/Pre-trained-Image-Classifier-to-Identify-Dog-Breeds

Project 1 as part of Udacity's `AI Programming with Python` Nanodegree.

Primary LanguagePython

Language

Pre-trained-Image-Classifier-to-Identify-Dog-Breeds 🐶

Objectif

  • Improving programming skills using Python.

  • Identifying which pet images are of dogs and which pet images aren't of dogs.

  • Classifying the breeds of dogs, for the images that are of dogs.

To complete the project, our results must be the same as the Project results from Udacity show below

Given our results, the best model architecture is VGG. It outperformed both of the other architectures when considering both objectives 1 and 2. You will notice that ResNet did classify dog breeds better than AlexNet, but only VGG and AlexNet were able to classify dogs and not-a-dog at $100$% accuracy. The model VGG was the one that was able to classify dogs and not-a-dog with $100$% accuracy and had the best performance regarding breed classification with $93.3$% accuracy.

My Results

At the end of each file you can see different percentage