caffe_weight_converter | Can also export weights | Machine Learning library
kandi X-RAY | caffe_weight_converter Summary
kandi X-RAY | caffe_weight_converter Summary
This is a Python tool to extract weights from a .caffemodel file and do either of two things:. That is, this is mainly a Caffe-to-Keras weight converter, but you can also have it export the weights into a simpler, possibly more familiar Python format (list of dictionaries) instead. Further below you can also find a list of links to weights for various models that I ported to Keras using this very converter. There are tools out there that attempt to convert both the model definition and the weights of a Caffe model to a given other deep learning framework (like the great caffe-tensorflow), but I don't believe that's the right approach. If you'd like to know why, read below. This program converts the weights only, not the model definition.
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Top functions reviewed by kandi - BETA
- Convert a caffe model to keras
- Convert a Caffe file to a dictionary
- Convert a caffe net file to a dictionary
caffe_weight_converter Key Features
caffe_weight_converter Examples and Code Snippets
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Trending Discussions on caffe_weight_converter
QUESTION
I want to implement caffeNet on keras with pre-trained on imagenet. So i got weight from caffe github there https://github.com/BVLC/caffe/tree/master/models/bvlc_reference_caffenet
I convert it to weight.h5 with caffe_weight_converter.Weight that i got on layer “conv2” have shape (256,48,5,5) but my implement model need (256,96,5,5).
I saw from Got confused after I extracted weights from Trained caffenet That because in layer "conv2" have split in 2 group. I want to ask that keras can split conv layer in to group ? or have any solution that can i get pretrained caffeNet on keras?
...ANSWER
Answered 2019-Jan-15 at 13:26I've tried to implement the lower part of CaffeNet(LRN layer omitted):
QUESTION
I want to fine tune a gender detector trained in caffe using my own data set. This model was trained by using around half a million face images. They fine tuned VGG16 pre-trained on ImageNet. I want to use this model as my base model.I downloaded gender.caffemodel file from this link:
I've used the tool provided in link below to convert this model to an h5 file to use in Keras:
https://github.com/pierluigiferrari/caffe_weight_converter
This tool only converts the weights. I want to use Keras to train my model. So, I define VGG-16 Architecture like this:
...ANSWER
Answered 2018-Mar-04 at 13:14In my opinion, weights_list only includes layers which contains weights, and normally it only has 16 layers because VGG16 has 16 layers which contain weights . But model.layers ranges from 0 to N, here N is larger than 16 since model.layers includes layers which contains no weights, such as relu layer,padding_layer, and max_pooling layer, so on.
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Install caffe_weight_converter
You can use caffe_weight_converter like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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