These python codes are a part of the project "Object Detection and Classification" of our Minor Project. They can be used for reference for any upcoming projects

--> Human_face_dog_breed_classification.py
This code can do multiple tasks like

1. Differntiate between a human face and a dog image.
2. Create a bounding box around the face detected.
3. Classify dogs into 133 trained breeds.

--> cat_vs_dog.py The code is for the classification of images of Dog and Cat. The code was run on Goolge Colab. The dataset can be found here. https://www.kaggle.com/c/dogs-vs-cats/data

Various CNN architectures like VGG16, VGG19, Inception, Exception, Resnet50 are used.

--> dog_breed.py This code uses pretrained Resnet50 Model to classify breeds of dog.

-->face_detection_webcam

The real time face and eyes detection through webcam is implemented in this code. xml files can be found here https://github.com/opencv/opencv/tree/master/data/haarcascades.

--> image_predict.py Add https://github.com/OlafenwaMoses/ImageAI/releases/download/1.0/DenseNet-BC-121-32.h5 for h5 data. This is the trained model which helps to apply its learnt algorithm to new image.