caffe_weight_converter | Can also export weights | Machine Learning library

 by   pierluigiferrari Python Version: Current License: GPL-3.0

kandi X-RAY | caffe_weight_converter Summary

kandi X-RAY | caffe_weight_converter Summary

caffe_weight_converter is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras applications. caffe_weight_converter has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However caffe_weight_converter build file is not available. You can download it from GitHub.

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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            kandi-support Support

              caffe_weight_converter has a low active ecosystem.
              It has 63 star(s) with 22 fork(s). There are 4 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 10 open issues and 6 have been closed. On average issues are closed in 2 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of caffe_weight_converter is current.

            kandi-Quality Quality

              caffe_weight_converter has no bugs reported.

            kandi-Security Security

              caffe_weight_converter has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              caffe_weight_converter is licensed under the GPL-3.0 License. This license is Strong Copyleft.
              Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

            kandi-Reuse Reuse

              caffe_weight_converter releases are not available. You will need to build from source code and install.
              caffe_weight_converter has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed caffe_weight_converter and discovered the below as its top functions. This is intended to give you an instant insight into caffe_weight_converter implemented functionality, and help decide if they suit your requirements.
            • Convert a caffe model to keras
            • Convert a Caffe file to a dictionary
            • Convert a caffe net file to a dictionary
            Get all kandi verified functions for this library.

            caffe_weight_converter Key Features

            No Key Features are available at this moment for caffe_weight_converter.

            caffe_weight_converter Examples and Code Snippets

            No Code Snippets are available at this moment for caffe_weight_converter.

            Community Discussions

            QUESTION

            How to Implement CaffeNet on Keras with pretrained weight from Caffe
            Asked 2019-Jan-16 at 09:42

            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 13:26

            I've tried to implement the lower part of CaffeNet(LRN layer omitted):

            Source https://stackoverflow.com/questions/54056857

            QUESTION

            Converting a .caffemodel to keras h5
            Asked 2018-Mar-04 at 13:14

            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:

            IMDB-Wiki

            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 13:14

            In 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.

            Source https://stackoverflow.com/questions/48598162

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install caffe_weight_converter

            You can download it from GitHub.
            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.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            https://github.com/pierluigiferrari/caffe_weight_converter.git

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            gh repo clone pierluigiferrari/caffe_weight_converter

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            git@github.com:pierluigiferrari/caffe_weight_converter.git

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