caffe_basic_image_classifier_example | This is a basic image classification example in Caffe
kandi X-RAY | caffe_basic_image_classifier_example Summary
kandi X-RAY | caffe_basic_image_classifier_example Summary
caffe_basic_image_classifier_example is a Python library. caffe_basic_image_classifier_example has no bugs, it has no vulnerabilities and it has low support. However caffe_basic_image_classifier_example build file is not available. You can download it from GitHub.
This is a basic image classification example in Caffe (under Linux), using C++. The example is provided for instructional purposes. The main code is minimalistic, and requires only basic linux utilities and the development environment necessary to compile the Caffe library.
This is a basic image classification example in Caffe (under Linux), using C++. The example is provided for instructional purposes. The main code is minimalistic, and requires only basic linux utilities and the development environment necessary to compile the Caffe library.
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caffe_basic_image_classifier_example has a low active ecosystem.
It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
caffe_basic_image_classifier_example has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of caffe_basic_image_classifier_example is current.
Quality
caffe_basic_image_classifier_example has no bugs reported.
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caffe_basic_image_classifier_example has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
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caffe_basic_image_classifier_example does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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caffe_basic_image_classifier_example releases are not available. You will need to build from source code and install.
caffe_basic_image_classifier_example has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions, examples and code snippets are available.
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Install caffe_basic_image_classifier_example
Compile Caffe under some directory (CAFFEROOT) following the instructions in http://caffe.berkeleyvision.org/installation.html. Note that you don't need root priviledges to perform this step. CAFFEROOT can be something like ~/caffe. Also, you don't need a full-fledged installation. For instance, the GPU support and the python interface are not crucial.
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