From 8ffa45af34d5fc6e3e0bc1df4b3508e3b8f995a1 Mon Sep 17 00:00:00 2001 From: Feng Ni Date: Mon, 14 Mar 2022 13:47:32 +0800 Subject: [PATCH] [MOT] Fix deepsort detectors config (#5344) * fix deepsort detectors cfgs, add ppyoloe * modify yolov3 40e * add ppyoloe mot17half modelzoo * add resnet embedding reid * remove fasterfpn picodet, fix nms for higher MOTA * add mot17 yml * fix _base_ cfgs * fix doc --- configs/mot/deepsort/README_cn.md | 20 +++- configs/mot/deepsort/_base_/mot17.yml | 33 ++++++ .../deepsort_faster_rcnn_fpn_pplcnet.yml | 65 ----------- .../deepsort_jde_yolov3_pcb_pyramid.yml | 4 +- .../deepsort/deepsort_jde_yolov3_pplcnet.yml | 3 +- .../mot/deepsort/deepsort_picodet_pplcnet.yml | 91 --------------- .../mot/deepsort/deepsort_ppyoloe_pplcnet.yml | 110 ++++++++++++++++++ .../mot/deepsort/deepsort_ppyoloe_resnet.yml | 109 +++++++++++++++++ .../deepsort/deepsort_ppyolov2_pplcnet.yml | 28 ++++- .../mot/deepsort/deepsort_yolov3_pplcnet.yml | 34 ++++-- configs/mot/deepsort/detector/README.md | 11 +- configs/mot/deepsort/detector/README_cn.md | 9 +- ...ter_rcnn_r50_fpn_2x_1333x800_mot17half.yml | 89 -------------- ...picodet_l_esnet_300e_896x896_mot17half.yml | 108 ----------------- .../ppyoloe_crn_l_36e_640x640_mot17half.yml | 80 +++++++++++++ ...olov2_r50vd_dcn_365e_640x640_mot17half.yml | 17 +-- ...olov3_darknet53_40e_608x608_mot17half.yml} | 45 ++++--- configs/mot/deepsort/reid/README.md | 2 +- .../reid/deepsort_pcb_pyramid_r101.yml | 3 +- configs/mot/deepsort/reid/deepsort_resnet.yml | 43 +++++++ ppdet/engine/tracker.py | 2 +- ppdet/modeling/reid/__init__.py | 2 + ppdet/modeling/reid/pyramidal_embedding.py | 6 +- ppdet/modeling/reid/resnet_embedding.py | 41 +++++++ 24 files changed, 535 insertions(+), 420 deletions(-) create mode 100644 configs/mot/deepsort/_base_/mot17.yml delete mode 100644 configs/mot/deepsort/deepsort_faster_rcnn_fpn_pplcnet.yml delete mode 100644 configs/mot/deepsort/deepsort_picodet_pplcnet.yml create mode 100644 configs/mot/deepsort/deepsort_ppyoloe_pplcnet.yml create mode 100644 configs/mot/deepsort/deepsort_ppyoloe_resnet.yml delete mode 100644 configs/mot/deepsort/detector/faster_rcnn_r50_fpn_2x_1333x800_mot17half.yml delete mode 100644 configs/mot/deepsort/detector/picodet_l_esnet_300e_896x896_mot17half.yml create mode 100644 configs/mot/deepsort/detector/ppyoloe_crn_l_36e_640x640_mot17half.yml rename configs/mot/deepsort/detector/{yolov3_darknet53_270e_608x608_pedestrian.yml => yolov3_darknet53_40e_608x608_mot17half.yml} (52%) create mode 100644 configs/mot/deepsort/reid/deepsort_resnet.yml create mode 100644 ppdet/modeling/reid/resnet_embedding.py diff --git a/configs/mot/deepsort/README_cn.md b/configs/mot/deepsort/README_cn.md index 8907513dd..8a957d7fa 100644 --- a/configs/mot/deepsort/README_cn.md +++ b/configs/mot/deepsort/README_cn.md @@ -39,11 +39,14 @@ | :-------- | :----- | :----: |:------: | :----: |:-----: |:----:|:----: | | MIX | JDE YOLOv3 | PCB Pyramid | - | 66.9 | 62.7 | - |[配置文件](./deepsort_jde_yolov3_pcb_pyramid.yml) | | MIX | JDE YOLOv3 | PPLCNet | - | 66.3 | 62.1 | - |[配置文件](./deepsort_jde_yolov3_pplcnet.yml) | -| pedestrian(未开放) | YOLOv3 | PPLCNet | 45.4 | 45.8 | 54.3 | - |[配置文件](./deepsort_yolov3_pplcnet.yml) | -| MOT-17 half train | PPYOLOv2 | PPLCNet | 46.8 | 48.7 | 54.5 | - |[配置文件](./deepsort_ppyolov2_pplcnet.yml) | +| MOT-17 half train | YOLOv3 | PPLCNet | 42.7 | 50.2 | 52.4 | - |[配置文件](./deepsort_yolov3_pplcnet.yml) | +| MOT-17 half train | PPYOLOv2 | PPLCNet | 46.8 | 51.8 | 55.8 | - |[配置文件](./deepsort_ppyolov2_pplcnet.yml) | +| MOT-17 half train | PPYOLOe | PPLCNet | 52.9 | 56.7 | 60.5 | - |[配置文件](./deepsort_ppyoloe_pplcnet.yml) | +| MOT-17 half train | PPYOLOe | ResNet-50 | 52.9 | 56.7 | 64.6 | - |[配置文件](./deepsort_ppyoloe_resnet.yml) | **注意:** -DeepSORT不需要训练MOT数据集，只用于评估，现在支持两种评估的方式。 +模型权重下载链接在配置文件中的```det_weights```和```reid_weights```，运行验证的命令即可自动下载。 +DeepSORT是分离检测器和ReID模型的，其中检测器单独训练MOT数据集，而组装成DeepSORT后只用于评估，现在支持两种评估的方式。 - **方式1**：加载检测结果文件和ReID模型，在使用DeepSORT模型评估之前，应该首先通过一个检测模型得到检测结果，然后像这样准备好结果文件: ``` det_results_dir @@ -75,6 +78,15 @@ wget https://dataset.bj.bcebos.com/mot/det_results_dir.zip ### 1. 评估 +#### 1.1 评估检测效果 +```bash +CUDA_VISIBLE_DEVICES=0 python tools/eval.py -c configs/mot/deepsort/detector/ppyoloe_crn_l_36e_640x640_mot17half.yml +``` + +**注意:** + - 评估检测使用的是```tools/eval.py```, 评估跟踪使用的是```tools/eval_mot.py```。 + +#### 1.2 评估跟踪效果 **方式1**：加载检测结果文件和ReID模型，得到跟踪结果 ```bash CUDA_VISIBLE_DEVICES=0 python tools/eval_mot.py -c configs/mot/deepsort/reid/deepsort_pcb_pyramid_r101.yml --det_results_dir {your detection results} @@ -89,6 +101,8 @@ CUDA_VISIBLE_DEVICES=0 python tools/eval_mot.py -c configs/mot/deepsort/deepsort CUDA_VISIBLE_DEVICES=0 python tools/eval_mot.py -c configs/mot/deepsort/deepsort_jde_yolov3_pplcnet.yml # 或者 CUDA_VISIBLE_DEVICES=0 python tools/eval_mot.py -c configs/mot/deepsort/deepsort_ppyolov2_pplcnet.yml --scaled=True +# 或者 +CUDA_VISIBLE_DEVICES=0 python tools/eval_mot.py -c configs/mot/deepsort/deepsort_ppyoloe_resnet.yml --scaled=True ``` **注意:** - JDE YOLOv3行人检测模型是和JDE和FairMOT使用同样的MOT数据集训练的，因此MOTA较高。而其他通用检测模型如PPYOLOv2只使用了MOT17 half数据集训练。 