Two-stage CenterNet

Overview

Probabilistic two-stage detection

Two-stage object detectors that use class-agnostic one-stage detectors as the proposal network.

Probabilistic two-stage detection,
Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl,
arXiv technical report (arXiv 2103.07461)

Contact: [email protected]. Any questions or discussions are welcomed!

Abstract

We develop a probabilistic interpretation of two-stage object detection. We show that this probabilistic interpretation motivates a number of common empirical training practices. It also suggests changes to two-stage detection pipelines. Specifically, the first stage should infer proper object-vs-background likelihoods, which should then inform the overall score of the detector. A standard region proposal network (RPN) cannot infer this likelihood sufficiently well, but many one-stage detectors can. We show how to build a probabilistic two-stage detector from any state-of-the-art one-stage detector. The resulting detectors are faster and more accurate than both their one- and two-stage precursors. Our detector achieves 56.4 mAP on COCO test-dev with single-scale testing, outperforming all published results. Using a lightweight backbone, our detector achieves 49.2 mAP on COCO at 33 fps on a Titan Xp.

Summary

  • Two-stage CenterNet: First stage estimates object probabilities, second stage conditionally classifies objects.

  • Resulting detector is faster and more accurate than both traditional two-stage detectors (fewer proposals required), and one-stage detectors (lighter first stage head).

  • Our best model achieves 56.4 mAP on COCO test-dev.

  • This repo also includes a detectron2-based CenterNet implementation with better accuracy (42.5 mAP at 70FPS) and a new FPN version of CenterNet (40.2 mAP with Res50_1x).

Main results

All models are trained with multi-scale training, and tested with a single scale. The FPS is tested on a Titan RTX GPU. More models and details can be found in the MODEL_ZOO.

COCO

Model COCO val mAP FPS
CenterNet-S4_DLA_8x 42.5 71
CenterNet2_R50_1x 42.9 24
CenterNet2_X101-DCN_2x 49.9 8
CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST 56.1 5
CenterNet2_DLA-BiFPN-P5_24x_ST 49.2 38

LVIS

Model val mAP box
CenterNet2_R50_1x 26.5
CenterNet2_FedLoss_R50_1x 28.3

Objects365

Model val mAP
CenterNet2_R50_1x 22.6

Installation

Our project is developed on detectron2. Please follow the official detectron2 installation. All our code is under projects/CenterNet2/. In theory, you should be able to copy-paste projects/CenterNet2/ to the latest detectron2 release or your own detectron2 repo to run our project. There might be API changes in future detectron2 releases that make it incompatible.

Demo

We use the default detectron2 demo script. To run inference on an image folder using our pre-trained model, run

python projects/CenterNet2/demo/demo.py --config-file projects/CenterNet2/configs/CenterNet2_R50_1x.yaml --input path/to/image/ --opts MODEL.WEIGHTS models/CenterNet2_R50_1x.pth

Benchmark evaluation and training

Please check detectron2 GETTING_STARTED.md for running evaluation and training. Our config files are under projects/CenterNet2/configs and the pre-trained models are in the MODEL_ZOO.

License

Our code under projects/CenterNet2/ is under Apache 2.0 license. projects/CenterNet2/centernet/modeling/backbone/bifpn_fcos.py are from AdelaiDet, which follows the original non-commercial license. The code from detectron2 follows the original Apache 2.0 license.

Citation

If you find this project useful for your research, please use the following BibTeX entry.

@inproceedings{zhou2021probablistic,
  title={Probabilistic two-stage detection},
  author={Zhou, Xingyi and Koltun, Vladlen and Kr{\"a}henb{\"u}hl, Philipp},
  booktitle={arXiv preprint arXiv:2103.07461},
  year={2021}
}
Comments
  • GPU memory is not fully used.

    GPU memory is not fully used.

    I have "cuda out of memory error" whereas in pytorch uses only 60% of my GPU memory. Can you help me with this issue? My GPU is RTX3090 wtih 24GB VRAM. However model only uses up to 15-16GB.

    opened by shoxa-mir 7
  • What are the difference Custom ROI head layers?

    What are the difference Custom ROI head layers?

    📚 Documentation

    Hi! Again. Thanks for opensouring the code. I wonder the main differences between "CustomCascadeROIHeads" "CustomFastRCNNOutputLayers" and original "CascadeROIHeads" and "FastRCNNOutputLayers" ?

