goldentimecoolk
goldentimecoolk
Hi, thanks for sharing your work. But logs that record the process corresponding to results reported in paper are lost. Can you please share them again?
When I begin to run the code, its cpu utilization is about 2000%, the training speed is acceptable. But with time going on, it falls to about 200% or 300%....
Hi, I'm new to object tracking and find your work amazing! Actually I'm a little bit confused about the spatial bias. After referring to these discussions[[1](https://github.com/STVIR/pysot/issues/111),[2](https://github.com/STVIR/pysot/issues/176)](by @beihaifusang), questions got answered...
Hi, why do not use the [common procedure](https://github.com/ifzhang/FairMOT/blob/master/src/lib/datasets/dataset/jde.py#L313-L316) to filter bboxes outside images, but use ```python targets = targets[targets[:, 2] < width] targets = targets[targets[:, 4] > 0] targets =...
Hi, thanks for your amazing work. I wonder how do you choose the best model after training. Because I found you didn't take validation during training. Do you take the...
您好，请问您使用的pytorch版本是多少呀？
```python C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\VC\Tools\MSVC\14.16.27023\bin\HostX86\x64\link.exe /nologo /INCREMENTAL:NO /LTCG /DLL /MANIFEST:EMBED,ID=2 /MANIFESTUAC:NO /LIBPATH:C:\Users\Administrator\anaconda3\envs\yol o\lib\site-packages\torch\lib "/LIBPATH:C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.1\lib/x64" /LIBPATH:C:\Users\Administrator\anaconda3\envs\yolo\libs /LIBPATH:C:\Users\Administrator\anaconda3\envs\yolo\PCbuild\amd64 "/LIBP ATH:C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\VC\Tools\MSVC\14.16.27023\ATLMFC\lib\x64" "/LIBPATH:C:\Program Files (x86)\Microsoft...
The link needs to be updated. Thank you.
Hi xingyi, thanks for your amazing work. I'm new to object detection and have made a few modifications based on your centernet with dla34 network. I found your performance on...
cMOTA
Thanks for your amazing work. I'm interested in the cMOTA and understand it theoretically. But I have no idea to implement it efficiently. I don't know how to get it...