From 3af2e211e81b2ef594081dc62e168bce68ec1a6d Mon Sep 17 00:00:00 2001 From: littletomatodonkey Date: Sun, 24 Nov 2019 18:22:04 +0800 Subject: [PATCH] Add models basd on OpenImage-v5 and Object365 (#26) * Add cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms model on oidv5 and obj365. * Add obj365 config annotation * Update docs. --- README.md | 8 +- README_en.md | 7 + ...are_r200_vd_fpn_dcnv2_nonlocal_softnms.yml | 190 ++++++ ...are_r200_vd_fpn_dcnv2_nonlocal_softnms.yml | 189 ++++++ demo/oidv5_gt.png | Bin 0 -> 1833741 bytes demo/oidv5_model_framework.png | Bin 0 -> 778185 bytes demo/oidv5_pred.jpg | Bin 0 -> 158853 bytes docs/MODEL_ZOO.md | 5 + docs/MODEL_ZOO_cn.md | 8 +- docs/OIDV5_BASELINE_MODEL.md | 58 ++ ppdet/modeling/target_assigners.py | 2 +- ppdet/utils/oid_eval.py | 544 ++++++++++++++++++ tools/eval.py | 5 +- tools/infer.py | 6 +- 14 files changed, 1016 insertions(+), 6 deletions(-) create mode 100644 configs/obj365/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml create mode 100644 configs/oidv5/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml create mode 100644 demo/oidv5_gt.png create mode 100644 demo/oidv5_model_framework.png create mode 100644 demo/oidv5_pred.jpg create mode 100644 docs/OIDV5_BASELINE_MODEL.md create mode 100644 ppdet/utils/oid_eval.py diff --git a/README.md b/README.md index 0f0375e7e..bab001a2e 100644 --- a/README.md +++ b/README.md @@ -71,6 +71,7 @@ PaddleDetection的目的是为工业界和学术界提供丰富、易用的目 - [行人检测和车辆检测预训练模型](contrib/README_cn.md) 针对不同场景的检测模型 - [YOLOv3增强模型](docs/YOLOv3_ENHANCEMENT.md) 改进原始YOLOv3,精度达到41.4%,原论文精度为33.0%,同时预测速度也得到提升 - [Objects365 2019 Challenge夺冠模型](docs/CACascadeRCNN.md) Objects365 Full Track任务中最好的单模型之一,精度达到31.7% +- [Open Images V5和Objects365数据集模型](docs/OIDV5_BASELINE_MODEL.md) ## 模型压缩 @@ -90,8 +91,13 @@ PaddleDetection的目的是为工业界和学术界提供丰富、易用的目 ## 版本更新 -### 10/2019 +### 21/11/2019 +- 增加CascadeClsAware RCNN模型。 +- 增加CBNet,ResNet200和Non-local模型。 +- 增加SoftNMS。 +- 增加Open Image V5数据集和Objects365数据集模型。 +### 10/2019 - 增加增强版YOLOv3模型,精度高达41.4%。 - 增加人脸检测模型BlazeFace、Faceboxes。 - 丰富基于COCO的模型,精度高达51.9%。 diff --git a/README_en.md b/README_en.md index e055beadc..e083193dd 100644 --- a/README_en.md +++ b/README_en.md @@ -80,6 +80,7 @@ Advanced Features: - [Pretrained models for pedestrian and vehicle detection](contrib/README.md) Models for object detection in specific scenarios. - [YOLOv3 enhanced model](docs/YOLOv3_ENHANCEMENT.md) Compared to MAP of 33.0% in paper, enhanced YOLOv3 reaches the MAP of 41.4% and inference speed is improved as well - [Objects365 2019 Challenge champion model](docs/CACascadeRCNN.md) One of the best single models in Objects365 Full Track of which MAP reaches 31.7%. +- [Open Images Dataset V5 and Objects365 Dataset models](docs/OIDV5_BASELINE_MODEL.md) ## Model compression @@ -98,6 +99,12 @@ Advanced Features: ## Updates +#### 21/11/2019 +- Add CascadeClsAware RCNN model. +- Add CBNet, ResNet200 and Non-local model. +- Add SoftNMS. +- Add models of Open Images Dataset V5 and Objects365 Dataset. + #### 10/2019 - Add enhanced YOLOv3 models, box mAP up to 41.4%. diff --git a/configs/obj365/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml b/configs/obj365/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml new file mode 100644 index 000000000..0de0e9f52 --- /dev/null +++ b/configs/obj365/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml @@ -0,0 +1,190 @@ +architecture: CascadeRCNNClsAware +train_feed: FasterRCNNTrainFeed +eval_feed: FasterRCNNEvalFeed +test_feed: FasterRCNNTestFeed +max_iters: 800000 +snapshot_iter: 10000 +use_gpu: true +log_smooth_window: 