Animals_Classification

This project is dependent to make classification between faces of cats, dogs and wild_animals and use multiple model such as CNN and pretrained model like ResNet and MobileNet and show the result of all model in the image using heatmap to know what is the part that model take decision when see it.

What is the option of Model if you have classification problem?

To make classification problem can train alot of data using CNN or updata of CNN such as Fast and Faster CNN or the last obtion use pretrained model such as MobileNet and ResNet in this repository we try to compare between most of model that i talk about to know what is the best model to this problem.

Can show what is the part of data that make you take decision? and Why if yes?

Yes, can explain what is the specific part of the image that make the model take this decision that like Saliency Map OR Heatmap and i am useing both of them in this repositoty to explain why choose cat, dog or wild animals.

What you will learn before this repo?

1. You will learn how to read image dataset.
2. How to make image_data_generator?
3. How to build CNN Model?
4. How to train and validation CNN Model?
5. Deal with using pretrained Model such as MobileNet and ResNet.
6. Testing all this models separate.
7. Make Saliency Map to know the reason of take decision to all Models.
8. Make Heatmap to show the defference between models dependent in accuracy of model.

In the last, I hope that my repository can be helpfully to you that's it.