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#### Introduction | ||
This page will introduce the usage of Caffe converter. It can convert a pretrained model in Caffe to cxxnet format. | ||
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#### Preparation | ||
* To begin with the convert, a latest version of Caffe should be built. | ||
* Currently, no automatic configuration file converter is provided. You need to convert the Caffe config file in prototxt to cxxnet configuration format by yourself. **Please make sure that all the layers in original Caffe model has corresponding layer in cxxnet!** | ||
* Converters are provided in both C++ and Python. | ||
- To use the C++ converter, you need to specify the following paths in the config.mk. For example, | ||
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```bash | ||
# whether to build caffe converter | ||
USE_CAFFE_CONVERTER = 1 | ||
CAFFE_ROOT = ~/caffe | ||
CAFFE_INCLUDE = ~/caffe/include/ | ||
CAFFE_LIB = ~/caffe/build/lib/ | ||
``` | ||
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Then, run ```make all``` in the root of cxxnet. if everything is correct, you could find ```caffe_converter``` and ```caffe_mean_converter``` in the ```bin``` folder. | ||
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- To use the Python converter, you should first make sure the Python wrapper of Caffe is successfully built. Then you need to specify the paths of Caffe and cxxnet in ```tools/caffe_converter/convert.py```. | ||
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#### Convert | ||
* Simply run '''bin/caffe_converter''' and '''tools/caffe_converter/convert.py''', and then follow the instructions. | ||
* To convert the mean file of Caffe, please use the C++ converter: ```caffe_mean_converter```. But we strongly recommend you to recompute the mean file in cxxnet due to the different data augmentation methods in Caffe and cxxnet. | ||
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