20 +save_dir: output +pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet200_vd_pretrained.tar +weights: output/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms/model_final +# obj365 dataset format and its eval method are same as those for coco +metric: COCO +num_classes: 366 + +CascadeRCNNClsAware: + backbone: ResNet + fpn: FPN + rpn_head: FPNRPNHead + roi_extractor: FPNRoIAlign + bbox_head: CascadeBBoxHead + bbox_assigner: CascadeBBoxAssigner + +ResNet: + norm_type: bn + depth: 200 + feature_maps: [2, 3, 4, 5] + freeze_at: 2 + variant: d + dcn_v2_stages: [3, 4, 5] + nonlocal_stages: [4] + +FPN: + min_level: 2 + max_level: 6 + num_chan: 256 + spatial_scale: [0.03125, 0.0625, 0.125, 0.25] + +FPNRPNHead: + anchor_generator: + anchor_sizes: [32, 64, 128, 256, 512] + aspect_ratios: [0.5, 1.0, 2.0] + stride: [16.0, 16.0] + variance: [1.0, 1.0, 1.0, 1.0] + anchor_start_size: 32 + min_level: 2 + max_level: 6 + num_chan: 256 + rpn_target_assign: + rpn_batch_size_per_im: 256 + rpn_fg_fraction: 0.5 + rpn_positive_overlap: 0.7 + rpn_negative_overlap: 0.3 + rpn_straddle_thresh: 0.0 + train_proposal: + min_size: 0.0 + nms_thresh: 0.7 + pre_nms_top_n: 2000 + post_nms_top_n: 2000 + test_proposal: + min_size: 0.0 + nms_thresh: 0.7 + pre_nms_top_n: 1000 + post_nms_top_n: 1000 + +FPNRoIAlign: + canconical_level: 4 + canonical_size: 224 + min_level: 2 + max_level: 5 + box_resolution: 14 + sampling_ratio: 2 + +CascadeBBoxAssigner: + batch_size_per_im: 512 + bbox_reg_weights: [10, 20, 30] + bg_thresh_lo: [0.0, 0.0, 0.0] + bg_thresh_hi: [0.5, 0.6, 0.7] + fg_thresh: [0.5, 0.6, 0.7] + fg_fraction: 0.25 + class_aware: True + +CascadeBBoxHead: + head: CascadeTwoFCHead + nms: MultiClassSoftNMS + +CascadeTwoFCHead: + mlp_dim: 1024 + +MultiClassSoftNMS: + score_threshold: 0.001 + keep_top_k: 300 + softnms_sigma: 0.15 + +LearningRate: + base_lr: 0.01 + schedulers: + - !PiecewiseDecay + gamma: 0.1 + milestones: [520000, 740000] + - !LinearWarmup + start_factor: 0.1 + steps: 1000 + +OptimizerBuilder: + optimizer: + momentum: 0.9 + type: Momentum + regularizer: + factor: 0.0001 + type: L2 + +FasterRCNNTrainFeed: + batch_size: 1 + dataset: + dataset_dir: dataset/obj365 + annotation: train.json + image_dir: train + sample_transforms: + - !DecodeImage + to_rgb: True + with_mixup: False + - !RandomFlipImage + prob: 0.5 + - !NormalizeImage + is_channel_first: false + is_scale: True + mean: + - 0.485 + - 0.456 + - 0.406 + std: + - 0.229 + - 0.224 + - 0.225 + - !ResizeImage + interp: 1 + target_size: [416, 448, 480, 512, 544, 576, 608, 640, 672, 704, 736, 768, 800, 832, 864, 896, 928, 960, 992, 1024, 1056, 1088, 1120, 1152, 1184, 1216, 1248, 1280, 1312, 1344, 1376, 1408] + max_size: 1800 + use_cv2: true + - !Permute + to_bgr: false + batch_transforms: + - !PadBatch + pad_to_stride: 32 + drop_last: false + num_workers: 2 + +FasterRCNNEvalFeed: + batch_size: 1 + dataset: + dataset_dir: dataset/obj365 + annotation: val.json + image_dir: val + sample_transforms: + - !DecodeImage + to_rgb: True + with_mixup: False + - !NormalizeImage + is_channel_first: false + is_scale: True + mean: + - 0.485 + - 0.456 + - 0.406 + std: + - 0.229 + - 0.224 + - 0.225 + - !ResizeImage + interp: 1 + target_size: + - 1200 + max_size: 2000 + use_cv2: true + - !Permute + to_bgr: false + batch_transforms: + - !PadBatch + pad_to_stride: 32 + +FasterRCNNTestFeed: + batch_size: 1 + dataset: + annotation: dataset/obj365/val.json + batch_transforms: + - !PadBatch + pad_to_stride: 32 + drop_last: false + num_workers: 2 diff --git a/configs/oidv5/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml