Comments (3)
DualDDetect is concatenation of two DDetect, and DDetect is a fully decoupled Detect module.
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Huge thanks to the folks behind these YOLO models. They're doing some awesome work!
Quick thing, I'm curious about the different training scripts – train.py, train_dual.py, and train_triple.py. Why the need for separate scripts based on the number of GPUs? In the past, we could just pick a GPU with an ID. What's the story behind these variations? Appreciate the insights!
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Related Issues (20)
- detect时,augment为True 推理报错 HOT 3
- Training is too slow HOT 16
- 速度的对比呢 HOT 10
- AttributeError: 'list' object has no attribute 'device' HOT 2
- NMS plugin for segmentation model HOT 1
- hubconf.py does not work with pytorch hub
- Do yolo-seg support exporting to "ONNX END2END"? HOT 2
- CBLinear question HOT 1
- Doubts on the confusion matrix in yolov9
- Where is the yolov9-T configuration file? HOT 2
- Error: BaseModel.fuse() got an unexpected keyword argument 'verbose' HOT 2
- s += f"{n} {names[int(c)]}{'s' * (n > 1)}, " # add to string KeyError: 595 HOT 5
- I have converted model yolov9 using format type : TFLITE. HOT 3
- about running the reparameterization.ipynb appear the error HOT 3
- SyntaxError: invalid syntax
- GFLOPS measurement inaccuracy HOT 1
- Broken links on main page HOT 1
- Why val/loss was 0? HOT 13
- RuntimeError: The size of tensor a (1024) must match the size of tensor b (128) at non-singleton dimension 1 HOT 2
- Abnormal segmentation training for YOLOv9 HOT 1
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