    What are the results of using original modules by replacing RPN with CenterNet ?

    documentation 
    opened by lxtGH 7
  • problem with registering custom dataset

    problem with registering custom dataset

    command Line Args: Namespace(config_file='/content/CenterNet2/projects/CenterNet2/configs/CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST.yaml', dist_url='tcp://127.0.0.1:23538', eval_only=False, machine_rank=0, manual_device='', num_gpus=1, num_machines=1, opts=[], resume=False) Config '/content/CenterNet2/projects/CenterNet2/configs/CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST.yaml' has no VERSION. Assuming it to be compatible with latest v2. Traceback (most recent call last): File "/content/CenterNet2/projects/CenterNet2/train_net.py", line 227, in args=(args,), File "/usr/local/lib/python3.7/dist-packages/detectron2/engine/launch.py", line 62, in launch main_func(*args) File "/content/CenterNet2/projects/CenterNet2/train_net.py", line 187, in main cfg = setup(args) File "/content/CenterNet2/projects/CenterNet2/train_net.py", line 175, in setup cfg.merge_from_file(args.config_file) File "/usr/local/lib/python3.7/dist-packages/detectron2/config/config.py", line 54, in merge_from_file self.merge_from_other_cfg(loaded_cfg) File "/usr/local/lib/python3.7/dist-packages/fvcore/common/config.py", line 123, in merge_from_other_cfg return super().merge_from_other_cfg(cfg_other) File "/usr/local/lib/python3.7/dist-packages/yacs/config.py", line 217, in merge_from_other_cfg _merge_a_into_b(cfg_other, self, self, []) File "/usr/local/lib/python3.7/dist-packages/yacs/config.py", line 474, in _merge_a_into_b v = _check_and_coerce_cfg_value_type(v, b[k], k, full_key) File "/usr/local/lib/python3.7/dist-packages/yacs/config.py", line 537, in _check_and_coerce_cfg_value_type original_type, replacement_type, original, replacement, full_key ValueError: Type mismatch (<class 'detectron2.config.config.CfgNode'> vs. <class 'str'>) with values (PRECOMPUTED_PROPOSAL_TOPK_TEST: 1000 PRECOMPUTED_PROPOSAL_TOPK_TRAIN: 2000 PROPOSAL_FILES_TEST: () PROPOSAL_FILES_TRAIN: () TEST: () TRAIN: () vs. TRAIN = ('my_dataset_train',) TEST = ('my_dataset_test',)) for config key: DATASETS

    thanks for this amazing work , I am running into this issue after I register my dataset i am using colab and before running !python /content/CenterNet2/projects/CenterNet2/train_net.py --config /content/CenterNet2/projects/CenterNet2/configs/CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST.yaml I am registering the dataset like this from detectron2.data.datasets import register_coco_instances register_coco_instances("my_dataset_train", {}, "/content/results/yolo2coco/train.json", "/content/results/yolo2coco/train") #register_coco_instances("my_dataset_val", {}, "/content/results/yolo2coco/test.json", "/content/results/yolo2coco/valid") register_coco_instances("my_dataset_test", {}, "/content/results/yolo2coco/test.json", "/content/results/yolo2coco/test") and adding the name my_dataset_train and my_dataset_test in config Could you please help me out .

    opened by gauravlochab 7
  • KeyError: 'Non-existent config key: MODEL.ROI_BOX_HEAD.MULT_PROPOSAL_SCORE'

    KeyError: 'Non-existent config key: MODEL.ROI_BOX_HEAD.MULT_PROPOSAL_SCORE'

    when I am trying to train the center2 with my own data, here is an error.

    File "/home/atesi3/anaconda3/envs/torch18/lib/python3.6/site-packages/yacs/config.py", line 491, in _merge_a_into_b raise KeyError("Non-existent config key: {}".format(full_key)) KeyError: 'Non-existent config key: MODEL.ROI_BOX_HEAD.MULT_PROPOSAL_SCORE'

    Which version of the yacs did you use? or which version of the detectron2? Plese help.

    opened by lbf4616 5
  • Custom dataset classes

    Custom dataset classes

    📚 Documentation

    • Links to the relevant documentation/comment: https://github.com/facebookresearch/detectron2/blob/master/datasets/README.md

    Hi, I wonder how to register custom dataset classes, since I already tried to train with custom dataset and getting this error.

