CNN to classify animal pictures from the Animal-10 dataset
This project is about testing a CNN on the Animal-10 dataset, which contains 28K medium quality image of ten animals : squirrel, hen, horse, butterfly, dog, cat, cow, spider, sheep and elephant. The pictures have been all downloaded from google so they have different sizes. I will test a multilayered CNN to try and categorize the pictures, after having processed the images and done the essential transformations. And after the training phase I will go on to test my model of a test set it has never seen before. I'm hoping for an accuracy of about 80%.
- Preprocess the data to make it machine learning ready
- Build a CNN with enough layers to identify the differences between the images
- Train and test the model and get the accuracy
- Importing libraries
- The dataset
- Image processing
- Some visualization
- Building the classifier
- Training the model
- Testing the model
- Conclusion
- Pandas
- Numpy
- Torchvision
- Matplotlib
- Glob
- CV2