resume --flip_test
cd ..

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cd src
# train
python main.py ctdet --exp_id pascal_resdcn101_512 --arch resdcn_101 --dataset pascal --input_res 512 --num_epochs 70 --lr_step 45,60 --gpus 0,1,2,3
# test
python test.py ctdet --exp_id pascal_resdcn101_512 --arch resdcn_101 --dataset pascal --input_res 512 --resume
# flip test
python test.py ctdet --exp_id pascal_resdcn101_512 --arch resdcn_101 --dataset pascal --input_res 512 --resume --flip_test
cd ..

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cd src
# train
python main.py ctdet --exp_id pascal_resdcn18_384 --arch resdcn_18 --dataset pascal --num_epochs 70 --lr_step 45,60
# test
python test.py ctdet --exp_id pascal_resdcn18_384 --arch resdcn_18 --dataset pascal --resume
# flip test
python test.py ctdet --exp_id pascal_resdcn18_384 --arch resdcn_18 --dataset pascal --resume --flip_test
cd ..

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cd src
# train
python main.py ctdet --exp_id pascal_resdcn18_512 --arch resdcn_18 --dataset pascal --input_res 512 --num_epochs 70 --lr_step 45,60
# test
python test.py ctdet --exp_id pascal_resdcn18_512 --arch resdcn_18 --dataset pascal --input_res 512 --resume
# flip test
python test.py ctdet --exp_id pascal_resdcn18_512 --arch resdcn_18 --dataset pascal --input_res 512 --resume --flip_test
cd ..

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experiments/ddd_3dop.sh Normal file
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cd src
# train
python main.py ddd --exp_id 3dop --dataset kitti --kitti_split 3dop --batch_size 16 --master_batch 7 --num_epochs 70 --lr_step 45,60 --gpus 0,1
# test
python test.py ddd --exp_id 3dop --dataset kitti --kitti_split 3dop --resume
cd ..

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experiments/ddd_sub.sh Normal file
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cd src
# train
python main.py ddd --exp_id sub --dataset kitti --kitti_split subcnn --batch_size 16 --master_batch 7 --num_epochs 70 --lr_step 45,60 --gpus 0,1
# test
python test.py ddd --exp_id sub --dataset kitti --kitti_split subcnn --resume
cd ..

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cd src
# train
python main.py exdet --exp_id coco_dla --batch_size 64 --master_batch 1 --lr 2.5e-4 --gpus 0,1,2,3,4,5,6,7 --num_workers 8
# test
python test.py exdet --exp_id coco_dla --keep_res --resume
# flip test
python test.py exdet --exp_id coco_dla --keep_res --resume --flip_test
# multi scale test
python test.py exdet --exp_id coco_dla --keep_res --resume --flip_test --test_scales 0.5,0.75,1,1.25,1.5
cd ..

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cd src
# train
python main.py exdet --exp_id coco_hg --arch hourglass --batch_size 24 --master_batch 4 --lr 2.5e-4 --gpus 0,1,2,3,4
# test
python test.py exdet --exp_id coco_hg --arch hourglass --keep_res --resume
# flip test
python test.py exdet --exp_id coco_hg --arch hourglass --keep_res --resume --flip_test
# multi scale test
python test.py exdet --exp_id coco_hg --arch hourglass --keep_res --resume --flip_test --test_scales 0.5,0.75,1,1.25,1.5
cd ..

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cd src
# train
python main.py multi_pose --exp_id dla_1x --batch_size 128 --master_batch 9 --lr 5e-4 --load_model ../models/ctdet_coco_dla_2x.pth --gpus 0,1,2,3,4,5,6,7 --num_workers 16
# test
python test.py multi_pose --exp_id dla_1x --keep_res --resume
# flip test
python test.py multi_pose --exp_id dla_1x --keep_res --resume --flip_test
cd ..

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cd src
# train
python main.py multi_pose --exp_id dla_3x --batch_size 128 --master_batch 9 --lr 5e-4 --load_model ../models/ctdet_coco_dla_2x.pth --gpus 0,1,2,3,4,5,6,7 --num_workers 16 --num_epochs 320 lr_step 270,300
# or use the following command if your have dla_1x trained
# python main.py multi_pose --exp_id dla_3x --batch_size 128 --master_batch 9 --lr 5e-4 --gpus 0,1,2,3,4,5,6,7 --num_workers 16 --load_model ../exp/multi_pose/dla_1x/model_90.pth --resume
# test
python test.py multi_pose --exp_id dla_3x --keep_res --resume
# flip test
python test.py multi_pose --exp_id dla_3x --keep_res --resume --flip_test
cd ..

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cd src
# train
python main.py multi_pose --exp_id hg_1x --arch hourglass --batch_size 24 --master_batch 4 --lr 2.5e-4 --load_model ../models/ctdet_coco_hg.pth --gpus 0,1,2,3,4 --num_epochs 50 --lr_step 40
# test
python test.py multi_pose --exp_id hg_1x --arch hourglass --keep_res --resume
# flip test
python test.py multi_pose --exp_id hg_1x --arch hourglass --keep_res --resume --flip_test
cd ..

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cd src
# train
python main.py multi_pose --exp_id hg_3x --arch hourglass --batch_size 24 --master_batch 4 --lr 2.5e-4 -load_model ../models/ctdet_coco_hg.pth --gpus 0,1,2,3,4 --num_epochs 150 --lr_step 130
# or use the following command if your have dla_1x trained
# python main.py multi_pose --exp_id hg_3x --arch hourglass --batch_size 24 --master_batch 4 --lr 2.5e-4 --gpus 0,1,2,3,4 --num_epochs 150 --lr_step 130 --load_model ../exp/multi_pose/hg_1x/model_40.pth --resume
# test
python test.py multi_pose --exp_id hg_3x --arch hourglass --keep_res --resume
# flip test
python test.py multi_pose --exp_id hg_3x --arch hourglass --keep_res --resume --flip_test
cd ..