diff --git a/configs/mot/deepsort/_base_/mot17.yml b/configs/mot/deepsort/_base_/mot17.yml new file mode 100644 index 000000000..2efa55546 --- /dev/null +++ b/configs/mot/deepsort/_base_/mot17.yml @@ -0,0 +1,33 @@ +metric: COCO +num_classes: 1 + +# Detection Dataset for training +TrainDataset: + !COCODataSet + dataset_dir: dataset/mot/MOT17 + anno_path: annotations/train_half.json + image_dir: images/train + data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd'] + +EvalDataset: + !COCODataSet + dataset_dir: dataset/mot/MOT17 + anno_path: annotations/val_half.json + image_dir: images/train + +TestDataset: + !ImageFolder + anno_path: annotations/val_half.json + + +# MOTDataset for MOT evaluation and inference +EvalMOTDataset: + !MOTImageFolder + dataset_dir: dataset/mot + data_root: MOT17/images/half + keep_ori_im: True # set as True in DeepSORT and ByteTrack + +TestMOTDataset: + !MOTImageFolder + dataset_dir: dataset/mot + keep_ori_im: True # set True if save visualization images or video diff --git a/configs/mot/deepsort/deepsort_faster_rcnn_fpn_pplcnet.yml b/configs/mot/deepsort/deepsort_faster_rcnn_fpn_pplcnet.yml deleted file mode 100644 index ce8ac6de1..000000000 --- a/configs/mot/deepsort/deepsort_faster_rcnn_fpn_pplcnet.yml +++ /dev/null @@ -1,65 +0,0 @@ -_BASE_: [ - 'detector/faster_rcnn_r50_fpn_2x_1333x800_mot17half.yml', - '../../datasets/mot.yml', - '../../runtime.yml', - '_base_/deepsort_reader_1088x608.yml', -] -metric: MOT -num_classes: 1 - -EvalMOTDataset: - !MOTImageFolder - dataset_dir: dataset/mot - data_root: MOT17/images/half - keep_ori_im: True # set as True in DeepSORT - -det_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/faster_rcnn_r50_fpn_2x_1333x800_mot17half.pdparams -reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pplcnet.pdparams - - -# DeepSORT configuration -architecture: DeepSORT -pretrain_weights: None - -DeepSORT: - detector: FasterRCNN - reid: PPLCNetEmbedding - tracker: DeepSORTTracker - - -# reid and tracker configuration -# see 'configs/mot/deepsort/reid/deepsort_pplcnet.yml' -PPLCNetEmbedding: - input_ch: 1280 - output_ch: 512 - -DeepSORTTracker: - input_size: [64, 192] - min_box_area: 0 - vertical_ratio: -1 - budget: 100 - max_age: 70 - n_init: 3 - metric_type: cosine - matching_threshold: 0.2 - max_iou_distance: 0.9 - motion: KalmanFilter - - -# detector configuration -# see 'configs/mot/deepsort/detector/faster_rcnn_r50_fpn_2x_1333x800_mot17half.yml' -FasterRCNN: - backbone: ResNet - neck: FPN - rpn_head: RPNHead - bbox_head: BBoxHead - bbox_post_process: BBoxPostProcess - -# Tracking requires higher quality boxes, so nms.score_threshold will be higher -BBoxPostProcess: - decode: RCNNBox - nms: - name: MultiClassNMS - keep_top_k: 100 - score_threshold: 0.2 # 0.05 in original detector - nms_threshold: 0.5 diff --git a/configs/mot/deepsort/deepsort_jde_yolov3_pcb_pyramid.yml b/configs/mot/deepsort/deepsort_jde_yolov3_pcb_pyramid.yml index 4da1fadcb..066e0ec08 100644 --- a/configs/mot/deepsort/deepsort_jde_yolov3_pcb_pyramid.yml +++ b/configs/mot/deepsort/deepsort_jde_yolov3_pcb_pyramid.yml @@ -1,7 +1,6 @@ _BASE_: [ 'detector/jde_yolov3_darknet53_30e_1088x608_mix.yml', - '../../datasets/mot.yml', - '../../runtime.yml', + '_base_/mot17.yml', '_base_/deepsort_reader_1088x608.yml', ] metric: MOT @@ -30,6 +29,7 @@ DeepSORT: # reid and tracker configuration # see 'configs/mot/deepsort/reid/deepsort_pcb_pyramid_r101.yml' PCBPyramid: + model_name: "ResNet101" num_conv_out_channels: 128 num_classes: 751 diff --git a/configs/mot/deepsort/deepsort_jde_yolov3_pplcnet.yml b/configs/mot/deepsort/deepsort_jde_yolov3_pplcnet.yml index e6d74411d..a412c9e5a 100644 --- a/configs/mot/deepsort/deepsort_jde_yolov3_pplcnet.yml +++ b/configs/mot/deepsort/deepsort_jde_yolov3_pplcnet.yml @@ -1,7 +1,6 @@ _BASE_: [ 'detector/jde_yolov3_darknet53_30e_1088x608_mix.yml', - '../../datasets/mot.yml', - '../../runtime.yml', + '_base_/mot17.yml', '_base_/deepsort_reader_1088x608.yml', ] metric: MOT diff --git a/configs/mot/deepsort/deepsort_picodet_pplcnet.yml b/configs/mot/deepsort/deepsort_picodet_pplcnet.yml deleted file mode 100644 index 35c619995..000000000 --- a/configs/mot/deepsort/deepsort_picodet_pplcnet.yml +++ /dev/null @@ -1,91 +0,0 @@ -_BASE_: [ - 'detector/picodet_l_esnet_300e_896x896_mot17half.yml', - '../../datasets/mot.yml', - '../../runtime.yml', - '_base_/deepsort_reader_1088x608.yml', -] -metric: MOT -num_classes: 1 - -EvalMOTDataset: - !MOTImageFolder - dataset_dir: dataset/mot - data_root: MOT17/images/half - keep_ori_im: True # set as True in DeepSORT - -det_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/picodet_l_esnet_300e_896x896_mot17half.pdparams -reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pplcnet.pdparams - - -# DeepSORT configuration -architecture: DeepSORT -pretrain_weights: None - -DeepSORT: - detector: PicoDet - reid: PPLCNetEmbedding - tracker: DeepSORTTracker - - -# reid and tracker configuration -# see 'configs/mot/deepsort/reid/deepsort_pplcnet.yml' -PPLCNetEmbedding: - input_ch: 1280 - output_ch: 512 - -DeepSORTTracker: - input_size: [64, 192] - min_box_area: 0 - vertical_ratio: -1 - budget: 100 - max_age: 70 - n_init: 3 - metric_type: cosine - matching_threshold: 0.2 - max_iou_distance: 0.9 - motion: KalmanFilter - - -# detector configuration -# see 'configs/mot/deepsort/detector/picodet_l_esnet_300e_640x640_mot17half.yml' -PicoDet: - backbone: ESNet - neck: CSPPAN - head: PicoHead - -PicoHead: - conv_feat: - name: PicoFeat - feat_in: 128 - feat_out: 128 - num_convs: 4 - num_fpn_stride: 4 - norm_type: bn - share_cls_reg: False - fpn_stride: [8, 16, 32, 64] - feat_in_chan: 128 - prior_prob: 0.01 - reg_max: 7 - cell_offset: 0.5 - loss_class: - name: VarifocalLoss - use_sigmoid: True - iou_weighted: True - loss_weight: 1.0 - loss_dfl: - name: DistributionFocalLoss - loss_weight: 0.25 - loss_bbox: - name: GIoULoss - loss_weight: 2.0 - assigner: - name: SimOTAAssigner - candidate_topk: 10 - iou_weight: 6 - nms: - name: MultiClassNMS - nms_top_k: 1000 - keep_top_k: 100 - score_threshold: 0.25 # 0.025 in original detector - nms_threshold: 0.6 - diff --git a/configs/mot/deepsort/deepsort_ppyoloe_pplcnet.yml b/configs/mot/deepsort/deepsort_ppyoloe_pplcnet.yml new file mode 100644 index 000000000..972a1d169 --- /dev/null +++ b/configs/mot/deepsort/deepsort_ppyoloe_pplcnet.yml @@ -0,0 +1,110 @@ +_BASE_: [ + 'detector/ppyoloe_crn_l_36e_640x640_mot17half.yml', + '_base_/mot17.yml', + '_base_/deepsort_reader_1088x608.yml', +] +metric: MOT +num_classes: 1 + +EvalMOTDataset: + !MOTImageFolder + dataset_dir: dataset/mot + data_root: MOT17/images/half + keep_ori_im: True # set as True in DeepSORT + +det_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/ppyoloe_crn_l_36e_640x640_mot17half.pdparams +reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pplcnet.pdparams + +# reader +EvalMOTReader: + sample_transforms: + - Decode: {} + - Resize: {target_size: [640, 640], keep_ratio: False, interp: 2} + - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True} + - Permute: {} + batch_size: 1 + +TestMOTReader: + inputs_def: + image_shape: [3, 640, 640] + sample_transforms: + - Decode: {} + - Resize: {target_size: [640, 640], keep_ratio: False, interp: 2} + - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True} + - Permute: {} + batch_size: 1 + + +# DeepSORT configuration +architecture: DeepSORT +pretrain_weights: None + +DeepSORT: + detector: YOLOv3 # PPYOLOe version + reid: PPLCNetEmbedding + tracker: DeepSORTTracker + + +# reid and tracker configuration +# see 'configs/mot/deepsort/reid/deepsort_pplcnet.yml' +PPLCNetEmbedding: + input_ch: 1280 + output_ch: 512 + +DeepSORTTracker: + input_size: [64, 192] + min_box_area: 0 + vertical_ratio: -1 + budget: 100 + max_age: 70 + n_init: 3 + metric_type: cosine + matching_threshold: 0.2 + max_iou_distance: 0.9 + motion: KalmanFilter + + +# detector configuration: PPYOLOe version +# see 'configs/mot/deepsort/detector/ppyoloe_crn_l_300e_640x640_mot17half.yml' +YOLOv3: + backbone: CSPResNet + neck: CustomCSPPAN + yolo_head: PPYOLOEHead + post_process: ~ + +CSPResNet: + layers: [3, 6, 6, 3] + channels: [64, 128, 256, 512, 1024] + return_idx: [1, 2, 3] + use_large_stem: True + +CustomCSPPAN: + out_channels: [768, 384, 192] + stage_num: 1 + block_num: 3 + act: 'swish' + spp: true + +# Tracking requires higher quality boxes, so NMS score_threshold will be higher +PPYOLOEHead: + fpn_strides: [32, 16, 8] + grid_cell_scale: 5.0 + grid_cell_offset: 0.5 + static_assigner_epoch: -1 # 100 + use_varifocal_loss: True + eval_input_size: [640, 640] + loss_weight: {class: 1.0, iou: 2.5, dfl: 0.5} + static_assigner: + name: ATSSAssigner + topk: 9 + assigner: + name: TaskAlignedAssigner + topk: 13 + alpha: 1.0 + beta: 6.0 + nms: + name: MultiClassNMS + nms_top_k: 1000 + keep_top_k: 100 + score_threshold: 0.4 # 0.01 in original detector + nms_threshold: 0.6 diff --git a/configs/mot/deepsort/deepsort_ppyoloe_resnet.yml b/configs/mot/deepsort/deepsort_ppyoloe_resnet.yml new file mode 100644 index 000000000..cde2cf23c --- /dev/null +++ b/configs/mot/deepsort/deepsort_ppyoloe_resnet.yml @@ -0,0 +1,109 @@ +_BASE_: [ + 'detector/ppyoloe_crn_l_36e_640x640_mot17half.yml', + '_base_/mot17.yml', + '_base_/deepsort_reader_1088x608.yml', +] +metric: MOT +num_classes: 1 + +EvalMOTDataset: + !MOTImageFolder + dataset_dir: dataset/mot + data_root: MOT17/images/half + keep_ori_im: True # set as True in DeepSORT + +det_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/ppyoloe_crn_l_36e_640x640_mot17half.pdparams +reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_resnet.pdparams + +# reader +EvalMOTReader: + sample_transforms: + - Decode: {} + - Resize: {target_size: [640, 640], keep_ratio: False, interp: 2} + - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True} + - Permute: {} + batch_size: 1 + +TestMOTReader: + inputs_def: + image_shape: [3, 640, 640] + sample_transforms: + - Decode: {} + - Resize: {target_size: [640, 640], keep_ratio: False, interp: 2} + - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True} + - Permute: {} + batch_size: 1 + + +# DeepSORT configuration +architecture: DeepSORT +pretrain_weights: None + +DeepSORT: + detector: YOLOv3 # PPYOLOe version + reid: ResNetEmbedding + tracker: DeepSORTTracker + + +# reid and tracker configuration +# see 'configs/mot/deepsort/reid/deepsort_resnet.yml' +ResNetEmbedding: + model_name: "ResNet50" + +DeepSORTTracker: + input_size: [64, 192] + min_box_area: 0 + vertical_ratio: -1 + budget: 100 + max_age: 70 + n_init: 3 + metric_type: cosine + matching_threshold: 0.2 + max_iou_distance: 0.9 + motion: KalmanFilter + + +# detector configuration: PPYOLOe version +# see 'configs/mot/deepsort/detector/ppyoloe_crn_l_300e_640x640_mot17half.yml' +YOLOv3: + backbone: CSPResNet + neck: CustomCSPPAN + yolo_head: PPYOLOEHead + post_process: ~ + +CSPResNet: + layers: [3, 6, 6, 3] + channels: [64, 128, 256, 512, 1024] + return_idx: [1, 2, 3] + use_large_stem: True + +CustomCSPPAN: + out_channels: [768, 384, 192] + stage_num: 1 + block_num: 3 + act: 'swish' + spp: true + +# Tracking requires higher quality boxes, so