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镜像社区 可搜索到所有公开的ymir算法镜像， 同时可共享其他人发布的镜像。
| docker image | finetune | tensorboard | args/cfg options | framework | onnx | pretrained weight |
|---|---|---|---|---|---|---|
| yolov4 | ? | ✔️ | ❌ | darknet + mxnet | ❌ | local |
| yolov5 | ✔️ | ✔️ | ✔️ | pytorch | ✔️ | local+online |
| yolov7 | ✔️ | ✔️ | ✔️ | pytorch | ❌ | local+online |
| mmdetection | ✔️ | ✔️ | ✔️ | pytorch | ❌ | local+online |
| detectron2 | ✔️ | ✔️ | ✔️ | pytorch | ❌ | online |
| vidt | ? | ✔️ | ✔️ | pytorch | ❌ | online |
| nanodet | ✔️ | ✔️ | ❌ | pytorch_lightning | ❌ | local+online |
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online预训练权重可能在训练时通过网络下载 -
local预训练权重在构建镜像时复制到了镜像
- 训练集: voc2012-train 5717 images
- 测试集: voc2012-val 5823 images
- 图像大小: 640 (nanodet为416, yolov4为608)
由于 coco 数据集包含 voc 数据集中的类, 因此这个对比并不公平, 仅供参考
gpu: single Tesla P4
| docker image | batch size | epoch number | model | voc2012 val map50 | training time | note |
|---|---|---|---|---|---|---|
| yolov5 | 16 | 100 | yolov5s | 70.05% | 9h | coco-pretrained |
| vidt | 2 | 100 | swin-nano | 54.13% | 2d | imagenet-pretrained |
| yolov4 | 4 | 20000 steps | yolov4 | 66.18% | 2d | imagenet-pretrained |
| yolov7 | 16 | 100 | yolov7-tiny | 70% | 8h | coco-pretrained |
gpu: single GeForce GTX 1080 Ti
| docker image | image size | batch size | epoch number | model | voc2012 val map50 | training time | note |
|---|---|---|---|---|---|---|---|
| yolov4 | 608 | 64/32 | 20000 steps | yolov4 | 72.73% | 6h | imagenet-pretrained |
| yolov5 | 640 | 16 | 100 | yolov5s | 70.35% | 2h | coco-pretrained |
| yolov7 | 640 | 16 | 100 | yolov7-tiny | 70.4% | 5h | coco-pretrained |
| mmdetection | 640 | 16 | 100 | yolox_tiny | 66.2% | 5h | coco-pretrained |
| detectron2 | 640 | 2 | 20000 steps | retinanet_R_50_FPN_1x | 53.54% | 2h | imagenet-pretrained |
| nanodet | 416 | 16 | 100 | nanodet-plus-m_416 | 58.63% | 5h | imagenet-pretrained |
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- 通过ymir网页端的
模型管理/模型列表/导入模型同样可以导入模型
- 通过ymir网页端的