    Traceback (most recent call last):
      File "train_net.py", line 228, in <module>
        args=(args,),
      File "/usr/local/lib/python3.7/dist-packages/detectron2/engine/launch.py", line 62, in launch
        main_func(*args)
      File "train_net.py", line 208, in main
        do_train(cfg, model, resume=args.resume)
      File "train_net.py", line 108, in do_train
        data_loader = build_detection_train_loader(cfg, mapper=mapper)
      File "/usr/local/lib/python3.7/dist-packages/detectron2/config/config.py", line 201, in wrapped
        explicit_args = _get_args_from_config(from_config, *args, **kwargs)
      File "/usr/local/lib/python3.7/dist-packages/detectron2/config/config.py", line 238, in _get_args_from_config
        ret = from_config_func(*args, **kwargs)
      File "/usr/local/lib/python3.7/dist-packages/detectron2/data/build.py", line 314, in _train_loader_from_config
        proposal_files=cfg.DATASETS.PROPOSAL_FILES_TRAIN if cfg.MODEL.LOAD_PROPOSALS else None,
      File "/usr/local/lib/python3.7/dist-packages/detectron2/data/build.py", line 227, in get_detection_dataset_dicts
        dataset_dicts = [DatasetCatalog.get(dataset_name) for dataset_name in names]
      File "/usr/local/lib/python3.7/dist-packages/detectron2/data/build.py", line 227, in <listcomp>
        dataset_dicts = [DatasetCatalog.get(dataset_name) for dataset_name in names]
      File "/usr/local/lib/python3.7/dist-packages/detectron2/data/catalog.py", line 58, in get
        return f()
      File "/usr/local/lib/python3.7/dist-packages/detectron2/data/datasets/coco.py", line 489, in <lambda>
        DatasetCatalog.register(name, lambda: load_coco_json(json_file, image_root, name))
      File "/usr/local/lib/python3.7/dist-packages/detectron2/data/datasets/coco.py", line 80, in load_coco_json
        meta.thing_classes = thing_classes
      File "/usr/local/lib/python3.7/dist-packages/detectron2/data/catalog.py", line 150, in __setattr__
        "to a different value!\n{} != {}".format(key, self.name, oldval, val)
    AssertionError: Attribute 'thing_classes' in the metadata of 'coco_2017_train' cannot be set to a different value!
    ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear', 'hair drier', 'toothbrush'] != ['class1', 'class2', 'class3']
    
    documentation 
    opened by salmanhiro 4
  • I got an error when I train CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST

    I got an error when I train CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST

    I trained : python ./tools/train_net.py --config-file ./configs/COCO-Detection/faster_rcnn_R_50_C4_1x.yaml --num-gpus 1 SOLVER.IMS_PER_BATCH 2 SOLVER.BASE_LR 0.0025 image Susccessful!! But I run : python ./projects/CenterNet2/train_net.py --config-file ./projects/CenterNet2/configs/CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST.yaml --num-gpus 1 SOLVER.IMS_PER_BATCH 2

    image There is an error, I don't know why?

    opened by marcovwu 3
  • CenterNet2_DLA-BiFPN-P5_640_24x_ST Config Missing

    CenterNet2_DLA-BiFPN-P5_640_24x_ST Config Missing

    📚 Documentation

    It looks like CenterNet2_DLA-BiFPN-P5_640_24x_ST config is missing and the link in the ModelZoo table is broken config. Is this configuration deprecated?

    documentation 
    opened by bakerada 2
  • Error :AssertionError: Box tensor contains infinite or NaN!

    Error :AssertionError: Box tensor contains infinite or NaN!

    📚 Documentation

    I used the coco dataset to train centernet2, but got a error:

