A CNN trained to determine the dog breed based on the face provided in an image
It's the Convolutional Neural Network(CNN) project in the Deep Learning Nanodegree program of Udacity. I learned 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, my algorithm identifies an estimate of the dog's breed. If supplied an image of a human, the code identifies the resembling dog breed.
- Clone the repository and navigate to the downloaded folder.
git clone https://github.com/ayowolet/Dog-breed-Classifier.git cd Dog-breed-Classifier
- Open the
Dog-breed Classifier.ipynb
file. The HTML version of the file is available.jupyter notebook Dog-breed Classifier.ipynb
- Read and follow the instructions! This repository doesn't include any dataset you need. You can check out the notebook to download them.
- Intro
- Step 0: Import Datasets
- Step 1: Detect Humans
- Step 2: Detect Dog
- Step 3: Create a CNN to Classify Dog Breeds (from Scratch)
- Step 4: Create a CNN to Classify Dog Breeds (using Transfer Learning)
- Step 5: Write Your Algorithm
- Step 6: Test Your Algorithm