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Udacity Self-Driving Car Engineer Nanodegree. Project: Build a Traffic Sign Recognition Classifier

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saadhaxxan/Street-Signs-and-boards-classification-using-DCNN

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Street-Signs-and-boards-classification-using-DCNN

Build Status Open Source Love svg1 GitHub Forks GitHub Issues contributions welcome

Requirements

Type below command in cmd to get up and running with the dependencies of the file.

pip install -r requirement.txt

Usage

https://colab.research.google.com/drive/1KvnE8zTiYm6Ue2mE5gUzFMPZsFA53LeC

The link above refers to the colab runtime file of this project you can either access that through here or you can create your own by just going at https://colab.research.google.com. This project uses a deep convolutional neural network to classify images of 43 different classes. This project classify street symbols and signs. The dataset used in the project is open source and available on bitbucket to download.Here is the link of the dataset https://bitbucket.org/jadslim/german-traffic-signs/src/master/. ipython notebook along with the py file of this project is available. You can add new layers to the model to make it robust and also play around with the parameters of each layer to get more better results. You can also add more images to the project so that it has larger data to learn.

Author

You can get in touch with me on my LinkedIn Profile:

Saad Hassan

LinkedIn Link

You can also follow my GitHub Profile to stay updated about my latest projects: GitHub Follow

If you liked the repo then kindly support it by giving it a star ⭐!

Contributions Welcome

forthebadge

If you find any bug in the code or have any improvements in mind then feel free to generate a pull request.

Issues

GitHub Issues

If you face any issue, you can create a new issue in the Issues Tab and I will be glad to help you out.

License

MIT

Copyright (c) 2019 SAAD HASSAN

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Udacity Self-Driving Car Engineer Nanodegree. Project: Build a Traffic Sign Recognition Classifier

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