This repo is implemented based on detectron2 and CenterNet
- Support imgaug data augmentation
- Support swa
- Support Knowledge Distill, teacher-student, designed by myself
- Support other LR_SCHEDULER
- Support Optimizer RangerLars, not convergence in COCO
- We provide some examples and scripts to convert centerX to Caffe, ONNX and TensorRT format in projects/speedup
- [️✔] Support simple inference
- [✔] Support to caffe, onnx, tensorRT
- Support keypoints
- Python >= 3.7
- PyTorch >= 1.5
- torchvision that matches the PyTorch installation.
- OpenCV
- pycocotools
pip install cython; pip install 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'
- GCC >= 4.9
gcc --version
- detectron2
pip install -U 'git+https://github.com/CPFLAME/detectron2.git'
pip install git+https://github.com/pabloppp/pytorch-tools -U
the same as detectron2
modify your yamls in run.sh
sh run.sh
modify your yamls in run.sh, add eval-only and MODEL.WEIGHTS in your setting
sh run.sh
This repo use less training time to get a competitive performance compared to other versions
Backbone ResNet-50
Code | mAP | epoch |
---|---|---|
centerX | 33.2 | 70 |
centerX | 34.3 | 140 |
centernet-better | 34.9 | 140 |
Backbone ResNet-18
centerX_KD means ResNet-50(33.2) as teacher, ResNet-18(27.9) as student, Knowledge Distill for 70 epoch in coco.
Code | mAP | epoch |
---|---|---|
centerX | 30.2 | 140 |
centerX | 27.9 | 70 |
centerX_KD | 31.0 | 70 |
centernet-better | 29.8 | 140 |
centernet | 28.1 | 140 |
- optim: SGD
- lr: 0.02
- scheduler: WarmupMultiStepLR ,drop 0.1 in (50, 62) for 80 epoch; (90 ,120) for 140 epoch
- train size: 512 max size
- test size: 512 max size
- batch size: 64
- woGT: KD only use teacher loss
Backbone | mAP | mAP50 | mAP75 | epoch | teacher | student_pretrain |
---|---|---|---|---|---|---|
resdcn18 | 31.2 | 56.6 | 30.8 | 80 | - | - |
resdcn18_swa | 31.1 | 56.6 | 30.4 | 80 | - | - |
resdcn18_syncBN | 31.3 | 56.6 | 30.7 | 80 | - | - |
resdcn18_imgaug | 29.6 | 54.7 | 28.9 | 80 | - | - |
resdcn18_KD | 34.5 | 60.2 | 34.3 | 80 | resdcn50 | resdcn18 |
resdcn18_KD_woGT | 33.0 | 58.3 | 32.7 | 80 | resdcn50 | resdcn18 |
resdcn18_KD_woGT_scratch | 32.8 | 58.1 | 32.6 | 140 | resdcn50 | imagenet |
resdcn50 | 35.1 | 61.2 | 35.3 | 80 | - | - |
Generalization performance for Knowledge Distill
Backbone | crowd mAP | coco_person mAP | epoch | teacher | student_pretrain | train_set |
---|---|---|---|---|---|---|
resdcn50 | 35.1 | 35.7 | 80 | - | - | crowd |
resdcn18(baseline) | 31.2 | 31.2 | 80 | - | - | crowd |
resdcn18_KD | 34.5 | 34.9 | 80 | resdcn50 | resdcn18 | crowd |
resdcn18_KD_woGT_scratch | 32.8 | 34.2 | 140 | resdcn50 | imagenet | crowd |
resdcn18_KD_woGT_scratch | 34.1 | 36.3 | 140 | resdcn50 | imagenet | crowd+coco |
Backbone | mAP crowd | mAP coco_car | epoch | teacher | student_pretrain | train_set |
---|---|---|---|---|---|---|
1.resdcn50 | 35.1 | - | 80 | - | - | crowd |
2.resdcn18 | 31.7 | - | 70 | - | - | crowd |
3.resdcn50 | - | 31.6 | 70 | - | - | coco_car |
4.resdcn18 | - | 27.8 | 70 | - | - | coco_car |
resdcn18_KD_woGT_scratch | 31.6 | 29.4 | 140 | 1,3 | imagenet | crowd+coco_car |
Backbone | mAP crowd_human | mAP widerface | epoch | teacher | student_pretrain | train_set |
---|---|---|---|---|---|---|
1.resdcn50 | 35.1 | - | 80 | - | - | crowd |
2.resdcn18 | 31.7 | - | 70 | - | - | crowd |
3.resdcn50 | - | 32.9 | 70 | - | - | widerface |
4.resdcn18 | - | 29.6 | 70 | - | - | widerface |
5.resdcn18_ignore_nolabel | 29.1 | 24.2 | 140 | - | - | crowd+wider |
6.resdcn18_pseudo_label | 28.9 | 27.7 | 140 | - | - | crowd+wider |
7.resdcn18_KD_woGT_scratch | 31.3 | 32.1 | 140 | 1,3 | imagenet | crowd+wider |
centerX is released under the Apache 2.0 license.