metafile.yml
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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_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_mstrain-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_mstrain-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_fp16_mstrain-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_320_300e_coco
In Collection: YOLOv3
Config: configs/yolo/yolov3_mobilenetv2_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_mstrain-416_300e_coco
In Collection: YOLOv3
Config: configs/yolo/yolov3_mobilenetv2_mstrain-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