Comments (5)
hhaAndroid
commented on August 29, 2024
@SunshinePi Thank you very much, let's check the window
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vansin
commented on August 29, 2024
Please provide the command you start the train.py like
python tools/train.py configs/xxxx.pyfrom mmyolo.
SunshinePi
commented on August 29, 2024
Sorry that I replied you late, the issue is not fixed.
The command I started the train.py in this way:
python tools/train.py configs/yolov5/yolov5_s-v61_syncbn_fast_1xb4-300e_balloon.py
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vansin
commented on August 29, 2024
can you try in latest mmyolo mmengine version?
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SunshinePi
commented on August 29, 2024
I re-downloaded mmyolo code, and re-installed dependencies.
During the running in my computer, The filename value is: 'C:\Users\FENG~1.ZHA\AppData\Local\Temp\tmp93ajmopa\tmp3l2tqy_w.py'
TorchVision: 0.13.1
OpenCV: 4.6.0
MMEngine: 0.3.1
MMCV: 2.0.0rc1
MMDetection: 3.0.0rc3
MMYOLO: 0.1.3+178b0bf
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Related Issues (20)
- Please upgrade the python version of this project
- Padding bug
- This line works but seems not good HOT 1
- Cat example does not work out of the box HOT 4
- It worked particularly poorly after changing the bbox_loss to SiouLoss on RTMDet.
- ValueError: Key img_path is not in available keys. Unable to find a solution. HOT 3
- Discrepancy in Training Times
- How to control randomness？如何控制随机性？
- Why do I get an error when visualizing with GradCAM methods? How to solve it? HOT 1
- Would you consider supporting the YOLOv8-p2 model？
- deepstream7.0部署适配
- Bounding Box Thickness
- MMYOLO for yolov5 instance segmentation on balloon dataset getting this error "ValueError: Key img_path is not in available keys." HOT 2
- MMYOLO with TFLite
- Build Error: AttributeError: 'MinimalDistribution' object has no attribute '_referenced_files'
- ImportError: dlopen(mmyolo/venv/lib/python3.9/site-packages/mmcv/_ext.cpython-39-darwin.so, 0x0002): symbol not found in flat namespace N2at3mps9MPSStream6commitEb)
- [Docs] A100算力加持！书生大模型实战营第3期全面升级，趣味闯关模式等你开启
- In the classification loss calculation, ensure that the ignored regions of the image do not participate, meaning they should not contribute to the classification loss.
- error installing
- How does RTMDet ensure that the outputs of reg branch are non-negative?
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