Car-Model-Recognition | Car Model Recognition project | Machine Learning library

 by   Helias Python Version: Current License: No License

kandi X-RAY | Car-Model-Recognition Summary

kandi X-RAY | Car-Model-Recognition Summary

Car-Model-Recognition is a Python library typically used in Manufacturing, Utilities, Machinery, Process, Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. Car-Model-Recognition has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

This is a university project for the course "Computer Vision". This project consists in a classifier of car model.
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            kandi-support Support

              Car-Model-Recognition has a low active ecosystem.
              It has 60 star(s) with 19 fork(s). There are 4 watchers for this library.
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              It had no major release in the last 6 months.
              There are 0 open issues and 6 have been closed. On average issues are closed in 19 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of Car-Model-Recognition is current.

            kandi-Quality Quality

              Car-Model-Recognition has 0 bugs and 0 code smells.

            kandi-Security Security

              Car-Model-Recognition has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              Car-Model-Recognition code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              Car-Model-Recognition does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              Car-Model-Recognition releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed Car-Model-Recognition and discovered the below as its top functions. This is intended to give you an instant insight into Car-Model-Recognition implemented functionality, and help decide if they suit your requirements.
            • Train a model iteratively
            • Train a model
            • Test the model
            • Plots training and test loss
            • Write the confusion matrix
            • Prepare data for training
            • Get class by index
            Get all kandi verified functions for this library.

            Car-Model-Recognition Key Features

            No Key Features are available at this moment for Car-Model-Recognition.

            Car-Model-Recognition Examples and Code Snippets

            No Code Snippets are available at this moment for Car-Model-Recognition.

            Community Discussions

            QUESTION

            Use multiple GPUs on Pytorch
            Asked 2020-May-28 at 00:50

            I have two GPUs, and both of them are CUDA devices, but I don't know, how to use both of them to train my resnext model: link for a github repository, which I took as a base code for my project. The only important thing I've changed is this:

            ...

            ANSWER

            Answered 2020-May-28 at 00:50

            QUESTION

            How to fix multiprocessing problems in python in windows10
            Asked 2020-Feb-17 at 18:08

            I try to use this tutorial to train my own car model recognition model: https://github.com/Helias/Car-Model-Recognition. And i want to use coda and my gpu perfomance to enhance training speed (preprocesssing step was completed without any errors).But when I try to train my model, I've got the following errors:

            ...

            ANSWER

            Answered 2020-Feb-17 at 18:08

            Looking at main.py, you run a lot of code at the module level. On Windows, python's multiprocessing module will start a new python interpreter, import your modules, unpickle a snapshot of your parent context and then call your worker function. The problem is that all of that module level code executes merely by import and you essentially run a new copy of your program instead of building a context for your worker.

            The solution is two-fold. First, move all of the module level code into functions. You want to be a able to import your module without side effects. Second, call the function(s) that start your program from a conditional

            Source https://stackoverflow.com/questions/60266256

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

            Vulnerabilities

            No vulnerabilities reported

            Install Car-Model-Recognition

            I suggest to use VMMRdb as dataset, it's free and full of labelled images for car model recognition instead of detection (the most dataset is for this). So download the dataset, select some models and put the directory model in the dataset folder, any directory in "dataset" will be considered a new class.
            Stanford Cars Dataset from jkrause (low images quantity)
            Comprehensive Cars Database, here the module to get this dataset MODULE

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            gh repo clone Helias/Car-Model-Recognition

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