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20 Open 26 Closed
20 Open 26 Closed
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Issues list

Caffe2keras.py: ValueError: need more than 3 values to unpack in convert.py
#61 opened Jan 20, 2020 by rubeea
Hi, I'm just wondering why you coded like this.
#60 opened Jul 26, 2019 by seolhokim
Negative dimension size for 'pool2/MaxPool' (op: 'MaxPool') with input shapes:[?,1,112,128].
#59 opened Jun 21, 2018 by SANTO-P
TypeError: expected bytes, str found
#58 opened Jun 12, 2018 by SANTO-P
4
TypeError: __call__() takes 2 positional arguments but 4 were given
#56 opened Mar 29, 2018 by Imorton-zd
4
Error when converting with Scale layer
#55 opened Mar 26, 2018 by zihangJiang
1
Error when converting with merge layer
#51 opened Dec 1, 2017 by dangz90
python3 support for caffe2keras
#50 opened Nov 26, 2017 by kamikawa
1
Conversion of PoolingND Layer
#47 opened Aug 19, 2017 by User-Ali
when i run test_segmentation.py i receive this essor str(n) + ' integers. Received: ' + str(value)) ValueError: The 1st entry of padding argument must be a tuple of 2 integers. Received: 100
#46 opened Aug 10, 2017 by mosbahi1
4 tasks
Bug when run caffe2keras
#43 opened Aug 8, 2017 by lelechen63
1
Deconvolution layer not supported, while converting caffemodel weight into keras.
#36 opened Apr 8, 2017 by rajeev-cmi
3
Problems in Inferring input shape in caffe_to_keras function in convert.py
#34 opened Apr 4, 2017 by akshaychawla
Error when converting places205VGG to keras
#29 opened Mar 7, 2017 by nabilasan
Error converting Places365 caffe models to keras
#28 opened Mar 7, 2017 by tonizzz
1
Squeeze net conversion
#27 opened Mar 4, 2017 by AliaMYH
3
No model found in config file when trying to load converted model
#25 opened Jan 13, 2017 by dchouren
4
Problem in converting V2 models
#24 opened Dec 25, 2016 by divamgupta
Please provide to Input either a shape or a batch_shape argument. Note that shape does not include the batch dimension.
#22 opened Dec 1, 2016 by abdulqayyum
2
Error trying to read model from keras/caffe/models/googleNet_structure.json
#13 opened Jul 11, 2016 by ternaus
2
ProTip! Exclude everything labeled bug with -label:bug.