dog_breed_recognizer | Convolutional Neural Networks project in the AI
kandi X-RAY | dog_breed_recognizer Summary
kandi X-RAY | dog_breed_recognizer Summary
dog_breed_recognizer is a Jupyter Notebook library. dog_breed_recognizer has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.
Welcome to the Convolutional Neural Networks (CNN) project in the AI Nanodegree! In this project, you will learn how to build a pipeline that can be used within a web or mobile app to process real-world, user-supplied images. Given an image of a dog, your algorithm will identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed.
Welcome to the Convolutional Neural Networks (CNN) project in the AI Nanodegree! In this project, you will learn how to build a pipeline that can be used within a web or mobile app to process real-world, user-supplied images. Given an image of a dog, your algorithm will identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed.
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dog_breed_recognizer 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.
dog_breed_recognizer has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of dog_breed_recognizer is current.
Quality
dog_breed_recognizer has no bugs reported.
Security
dog_breed_recognizer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
dog_breed_recognizer does not have a standard license declared.
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Without a license, all rights are reserved, and you cannot use the library in your applications.
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dog_breed_recognizer releases are not available. You will need to build from source code and install.
Installation instructions are not available. Examples and code snippets are available.
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dog_breed_recognizer Key Features
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dog_breed_recognizer Examples and Code Snippets
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