Collections: - Name: YOLOv3 Metadata: Training Data: COCO Training Techniques: - SGD with Momentum - Weight Decay Training Resources: 8x V100 GPUs Architecture: - DarkNet Paper: URL: https://arxiv.org/abs/1804.02767 Title: 'YOLOv3: An Incremental Improvement' README: configs/yolo/README.md Code: URL: https://github.com/open-mmlab/mmdetection/blob/v2.4.0/mmdet/models/detectors/yolo.py#L8 Version: v2.4.0 Models: - Name: yolov3_d53_320_273e_coco In Collection: YOLOv3 Config: configs/yolo/yolov3_d53_8xb8-320-273e_coco.py Metadata: Training Memory (GB): 2.7 inference time (ms/im): - value: 15.65 hardware: V100 backend: PyTorch batch size: 1 mode: FP32 resolution: (320, 320) Epochs: 273 Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 27.9 Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_d53_320_273e_coco/yolov3_d53_320_273e_coco-421362b6.pth - Name: yolov3_d53_mstrain-416_273e_coco In Collection: YOLOv3 Config: configs/yolo/yolov3_d53_8xb8-ms-416-273e_coco.py Metadata: Training Memory (GB): 3.8 inference time (ms/im): - value: 16.34 hardware: V100 backend: PyTorch batch size: 1 mode: FP32 resolution: (416, 416) Epochs: 273 Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 30.9 Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_d53_mstrain-416_273e_coco/yolov3_d53_mstrain-416_273e_coco-2b60fcd9.pth - Name: yolov3_d53_mstrain-608_273e_coco In Collection: YOLOv3 Config: configs/yolo/yolov3_d53_8xb8-ms-608-273e_coco.py Metadata: Training Memory (GB): 7.4 inference time (ms/im): - value: 20.79 hardware: V100 backend: PyTorch batch size: 1 mode: FP32 resolution: (608, 608) Epochs: 273 Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 33.7 Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_d53_mstrain-608_273e_coco/yolov3_d53_mstrain-608_273e_coco_20210518_115020-a2c3acb8.pth - Name: yolov3_d53_fp16_mstrain-608_273e_coco In Collection: YOLOv3 Config: configs/yolo/yolov3_d53_8xb8-amp-ms-608-273e_coco.py Metadata: Training Memory (GB): 4.7 inference time (ms/im): - value: 20.79 hardware: V100 backend: PyTorch batch size: 1 mode: FP16 resolution: (608, 608) Epochs: 273 Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 33.8 Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_d53_fp16_mstrain-608_273e_coco/yolov3_d53_fp16_mstrain-608_273e_coco_20210517_213542-4bc34944.pth - Name: yolov3_mobilenetv2_8xb24-320-300e_coco In Collection: YOLOv3 Config: configs/yolo/yolov3_mobilenetv2_8xb24-320-300e_coco.py Metadata: Training Memory (GB): 3.2 Epochs: 300 Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 22.2 Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_mobilenetv2_320_300e_coco/yolov3_mobilenetv2_320_300e_coco_20210719_215349-d18dff72.pth - Name: yolov3_mobilenetv2_8xb24-ms-416-300e_coco In Collection: YOLOv3 Config: configs/yolo/yolov3_mobilenetv2_8xb24-ms-416-300e_coco.py Metadata: Training Memory (GB): 5.3 Epochs: 300 Results: - Task: Object Detection Dataset: COCO Metrics: box AP: 23.9 Weights: https://download.openmmlab.com/mmdetection/v2.0/yolo/yolov3_mobilenetv2_mstrain-416_300e_coco/yolov3_mobilenetv2_mstrain-416_300e_coco_20210718_010823-f68a07b3.pth