NMS score_threshold will be higher +PPYOLOEHead: + fpn_strides: [32, 16, 8] + grid_cell_scale: 5.0 + grid_cell_offset: 0.5 + static_assigner_epoch: -1 # 100 + use_varifocal_loss: True + eval_input_size: [640, 640] + loss_weight: {class: 1.0, iou: 2.5, dfl: 0.5} + static_assigner: + name: ATSSAssigner + topk: 9 + assigner: + name: TaskAlignedAssigner + topk: 13 + alpha: 1.0 + beta: 6.0 + nms: + name: MultiClassNMS + nms_top_k: 1000 + keep_top_k: 100 + score_threshold: 0.4 # 0.01 in original detector + nms_threshold: 0.6 diff --git a/configs/mot/deepsort/deepsort_ppyolov2_pplcnet.yml b/configs/mot/deepsort/deepsort_ppyolov2_pplcnet.yml index 342249e06..8cd393e45 100644 --- a/configs/mot/deepsort/deepsort_ppyolov2_pplcnet.yml +++ b/configs/mot/deepsort/deepsort_ppyolov2_pplcnet.yml @@ -1,7 +1,6 @@ _BASE_: [ 'detector/ppyolov2_r50vd_dcn_365e_640x640_mot17half.yml', - '../../datasets/mot.yml', - '../../runtime.yml', + '_base_/mot17.yml', '_base_/deepsort_reader_1088x608.yml', ] metric: MOT @@ -16,6 +15,25 @@ EvalMOTDataset: det_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/ppyolov2_r50vd_dcn_365e_640x640_mot17half.pdparams reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pplcnet.pdparams +# reader +EvalMOTReader: + sample_transforms: + - Decode: {} + - Resize: {target_size: [640, 640], keep_ratio: False, interp: 2} + - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True} + - Permute: {} + batch_size: 1 + +TestMOTReader: + inputs_def: + image_shape: [3, 640, 640] + sample_transforms: + - Decode: {} + - Resize: {target_size: [640, 640], keep_ratio: False, interp: 2} + - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True} + - Permute: {} + batch_size: 1 + # DeepSORT configuration architecture: DeepSORT @@ -63,7 +81,7 @@ ResNet: freeze_norm: false norm_decay: 0. -# Tracking requires higher quality boxes, so decode.conf_thresh will be higher +# Tracking requires higher quality boxes, so NMS score_threshold will be higher BBoxPostProcess: decode: name: YOLOBox @@ -74,7 +92,7 @@ BBoxPostProcess: nms: name: MatrixNMS keep_top_k: 100 - score_threshold: 0.25 # 0.01 in original detector - post_threshold: 0.25 # 0.01 in original detector + score_threshold: 0.4 # 0.01 in original detector + post_threshold: 0.4 # 0.01 in original detector nms_top_k: -1 background_label: -1 diff --git a/configs/mot/deepsort/deepsort_yolov3_pplcnet.yml b/configs/mot/deepsort/deepsort_yolov3_pplcnet.yml index 0064a36c5..adb0aa9a0 100644 --- a/configs/mot/deepsort/deepsort_yolov3_pplcnet.yml +++ b/configs/mot/deepsort/deepsort_yolov3_pplcnet.yml @@ -1,7 +1,6 @@ _BASE_: [ - 'detector/yolov3_darknet53_270e_608x608_pedestrian.yml', - '../../datasets/mot.yml', - '../../runtime.yml', + 'detector/yolov3_darknet53_40e_608x608_mot17half.yml', + '_base_/mot17.yml', '_base_/deepsort_reader_1088x608.yml', ] metric: MOT @@ -13,9 +12,28 @@ EvalMOTDataset: data_root: MOT17/images/half keep_ori_im: True # set as True in DeepSORT -det_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/yolov3_darknet53_270e_608x608_pedestrian.pdparams +det_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/yolov3_darknet53_40e_608x608_mot17half.pdparams reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pplcnet.pdparams +# reader +EvalMOTReader: + sample_transforms: + - Decode: {} + - Resize: {target_size: [608, 608], keep_ratio: False, interp: 2} + - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True} + - Permute: {} + batch_size: 1 + +TestMOTReader: + inputs_def: + image_shape: [3, 608, 608] + sample_transforms: + - Decode: {} + - Resize: {target_size: [608, 608], keep_ratio: False, interp: 2} + - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True} + - Permute: {} + batch_size: 1 + # DeepSORT configuration architecture: DeepSORT @@ -47,23 +65,23 @@ DeepSORTTracker: # detector configuration: General YOLOv3 version -# see 'configs/mot/deepsort/detector/yolov3_darknet53_270e_608x608_pedestrian.yml' +# see 'configs/mot/deepsort/detector/yolov3_darknet53_40e_608x608_mot17half.yml' YOLOv3: backbone: DarkNet neck: YOLOv3FPN yolo_head: YOLOv3Head post_process: BBoxPostProcess -# Tracking requires higher quality boxes, so decode.conf_thresh will be higher +# Tracking requires higher quality boxes, so NMS score_threshold will be higher BBoxPostProcess: decode: name: YOLOBox - conf_thresh: 0.1 # 0.005 in original detector + conf_thresh: 0.005 downsample_ratio: 32 clip_bbox: true nms: name: MultiClassNMS keep_top_k: 100 - score_threshold: 0.01 + score_threshold: 0.3 # 0.01 in original detector nms_threshold: 0.45 nms_top_k: 1000 diff --git a/configs/mot/deepsort/detector/README.md b/configs/mot/deepsort/detector/README.md index e13bca406..8dd73801f 100644 --- a/configs/mot/deepsort/detector/README.md +++ b/configs/mot/deepsort/detector/README.md @@ -9,13 +9,12 @@ English | [简体中文](README_cn.md) ### Results on MOT17-half dataset | Backbone | Model | input size | lr schedule | FPS | Box AP | download | config | | :-------------- | :------------- | :--------: | :---------: | :-----------: | :-----: | :----------: | :-----: | +| DarkNet-53 | YOLOv3 | 608X608 | 40e | ---- | 42.7 | [download](https://paddledet.bj.bcebos.com/models/mot/deepsort/yolov3_darknet53_40e_608x608_mot17half.pdparams) | [config](./yolov3_darknet53_40e_608x608_mot17half.yml) | | ResNet50-vd | PPYOLOv2 | 640x640 | 365e | ---- | 46.8 | [download](https://paddledet.bj.bcebos.com/models/mot/deepsort/ppyolov2_r50vd_dcn_365e_640x640_mot17half.pdparams) | [config](./ppyolov2_r50vd_dcn_365e_640x640_mot17half.yml) | -| ResNet50-FPN | Faster R-CNN | 1333x800 | 1x | ---- | 44.2 | [download](https://paddledet.bj.bcebos.com/models/mot/deepsort/faster_rcnn_r50_fpn_2x_1333x800_mot17half.pdparams) | [config](./faster_rcnn_r50_fpn_2x_1333x800_mot17half.yml) | -| DarkNet-53 | YOLOv3 | 608X608 | 270e | ---- | 45.4 | [download](https://paddledet.bj.bcebos.com/models/mot/deepsort/yolov3_darknet53_270e_608x608_pedestrian.pdparams) | [config](./yolov3_darknet53_270e_608x608_pedestrian.yml) | -| ESNet | PicoDet | 896x896 | 300e | ---- | 40.9 | [download](https://paddledet.bj.bcebos.com/models/mot/deepsort/picodet_l_esnet_300e_896x896_mot17half.pdparams) | [config](./picodet_l_esnet_300e_896x896_mot17half.yml) | +| CSPResNet | PPYOLOe | 640x640 | 36e | ---- | 52.9 | [download](https://paddledet.bj.bcebos.com/models/mot/deepsort/ppyoloe_crn_l_36e_640x640_mot17half.pdparams) | [config](./ppyoloe_crn_l_36e_640x640_mot17half.yml) | **Notes:** - - The above model except for YOLOv3 is trained with **MOT17-half train** set. + - The above models are trained with **MOT17-half train** set, it can be downloaded from this [link](https://dataset.bj.bcebos.com/mot/MOT17.zip). - **MOT17-half train** set is a dataset composed of pictures and labels of the first half frame of each video in MOT17 Train dataset (7 sequences in total). **MOT17-half val set** is used for evaluation, which is composed of the second half frame of each video. They can be downloaded from this [link](https://paddledet.bj.bcebos.com/data/mot/mot17half/annotations.zip). Download and unzip it in the `dataset/mot/MOT17/images/`folder. - YOLOv3 is trained with the same pedestrian dataset as `configs/pedestrian/pedestrian_yolov3_darknet.yml`, which is not open yet. - For pedestrian tracking, please use pedestrian detector combined with pedestrian ReID model. For vehicle tracking, please use vehicle detector combined with vehicle ReID model. @@ -25,11 +24,11 @@ English | [简体中文](README_cn.md) Start the training and evaluation with the following command ```bash -job_name=ppyolov2_r50vd_dcn_365e_640x640_mot17half +job_name=ppyoloe_crn_l_36e_640x640_mot17half config=configs/mot/deepsort/detector/${job_name}.yml log_dir=log_dir/${job_name} # 1. training -python -m paddle.distributed.launch --log_dir=${log_dir} --gpus 0,1,2,3,4,5,6,7 tools/train.py -c ${config} +python -m paddle.distributed.launch --log_dir=${log_dir} --gpus 0,1,2,3,4,5,6,7 tools/train.py -c ${config} --eval --amp --fleet # 2. evaluation CUDA_VISIBLE_DEVICES=0 python tools/eval.py -c ${config} -o weights=https://paddledet.bj.bcebos.com/models/mot/deepsort/${job_name}.pdparams ``` diff --git a/configs/mot/deepsort/detector/README_cn.md b/configs/mot/deepsort/detector/README_cn.md index a40d1dd6a..1a984b5c3 100644 --- a/configs/mot/deepsort/detector/README_cn.md +++ b/configs/mot/deepsort/detector/README_cn.md @@ -10,13 +10,12 @@ ### 在MOT17-half val数据集上的检测结果 | 骨架网络 | 网络类型 | 输入尺度 | 学习率策略 |推理时间(fps) | Box AP | 下载 | 配置文件 | | :-------------- | :------------- | :--------: | :---------: | :-----------: | :-----: | :------: | :-----: | +| DarkNet-53 | YOLOv3 | 608X608 | 40e | ---- | 42.7 | [下载链接](https://paddledet.bj.bcebos.com/models/mot/deepsort/yolov3_darknet53_40e_608x608_mot17half.pdparams) | [配置文件](./yolov3_darknet53_40e_608x608_mot17half.yml) | | ResNet50-vd | PPYOLOv2 | 640x640 | 365e | ---- | 46.8 | [下载链接](https://paddledet.bj.bcebos.com/models/mot/deepsort/ppyolov2_r50vd_dcn_365e_640x640_mot17half.pdparams) | [配置文件](./ppyolov2_r50vd_dcn_365e_640x640_mot17half.yml) | -| ResNet50-FPN | Faster R-CNN | 1333x800 | 1x | ---- | 44.2 | [下载链接](https://paddledet.bj.bcebos.com/models/mot/deepsort/faster_rcnn_r50_fpn_2x_1333x800_mot17half.pdparams) | [配置文件](./faster_rcnn_r50_fpn_2x_1333x800_mot17half.yml) | -| DarkNet-53 | YOLOv3 | 608X608 | 270e | ---- | 45.4 | [下载链接](https://paddledet.bj.bcebos.com/models/mot/deepsort/yolov3_darknet53_270e_608x608_pedestrian.pdparams) | [配置文件](./yolov3_darknet53_270e_608x608_pedestrian.yml) | -| ESNet | PicoDet | 896x896 | 300e | ---- | 40.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mot/deepsort/picodet_l_esnet_300e_896x896_mot17half.pdparams) | [配置文件](./picodet_l_esnet_300e_896x896_mot17half.yml) | +| CSPResNet | PPYOLOe | 640x640 | 36e | ---- | 52.9 | [下载链接](https://paddledet.bj.bcebos.com/models/mot/deepsort/ppyoloe_crn_l_36e_640x640_mot17half.pdparams) | [配置文件](./ppyoloe_crn_l_36e_640x640_mot17half.yml) | **注意:** - - 以上模型除了YOLOv3以外均采用**MOT17-half train**数据集训练。 + - 以上模型均可采用**MOT17-half train**数据集训练，数据集可以从[此链接](https://dataset.bj.bcebos.com/mot/MOT17.zip)下载。 - **MOT17-half train**是MOT17的train序列(共7个)每个视频的前一半帧的图片和标注组成的数据集，而为了验证精度可以都用**MOT17-half val**数据集去评估，它是每个视频的后一半帧组成的，数据集可以从[此链接](https://paddledet.bj.bcebos.com/data/mot/mot17half/annotations.zip)下载，并解压放在`dataset/mot/MOT17/images/`文件夹下。 - YOLOv3和`configs/pedestrian/pedestrian_yolov3_darknet.yml`是相同的pedestrian数据集训练的，此数据集暂未开放。 - 行人跟踪请使用行人检测器结合行人ReID模型。车辆跟踪请使用车辆检测器结合车辆ReID模型。 @@ -31,7 +30,7 @@ job_name=ppyolov2_r50vd_dcn_365e_640x640_mot17half config=configs/mot/deepsort/detector/${job_name}.yml log_dir=log_dir/${job_name} # 1. training -python -m paddle.distributed.launch --log_dir=${log_dir} --gpus 0,1,2,3,4,5,6,7 tools/train.py -c ${config} +python -m paddle.distributed.launch --log_dir=${log_dir} --gpus 0,1,2,3,4,5,6,7 tools/train.py -c ${config} --eval --amp --fleet # 2. evaluation CUDA_VISIBLE_DEVICES=0 python tools/eval.py -c ${config} -o weights=https://paddledet.bj.bcebos.com/models/mot/deepsort/${job_name}.pdparams ``` diff --git a/configs/mot/deepsort/detector/faster_rcnn_r50_fpn_2x_1333x800_mot17half.yml b/configs/mot/deepsort/detector/faster_rcnn_r50_fpn_2x_1333x800_mot17half.yml deleted file mode 100644 index 032758e6c..000000000 --- a/configs/mot/deepsort/detector/faster_rcnn_r50_fpn_2x_1333x800_mot17half.yml +++ /dev/null @@ -1,89 +0,0 @@ -_BASE_: [ - '../../../faster_rcnn/faster_rcnn_r50_fpn_2x_coco.yml', -] -weights: output/faster_rcnn_r50_fpn_2x_1333x800_mot17half/model_final - -num_classes: 1 -TrainDataset: - !COCODataSet - dataset_dir: dataset/mot/MOT17/images - anno_path: annotations/train_half.json - image_dir: train - data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd'] - -EvalDataset: - !COCODataSet - dataset_dir: dataset/mot/MOT17/images - anno_path: annotations/val_half.json - image_dir: train - - -# detector configuration -architecture: FasterRCNN -pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams - -FasterRCNN: - backbone: ResNet - neck: FPN - rpn_head: RPNHead - bbox_head: BBoxHead - bbox_post_process: BBoxPostProcess - -ResNet: - depth: 50 - norm_type: bn - freeze_at: 0 - return_idx: [0,1,2,3] - num_stages: 4 - -FPN: - out_channel: 256 - -RPNHead: - anchor_generator: - aspect_ratios: [0.5, 1.0, 2.0] - anchor_sizes: [[32], [64], [128], [256], [512]] - strides: [4, 8, 16, 32, 64] - rpn_target_assign: - batch_size_per_im: 256 - fg_fraction: 0.5 - negative_overlap: 0.3 - positive_overlap: 0.7 - use_random: True - train_proposal: - min_size: 0.0 - nms_thresh: 0.7 - pre_nms_top_n: 2000 - post_nms_top_n: 1000 - topk_after_collect: True - test_proposal: - min_size: 0.0 - nms_thresh: 0.7 - pre_nms_top_n: 1000 - post_nms_top_n: 1000 - -BBoxHead: - head: TwoFCHead - roi_extractor: - resolution: 7 - sampling_ratio: 0 - aligned: True - bbox_assigner: BBoxAssigner - -BBoxAssigner: - batch_size_per_im: 512 - bg_thresh: 0.5 - fg_thresh: 0.5 - fg_fraction: 0.25 - use_random: True - -TwoFCHead: - out_channel: 1024 - -BBoxPostProcess: - decode: RCNNBox - nms: - name: MultiClassNMS - keep_top_k: 100 - score_threshold: 0.05 - nms_threshold: 0.5 diff --git a/configs/mot/deepsort/detector/picodet_l_esnet_300e_896x896_mot17half.yml b/configs/mot/deepsort/detector/picodet_l_esnet_300e_896x896_mot17half.yml deleted file mode 100644 index 250f4b2d4..000000000 --- a/configs/mot/deepsort/detector/picodet_l_esnet_300e_896x896_mot17half.yml +++ /dev/null @@ -1,108 +0,0 @@ -_BASE_: [ - '../../../picodet/picodet_l_640_coco.yml', -] -weights: output/picodet_l_esnet_300e_896x896_mot17half/model_final - -num_classes: 1 -TrainDataset: - !COCODataSet - dataset_dir: dataset/mot/MOT17/images - anno_path: annotations/train_half.json - image_dir: train - data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd'] - -EvalDataset: - !COCODataSet - dataset_dir: dataset/mot/MOT17/images - anno_path: annotations/val_half.json - image_dir: train - -worker_num: 6 -TrainReader: - sample_transforms: - - Decode: {} - - RandomCrop: {} - - RandomFlip: {prob: 0.5} - - RandomDistort: {} - batch_transforms: - - BatchRandomResize: {target_size: [832, 864, 896, 928, 960], random_size: True, random_interp: True, keep_ratio: False} - - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]} - - Permute: {} - batch_size: 32 - shuffle: true - drop_last: true - collate_batch: false - -EvalReader: - sample_transforms: - - Decode: {} - - Resize: {interp: 2, target_size: [896, 896], keep_ratio: False} - - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]} - - Permute: {} - batch_transforms: - - PadBatch: {pad_to_stride: 32} - batch_size: 8 - shuffle: false - - -# detector configuration -architecture: PicoDet -pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ESNet_x1_25_pretrained.pdparams -find_unused_parameters: True -use_ema: true -cycle_epoch: 40 -snapshot_epoch: 10 -epoch: 250 - -PicoDet: - backbone: ESNet - neck: CSPPAN - head: PicoHead - -ESNet: - scale: 1.25 - feature_maps: [4, 11, 14] - act: hard_swish - channel_ratio: [0.875, 0.5, 1.0, 0.625, 0.5, 0.75, 0.625, 0.625, 0.5, 0.625, 1.0, 0.625, 0.75] - -CSPPAN: - out_channels: 128 - use_depthwise: True - num_csp_blocks: 1 - num_features: 4 - -PicoHead: - conv_feat: - name: PicoFeat - feat_in: 128 - feat_out: 128 - num_convs: 4 - num_fpn_stride: 4 - norm_type: bn - share_cls_reg: False - fpn_stride: [8, 16, 32, 64] - feat_in_chan: 128 - prior_prob: 0.01 - reg_max: 7 - cell_offset: 0.5 - loss_class: - name: VarifocalLoss - use_sigmoid: True - iou_weighted: True - loss_weight: 1.0 - loss_dfl: - name: DistributionFocalLoss - loss_weight: 0.25 - loss_bbox: - name: GIoULoss - loss_weight: 2.0 - assigner: - name: SimOTAAssigner - candidate_topk: 10 - iou_weight: 6 - nms: - name: MultiClassNMS - nms_top_k: 1000 - keep_top_k: 100 - score_threshold: 0.025 - nms_threshold: 0.6 diff --git a/configs/mot/deepsort/detector/ppyoloe_crn_l_36e_640x640_mot17half.yml b/configs/mot/deepsort/detector/ppyoloe_crn_l_36e_640x640_mot17half.yml new file mode 100644 index 000000000..4852d6b7e --- /dev/null +++ b/configs/mot/deepsort/detector/ppyoloe_crn_l_36e_640x640_mot17half.yml @@ -0,0 +1,80 @@ +_BASE_: [ + '../../../ppyoloe/ppyoloe_crn_l_300e_coco.yml', + '../_base_/mot17.yml', +] +weights: output/ppyoloe_crn_l_36e_640x640_mot17half/model_final +log_iter: 20 +snapshot_epoch: 2 + +# schedule configuration for fine-tuning +epoch: 36 +LearningRate: + base_lr: 0.001 + schedulers: + - !CosineDecay + max_epochs: 43 + - !LinearWarmup + start_factor: 0.001 + steps: 100 + +OptimizerBuilder: + optimizer: + momentum: 0.9 + type: Momentum + regularizer: + factor: 0.0005 + type: L2 + +TrainReader: + batch_size: 8 + +# detector configuration +architecture: YOLOv3 +norm_type: sync_bn +use_ema: true +ema_decay: 0.9998 +pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/ppyoloe_crn_l_300e_coco.pdparams +depth_mult: 1.0 +width_mult: 1.0 + +YOLOv3: + backbone: CSPResNet + neck: CustomCSPPAN + yolo_head: PPYOLOEHead + post_process: ~ + +CSPResNet: + layers: [3, 6, 6, 3] + channels: [64, 128, 256, 512, 1024] + return_idx: [1, 2, 3] + use_large_stem: True + +CustomCSPPAN: + out_channels: [768, 384, 192] + stage_num: 1 + block_num: 3 + act: 'swish' + spp: true + +PPYOLOEHead: + fpn_strides: [32, 16, 8] + grid_cell_scale: 5.0 + grid_cell_offset: 0.5 + static_assigner_epoch: -1 # 100 + use_varifocal_loss: True + eval_input_size: [640, 640] + loss_weight: {class: 1.0, iou: 2.5, dfl: 0.5} + static_assigner: + name: ATSSAssigner + topk: 9 + assigner: + name: TaskAlignedAssigner + topk: 13 + alpha: 1.0 + beta: 6.0 + nms: + name: MultiClassNMS + nms_top_k: 1000 + keep_top_k: 100 + score_threshold: 0.01 + nms_threshold: 0.6 diff --git a/configs/mot/deepsort/detector/ppyolov2_r50vd_dcn_365e_640x640_mot17half.yml b/configs/mot/deepsort/detector/ppyolov2_r50vd_dcn_365e_640x640_mot17half.yml index c3b3344bc..cc55e46e7 100644 --- a/configs/mot/deepsort/detector/ppyolov2_r50vd_dcn_365e_640x640_mot17half.yml +++ b/configs/mot/deepsort/detector/ppyolov2_r50vd_dcn_365e_640x640_mot17half.yml @@ -1,21 +1,10 @@ _BASE_: [ '../../../ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml', + '../_base_/mot17.yml', ] weights: output/ppyolov2_r50vd_dcn_365e_640x640_mot17half/model_final - -num_classes: 1 -TrainDataset: - !COCODataSet - dataset_dir: dataset/mot/MOT17/images - anno_path: annotations/train_half.json - image_dir: train - data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd'] - -EvalDataset: - !COCODataSet - dataset_dir: dataset/mot/MOT17/images - anno_path: annotations/val_half.json - image_dir: train +log_iter: 20 +snapshot_epoch: 2 # detector configuration diff --git a/configs/mot/deepsort/detector/yolov3_darknet53_270e_608x608_pedestrian.yml b/configs/mot/deepsort/detector/yolov3_darknet53_40e_608x608_mot17half.yml similarity index 52% rename from configs/mot/deepsort/detector/yolov3_darknet53_270e_608x608_pedestrian.yml rename to configs/mot/deepsort/detector/yolov3_darknet53_40e_608x608_mot17half.yml index 900491d31..9ab55f977 100644 --- a/configs/mot/deepsort/detector/yolov3_darknet53_270e_608x608_pedestrian.yml +++ b/configs/mot/deepsort/detector/yolov3_darknet53_40e_608x608_mot17half.yml @@ -1,29 +1,40 @@ -# This config is the same as '../../../pedestrian/pedestrian_yolov3_darknet.yml'. _BASE_: [ '../../../yolov3/yolov3_darknet53_270e_coco.yml', + '../_base_/mot17.yml', ] -weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/pedestrian_yolov3_darknet.pdparams -num_classes: 1 +weights: output/yolov3_darknet53_40e_608x608_mot17half/model_final +log_iter: 20 +snapshot_epoch: 2 -# This pedestrian training dataset used is not open temporarily. -# Only the trained yolov3 model is provided, but you can eval on MOT17 half val dataset. -TrainDataset: - !COCODataSet - dataset_dir: dataset/pedestrian - anno_path: annotations/instances_train2017.json - image_dir: train2017 - data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd'] +# schedule configuration for fine-tuning +epoch: 40 +LearningRate: + base_lr: 0.0001 + schedulers: + - !PiecewiseDecay + gamma: 0.1 + milestones: + - 32 + - 36 + - !LinearWarmup + start_factor: 0.3333333333333333 + steps: 100 -EvalDataset: - !COCODataSet - dataset_dir: dataset/mot/MOT17/images - anno_path: annotations/val_half.json - image_dir: train +OptimizerBuilder: + optimizer: + momentum: 0.9 + type: Momentum + regularizer: + factor: 0.0005 + type: L2 +TrainReader: + batch_size: 8 + mixup_epoch: 35 # detector configuration architecture: YOLOv3 -pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/DarkNet53_pretrained.pdparams +pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/yolov3_darknet53_270e_coco.pdparams norm_type: sync_bn YOLOv3: diff --git a/configs/mot/deepsort/reid/README.md b/configs/mot/deepsort/reid/README.md index e19a92dd2..57a81b4fa 100644 --- a/configs/mot/deepsort/reid/README.md +++ b/configs/mot/deepsort/reid/README.md @@ -9,7 +9,7 @@ English | [简体中文](README_cn.md) ### Results on Market1501 pedestrian ReID dataset -| Backbone | Model | Params | FPS | mAP | Top1 | Top5 | download | config | +| Backbone | Model | Params | FPS | mAP | Top1 | Top5 | download | config | | :-------------: | :-----------------: | :-------: | :------: | :-------: | :-------: | :-------: | :-------: | :-------: | | ResNet-101 | PCB Pyramid Embedding | 289M | --- | 86.31 | 94.95 | 98.28 | [download](https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pcb_pyramid_r101.pdparams) | [config](./deepsort_pcb_pyramid_r101.yml) | | PPLCNet-2.5x | PPLCNet Embedding | 36M | --- | 71.59 | 87.38 | 95.49 | [download](https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pplcnet.pdparams) | [config](./deepsort_pplcnet.yml) | diff --git a/configs/mot/deepsort/reid/deepsort_pcb_pyramid_r101.yml