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metafile.yml
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Collections:
- Name: YOLACT
Metadata:
Training Data: COCO
Training Techniques:
- SGD with Momentum
- Weight Decay
Training Resources: 8x V100 GPUs
Architecture:
- FPN
- ResNet
Paper:
URL: https://arxiv.org/abs/1904.02689
Title: 'YOLACT: Real-time Instance Segmentation'
README: configs/yolact/README.md
Code:
URL: https://github.com/open-mmlab/mmdetection/blob/v2.5.0/mmdet/models/detectors/yolact.py#L9
Version: v2.5.0
Models:
- Name: yolact_r50_1x8_coco
In Collection: YOLACT
Config: configs/yolact/yolact_r50_1x8_coco.py
Metadata:
Training Resources: 1x V100 GPU
Batch Size: 8
inference time (ms/im):
- value: 23.53
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (550, 550)
Results:
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 29.0
Weights: https://download.openmmlab.com/mmdetection/v2.0/yolact/yolact_r50_1x8_coco/yolact_r50_1x8_coco_20200908-f38d58df.pth
- Name: yolact_r50_8x8_coco
In Collection: YOLACT
Config: configs/yolact/yolact_r50_8x8_coco.py
Metadata:
Batch Size: 64
inference time (ms/im):
- value: 23.53
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (550, 550)
Results:
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 28.4
Weights: https://download.openmmlab.com/mmdetection/v2.0/yolact/yolact_r50_8x8_coco/yolact_r50_8x8_coco_20200908-ca34f5db.pth
- Name: yolact_r101_1x8_coco
In Collection: YOLACT
Config: configs/yolact/yolact_r101_1x8_coco.py
Metadata:
Training Resources: 1x V100 GPU
Batch Size: 8
inference time (ms/im):
- value: 29.85
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (550, 550)
Results:
- Task: Instance Segmentation
Dataset: COCO
Metrics:
mask AP: 30.4
Weights: https://download.openmmlab.com/mmdetection/v2.0/yolact/yolact_r101_1x8_coco/yolact_r101_1x8_coco_20200908-4cbe9101.pth