    Traceback (most recent call last):
      File "./train_net.py", line 245, in <module>
        args=(args,),
      File "/dataset/datacode/code/CenterNet2/detectron2/engine/launch.py", line 62, in launch
        main_func(*args)
      File "./train_net.py", line 226, in main
        do_train(cfg, model, resume=args.resume)
      File "./train_net.py", line 128, in do_train
        loss_dict = model(data)
      File "/home/das/anaconda3/envs/centernet2/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
        result = self.forward(*input, **kwargs)
      File "/dataset/datacode/code/CenterNet2/detectron2/modeling/meta_arch/rcnn.py", line 166, in forward
        _, detector_losses = self.roi_heads(images, features, proposals, gt_instances)
      File "/home/das/anaconda3/envs/centernet2/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
        result = self.forward(*input, **kwargs)
      File "/dataset/datacode/code/CenterNet2/projects/CenterNet2/centernet/modeling/roi_heads/custom_roi_heads.py", line 166, in forward
        losses = self._forward_box(features, proposals, targets)
      File "/dataset/datacode/code/CenterNet2/projects/CenterNet2/centernet/modeling/roi_heads/custom_roi_heads.py", line 116, in _forward_box
        proposals = self._create_proposals_from_boxes(prev_pred_boxes, image_sizes)
      File "/dataset/datacode/code/CenterNet2/detectron2/modeling/roi_heads/cascade_rcnn.py", line 290, in _create_proposals_from_boxes
        boxes_per_image.clip(image_size)
      File "/dataset/datacode/code/CenterNet2/detectron2/structures/boxes.py", line 200, in clip
        assert torch.isfinite(self.tensor).all(), "Box tensor contains infinite or NaN!"
    AssertionError: Box tensor contains infinite or NaN!
    

    where is the main wrong? I think the coco dataset is OK

    documentation 
    opened by Lg955 2
  • The problem of training custom datasets

    The problem of training custom datasets

    Thanks for your great work! When I train my custom datasets, I used the command: python ./train_net.py --num-gpus 1 --config-file ./configs/CenterNet2_R50_1x.yaml but I met the follow problems: `No instances! torch.Size([0, 3]) torch.Size([0, 4]) 4 No instance in box reg loss No instances! torch.Size([0, 3]) torch.Size([0, 4]) 4 No instance in box reg loss No instances! torch.Size([0, 3]) torch.Size([0, 4]) 4 No instance in box reg loss No instances! torch.Size([0, 3]) torch.Size([0, 4]) 4 No instance in box reg loss No instances! torch.Size([0, 3]) torch.Size([0, 4]) 4 No instance in box reg loss No instances! torch.Size([0, 3]) torch.Size([0, 4]) 4 No instance in box reg loss No instances! torch.Size([0, 3]) torch.Size([0, 4]) 4 No instance in box reg loss No instances! torch.Size([0, 3]) torch.Size([0, 4]) 4 No instance in box reg loss No instances! torch.Size([0, 3]) torch.Size([0, 4]) 4 No instance in box reg loss No instances! torch.Size([0, 3]) torch.Size([0, 4]) 4 No instance in box reg loss Traceback (most recent call last): File "./train_net.py", line 237, in launch( File "e:\pytorchpro\centernet2-master\detectron2\engine\launch.py", line 62, in launch main_func(*args) File "./train_net.py", line 224, in main do_train(cfg, model, resume=args.resume) File "./train_net.py", line 128, in do_train loss_dict = model(data) File "D:\ProgramData\Anaconda3\envs\CenterNet2\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "e:\pytorchpro\centernet2-master\detectron2\modeling\meta_arch\rcnn.py", line 160, in forward proposals, proposal_losses = self.proposal_generator(images, features, gt_instances) File "D:\ProgramData\Anaconda3\envs\CenterNet2\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl result = self.forward(*input, **kwargs) File "E:\PytorchPro\CenterNet2-master\projects\CenterNet2\centernet\modeling\dense_heads\centernet.py", line 109, in forward losses = self.losses( File "E:\PytorchPro\CenterNet2-master\projects\CenterNet2\centernet\modeling\dense_heads\centernet.py", line 156, in losses assert (torch.isfinite(reg_pred).all().item()) AssertionError

