Udacity-Use-a-Pre-trained-Image-Classifier-to-Identify-Dog-Breeds

Overview

This project utilizes a pre-trained image classifier to identify dog breeds. It is part of the Udacity Nanodegree program. The classifier can take an image of a dog and predict its breed or determine if a human in the image resembles a particular dog breed.

Project Structure

The repository contains the following folders and files:

• Folders:

  • Picture for readme file: Contains images for the README file.
  • __pycache__: Contains compiled Python files.
  • pet_images: Contains images of dogs for the project.
  • uploaded_images: Contains images uploaded for classification.

• Files:

  • LICENSE: The MIT license file.
  • README.md: This readme file.
  • adjust_results4_isadog.py: Script to adjust results for is-a-dog determination.
  • adjust_results4_isadog_hints.py: Hints for adjust_results4_isadog.py.
  • calculates_results_stats.py: Script to calculate statistics of results.
  • calculates_results_stats_hints.py: Hints for calculates_results_stats.py.

Installation

1. Clone the repository:

   git clone https://github.com/niloydebbarma-code/Udacity-Use-a-Pre-trained-Image-Classifier-to-Identify-Dog-Breeds.git
   cd Udacity-Use-a-Pre-trained-Image-Classifier-to-Identify-Dog-Breeds

License

This project is licensed under the MIT License. For more details, see the LICENSE file.

Acknowledgments

• Udacity for providing the project guidelines and resources.
• The developers of the libraries and tools used in this project.

Contact

For any questions or comments, please contact Niloy Deb Barma at LinkedIn.