b/configs/mot/deepsort/reid/deepsort_pcb_pyramid_r101.yml index 1895bae22..42fe6eb2a 100644 --- a/configs/mot/deepsort/reid/deepsort_pcb_pyramid_r101.yml +++ b/configs/mot/deepsort/reid/deepsort_pcb_pyramid_r101.yml @@ -15,7 +15,7 @@ EvalMOTDataset: keep_ori_im: True # set as True in DeepSORT det_weights: None -reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams +reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_pcb_pyramid_r101.pdparams # A ReID only configuration of DeepSORT, detector should be None. @@ -28,6 +28,7 @@ DeepSORT: tracker: DeepSORTTracker PCBPyramid: + model_name: "ResNet101" num_conv_out_channels: 128 num_classes: 751 # default 751 classes in Market-1501 dataset. diff --git a/configs/mot/deepsort/reid/deepsort_resnet.yml b/configs/mot/deepsort/reid/deepsort_resnet.yml new file mode 100644 index 000000000..7ca06b3e1 --- /dev/null +++ b/configs/mot/deepsort/reid/deepsort_resnet.yml @@ -0,0 +1,43 @@ +# This config represents a ReID only configuration of DeepSORT, it has two uses. +# One is used for loading the detection results and ReID model to get tracking results; +# Another is used for exporting the ReID model to deploy infer. + +_BASE_: [ + '../../../datasets/mot.yml', + '../../../runtime.yml', + '../_base_/deepsort_reader_1088x608.yml', +] + +EvalMOTDataset: + !MOTImageFolder + dataset_dir: dataset/mot + data_root: MOT16/images/train + keep_ori_im: True # set as True in DeepSORT + +det_weights: None +reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort/deepsort_resnet.pdparams + + +# A ReID only configuration of DeepSORT, detector should be None. +architecture: DeepSORT +pretrain_weights: None + +DeepSORT: + detector: None + reid: ResNetEmbedding + tracker: DeepSORTTracker + +ResNetEmbedding: + model_name: "ResNet50" + +DeepSORTTracker: + input_size: [64, 192] + min_box_area: 0 # filter out too small boxes + vertical_ratio: -1 # filter out bboxes, usuallly set 1.6 for pedestrian + budget: 100 + max_age: 70 + n_init: 3 + metric_type: cosine + matching_threshold: 0.2 + max_iou_distance: 0.9 + motion: KalmanFilter diff --git a/ppdet/engine/tracker.py b/ppdet/engine/tracker.py index daa7a47af..6d6407418 100644 --- a/ppdet/engine/tracker.py +++ b/ppdet/engine/tracker.py @@ -241,7 +241,7 @@ class Tracker(object): outs['bbox'] = outs['bbox'].numpy() outs['bbox_num'] = outs['bbox_num'].numpy() - if outs['bbox_num'] > 0 and empty_detections == False: + if len(outs['bbox']) > 0 and empty_detections == False: # detector outputs: pred_cls_ids, pred_scores, pred_bboxes pred_cls_ids = outs['bbox'][:, 0:1] pred_scores = outs['bbox'][:, 1:2] diff --git a/ppdet/modeling/reid/__init__.py b/ppdet/modeling/reid/__init__.py index 3b461325f..3c176d705 100644 --- a/ppdet/modeling/reid/__init__.py +++ b/ppdet/modeling/reid/__init__.py @@ -17,9 +17,11 @@ from . import fairmot_embedding_head from . import resnet from . import pyramidal_embedding from . import pplcnet_embedding +from . import resnet_embedding from .fairmot_embedding_head import * from .jde_embedding_head import * from .resnet import * from .pyramidal_embedding import * from .pplcnet_embedding import * +from .resnet_embedding import * diff --git a/ppdet/modeling/reid/pyramidal_embedding.py b/ppdet/modeling/reid/pyramidal_embedding.py index a90d4e1ef..6b2a76d60 100644 --- a/ppdet/modeling/reid/pyramidal_embedding.py +++ b/ppdet/modeling/reid/pyramidal_embedding.py @@ -21,7 +21,7 @@ import paddle.nn as nn import paddle.nn.functional as F from paddle.nn.initializer import Normal, Constant from paddle import ParamAttr -from .resnet import * +from .resnet import ResNet50, ResNet101 from ppdet.core.workspace import register __all__ = ['PCBPyramid'] @@ -46,6 +46,7 @@ class PCBPyramid(nn.Layer): def __init__(self, input_ch=2048, + model_name='ResNet101', num_stripes=6, used_levels=(1, 1, 1, 1, 1, 1), num_classes=751, @@ -60,7 +61,8 @@ class PCBPyramid(nn.Layer): self.num_in_each_level = [i for i in range(self.num_stripes, 0, -1)] self.num_branches = sum(self.num_in_each_level) - self.base = ResNet101( + assert model_name in ['ResNet50', 'ResNet101'], "Unsupported ReID arch: {}".format(model_name) + self.base = eval(model_name)( lr_mult=0.1, last_conv_stride=last_conv_stride, last_conv_dilation=last_conv_dilation) diff --git a/ppdet/modeling/reid/resnet_embedding.py b/ppdet/modeling/reid/resnet_embedding.py new file mode 100644 index 000000000..28c11eb40 --- /dev/null +++ b/ppdet/modeling/reid/resnet_embedding.py @@ -0,0 +1,41 @@ +# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os +import paddle +import paddle.nn.functional as F +from paddle import nn +from .resnet import ResNet50, ResNet101 +from ppdet.core.workspace import register + +__all__ = ['ResNetEmbedding'] + + +@register +class ResNetEmbedding(nn.Layer): + in_planes = 2048 + def __init__(self, model_name='ResNet50', last_stride=1): + super(ResNetEmbedding, self).__init__() + assert model_name in ['ResNet50', 'ResNet101'], "Unsupported ReID arch: {}".format(model_name) + self.base = eval(model_name)(last_conv_stride=last_stride) + self.gap = nn.AdaptiveAvgPool2D(output_size=1) + self.flatten = nn.Flatten(start_axis=1, stop_axis=-1) + self.bn = nn.BatchNorm1D(self.in_planes, bias_attr=False) + + def forward(self, x): + base_out = self.base(x) + global_feat = self.gap(base_out) + global_feat = self.flatten(global_feat) + global_feat = self.bn(global_feat) + return global_feat -- GitLab