    How can I solve the problem? Thank you !`

    opened by trustguan 2
  • Get error when run demo.py

    Get error when run demo.py

    run: python projects/CenterNet2/demo.py --config-file projects/CenterNet2/configs/CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST.yaml --opts MODEL.WEIGHTS models/CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST.pth --input images/tupian/* the error is below: WARNING [03/23 03:24:43 d2.config.compat]: Config 'projects/CenterNet2/configs/CenterNet2_R2-101-DCN-BiFPN_4x+4x_1560_ST.yaml' has no VERSION. Assuming it to be compatible with latest v2. Traceback (most recent call last): File "projects/CenterNet2/demo.py", line 78, in <module> cfg = setup_cfg(args) File "projects/CenterNet2/demo.py", line 28, in setup_cfg cfg.merge_from_list(args.opts) File "/opt/conda/lib/python3.8/site-packages/fvcore-0.1.3.post20210317-py3.8.egg/fvcore/common/config.py", line 134, in merge_from_list File "/opt/conda/lib/python3.8/site-packages/yacs-0.1.8-py3.8.egg/yacs/config.py", line 243, in merge_from_list _assert_with_logging(subkey in d, "Non-existent key: {}".format(full_key)) File "/opt/conda/lib/python3.8/site-packages/yacs-0.1.8-py3.8.egg/yacs/config.py", line 545, in _assert_with_logging assert cond, msg AssertionError: Non-existent key: --input

    opened by lfxx 2
  • when I start train 2 gpu though python train_net.py --config ./output/CenterNet2/CenterNet-S4_DLA_8x/config.yaml --num-gpus 2 ,when start test ,the model have wrong following :

    when I start train 2 gpu though python train_net.py --config ./output/CenterNet2/CenterNet-S4_DLA_8x/config.yaml --num-gpus 2 ,when start test ,the model have wrong following :

    pre_nms_top_n = candidate_inds.contiguous().view(N, -1).sum(1) # N RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead. I change model as (ccandidate_inds.contiguous().view(N, -1).sum(1) # N),but stall have wrong ,can you help me ?

    opened by Bin-ze 2
  • Cannot download models from model zoo?

    Cannot download models from model zoo?

    📚 Documentation Issue

    This issue category is for problems about existing documentation, not for asking how-to questions.

    • Provide a link to an existing documentation/comment/tutorial:

    • How should the above documentation/comment/tutorial improve:

    documentation 
    opened by xiaowenhe 1
  • Is it easy to add rotated proposal to centernet2?

    Is it easy to add rotated proposal to centernet2?

    Hi, thanks for the great work and I'm a big fan of centernet. I'm new to detectron and I found that they support rotated anchor box and region proposal. The question is, is it possible or easy to add rotated anchor box and region proposal to centernet since it's anchor-free network. Thanks!

    enhancement 
    opened by pharrellyhy 1
  • TypeError: 'NoneType' object is not iterable

    TypeError: 'NoneType' object is not iterable

    /home/appuser/anaconda3/envs/centernet2/lib/python3.8/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2228.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] Traceback (most recent call last): File "projects/CenterNet2/demo.py", line 100, in predictions, visualized_output = demo.run_on_image( File "/home/idriver/projects/CenterNet2/projects/CenterNet2/predictor.py", line 83, in run_on_image vis_output = visualizer.draw_instance_predictions( File "/home/appuser/anaconda3/envs/centernet2/lib/python3.8/site-packages/detectron2-0.6-py3.8-linux-x86_64.egg/detectron2/utils/video_visualizer.py", line 111, in draw_instance_predictions else [y[0] for y in filter(lambda x: x[1], zip(labels, visibilities))] TypeError: 'NoneType' object is not iterable 本地使用的环境是在docker hub中找的一个docker环境,docker环境内部安装了detectron2,执行如下命令是可以正常显示检测结果的: python projects/CenterNet2/demo.py --config-file projects/CenterNet2/configs/CenterNet2_R50_1x.yaml --input ./images/ --opts MODEL.WEIGHTS models/CenterNet2_R50_1x.pth。 我想导出onnx model,所以使用tools/deploy/export_model.py文件,但是docker环境中的detectron2没有这个文件需要的依赖文件,所以我在docker内新建了一个虚拟环境,然后使用python setup.py build & install对本项目进行编译安装,再执行前面那个demo.py的命令的时候就报错了,对比detectron2 中的video_visualizer.py可以看出detectron2的内容是不一样的,想问下为什么会报错? 这个是detectron2的bug吗?

    opened by GeneralJing 2
  • Cannot find models/CenterNet2_R50_1x.pth

    Cannot find models/CenterNet2_R50_1x.pth

    📚 Documentation Issue

    This issue category is for problems about existing documentation, not for asking how-to questions.

    • Provide a link to an existing documentation/comment/tutorial:

    • How should the above documentation/comment/tutorial improve:

    documentation 
    opened by yafitsnirco 1
Owner
Xingyi Zhou
CS Ph.D. student at UT Austin.
Xingyi Zhou
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