xiaoheizi123 commented on issue #7162: Cant convert caffe model to mxnet URL: https://github.com/apache/incubator-mxnet/issues/7162#issuecomment-367900241 I also cannot convert resnet-50 using **python convert_caffe_modelzoo.py resnet-50** `converting scale layer, beta shape = (2048,), gamma shape = (2048,) skipping layer res5c of type Eltwise skipping layer res5c_relu of type ReLU skipping layer pool5 of type Pooling converting layer fc1000, wmat shape = (1000, 2048), bias shape = (1000,) skipping layer prob of type Softmax /home/users/rui.zheng/anaconda2/lib/python2.7/site-packages/mxnet/module/base_module.py:65: UserWarning: Data provided by label_shapes don't match names specified by label_names ([] vs. ['prob_label']) warnings.warn(msg) Traceback (most recent call last): File "convert_caffe_modelzoo.py", line 144, in <module> fname, _ = convert_caffe_model(args.model_name, model_meta_info[args.model_name]) File "convert_caffe_modelzoo.py", line 133, in convert_caffe_model convert_mean(mean, [mx_mean]) File "/home/users/rui.zheng/works/incubator-mxnet/tools/caffe_converter/convert_mean.py", line 44, in convert_mean mean_blob.ParseFromString(f.read()) google.protobuf.message.DecodeError: Error parsing message ` f.read() is ok, but mean_blob is None when print it? I also read [https://github.com/apache/incubator-mxnet/blob/430ea7bfbbda67d993996d81c7fd44d3a20ef846/docs/how_to/caffe.md](url), and do what **Converting Caffe trained models to MXNet** part shows, but it is still wrong, what should I do?
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