b/configs/oidv5/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml new file mode 100644 index 000000000..be07dd55a --- /dev/null +++ b/configs/oidv5/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms.yml @@ -0,0 +1,189 @@ +architecture: CascadeRCNNClsAware +train_feed: FasterRCNNTrainFeed +eval_feed: FasterRCNNEvalFeed +test_feed: FasterRCNNTestFeed +max_iters: 1500000 +snapshot_iter: 10000 +use_gpu: true +log_smooth_window: 20 +save_dir: output +pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet200_vd_pretrained.tar +weights: output/cascade_rcnn_cls_aware_r200_vd_fpn_dcnv2_nonlocal_softnms/model_final +metric: OID +num_classes: 501 + +CascadeRCNNClsAware: + backbone: ResNet + fpn: FPN + rpn_head: FPNRPNHead + roi_extractor: FPNRoIAlign + bbox_head: CascadeBBoxHead + bbox_assigner: CascadeBBoxAssigner + +ResNet: + norm_type: bn + depth: 200 + feature_maps: [2, 3, 4, 5] + freeze_at: 2 + variant: d + dcn_v2_stages: [3, 4, 5] + nonlocal_stages: [4] + +FPN: + min_level: 2 + max_level: 6 + num_chan: 256 + spatial_scale: [0.03125, 0.0625, 0.125, 0.25] + +FPNRPNHead: + anchor_generator: + anchor_sizes: [32, 64, 128, 256, 512] + aspect_ratios: [0.5, 1.0, 2.0] + stride: [16.0, 16.0] + variance: [1.0, 1.0, 1.0, 1.0] + anchor_start_size: 32 + min_level: 2 + max_level: 6 + num_chan: 256 + rpn_target_assign: + rpn_batch_size_per_im: 256 + rpn_fg_fraction: 0.5 + rpn_positive_overlap: 0.7 + rpn_negative_overlap: 0.3 + rpn_straddle_thresh: 0.0 + train_proposal: + min_size: 0.0 + nms_thresh: 0.7 + pre_nms_top_n: 2000 + post_nms_top_n: 2000 + test_proposal: + min_size: 0.0 + nms_thresh: 0.7 + pre_nms_top_n: 1000 + post_nms_top_n: 1000 + +FPNRoIAlign: + canconical_level: 4 + canonical_size: 224 + min_level: 2 + max_level: 5 + box_resolution: 14 + sampling_ratio: 2 + +CascadeBBoxAssigner: + batch_size_per_im: 512 + bbox_reg_weights: [10, 20, 30] + bg_thresh_lo: [0.0, 0.0, 0.0] + bg_thresh_hi: [0.5, 0.6, 0.7] + fg_thresh: [0.5, 0.6, 0.7] + fg_fraction: 0.25 + class_aware: True + +CascadeBBoxHead: + head: CascadeTwoFCHead + nms: MultiClassSoftNMS + +CascadeTwoFCHead: + mlp_dim: 1024 + +MultiClassSoftNMS: + score_threshold: 0.001 + keep_top_k: 300 + softnms_sigma: 0.15 + +LearningRate: + base_lr: 0.01 + schedulers: + - !PiecewiseDecay + gamma: 0.1 + milestones: [1000000, 1400000] + - !LinearWarmup + start_factor: 0.1 + steps: 1000 + +OptimizerBuilder: + optimizer: + momentum: 0.9 + type: Momentum + regularizer: + factor: 0.0001 + type: L2 + +FasterRCNNTrainFeed: + batch_size: 1 + dataset: + dataset_dir: dataset/oid + annotation: train.json + image_dir: train + sample_transforms: + - !DecodeImage + to_rgb: True + with_mixup: False + - !RandomFlipImage + prob: 0.5 + - !NormalizeImage + is_channel_first: false + is_scale: True + mean: + - 0.485 + - 0.456 + - 0.406 + std: + - 0.229 + - 0.224 + - 0.225 + - !ResizeImage + interp: 1 + target_size: [416, 448, 480, 512, 544, 576, 608, 640, 672, 704, 736, 768, 800, 832, 864, 896, 928, 960, 992, 1024, 1056, 1088, 1120, 1152, 1184, 1216, 1248, 1280, 1312, 1344, 1376, 1408] + max_size: 1800 + use_cv2: true + - !Permute + to_bgr: false + batch_transforms: + - !PadBatch + pad_to_stride: 32 + drop_last: false + num_workers: 2 + +FasterRCNNEvalFeed: + batch_size: 1 + dataset: + dataset_dir: dataset/oidv5 + annotation: val.json + image_dir: val + sample_transforms: + - !DecodeImage + to_rgb: True + with_mixup: False + - !NormalizeImage + is_channel_first: false + is_scale: True + mean: + - 0.485 + - 0.456 + - 0.406 + std: + - 0.229 + - 0.224 + - 0.225 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