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201 Open 75 Closed
201 Open 75 Closed
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Issues list

關於ImplicitA layer和ImplicitM layer的問題
#159 opened Dec 28, 2021 by chenweifu2008
1
What's differ ImpliictA and ImplicitC in layers.py ?
#158 opened Dec 24, 2021 by HERIUN
1
Training Yolor_p6 in darknet
#157 opened Dec 22, 2021 by Wazaki-Ou
1
Freeze
#156 opened Dec 17, 2021 by kadmor
Input Data Requirements
#155 opened Dec 16, 2021 by MarioCodeMatuschek
Is the scale_x_y (from cfg file) being used?
#153 opened Dec 12, 2021 by marcoslucianops
PermissionError: [Errno 13] Permission denied: 'libcrypto.so.1.1'
#152 opened Dec 10, 2021 by CharlesNJ
Could you clarify what happens in build_targets() function?
#149 opened Dec 6, 2021 by LaCandela
2
detect.py list index out of range error
#148 opened Dec 6, 2021 by lionopen64
3
Controlling celles to be scaned
#147 opened Dec 4, 2021 by loucif01
Single class training
#146 opened Dec 2, 2021 by MrCri5py
1
YOLOv4-CSP-X and YOLOR-CSP-X
#145 opened Dec 2, 2021 by kadmor
2
Mish_cuda
#144 opened Dec 2, 2021 by kadmor
1
想用自己的訓練集，但mAP一直是0，
#142 opened Nov 24, 2021 by FrankFang0813
1
Transfer Learning
#141 opened Nov 24, 2021 by sard0r
3
yolor_d6 cfg
#140 opened Nov 19, 2021 by Wooks-git
10
Hi, does the second stage classifier in the detect.py work? If yes, how to implement it? Please help.
#138 opened Nov 15, 2021 by Zypherous123
How to store checkpoints periodically?
#137 opened Nov 14, 2021 by neel04
2
Error just after training is completed
#136 opened Nov 13, 2021 by neel04
4
Detection results from test.py and detect.py are not the same
#135 opened Nov 7, 2021 by AMF2601
1
Question about detected objects features extraction
#134 opened Nov 6, 2021 by divid3d
4
augmentstion while inference is not working
#133 opened Nov 6, 2021 by AndreiErofeev
1
在最后一个Epoch训练完后，验证时报错
#132 opened Nov 5, 2021 by 20XYSong
How to increase fps with detect.py ?
#131 opened Nov 3, 2021 by ManurachTi
Would you mind change most of x.split('.')[-1] to os.path.splitext(x)[-1] in datasets.py?
#126 opened Oct 22, 2021 by bassaniokum
1
ProTip! Adding no:label will show everything without a label.