This project implements a Convolutional Neural Network (CNN) for detecting rats in images. The model is trained using a dataset of images containing rats and images without rats.

• dataset/: Contains the training data for the model.

  • rat/: Folder with images of rats for training.
  • no_rat/: Folder with images without rats for training.

• testing_folder/: Contains sample images used for testing the trained model.

  • test_image.jpeg: A sample image for testing the model's predictions.

• model/: Stores the trained CNN model.

  • rat_cnn_model.h5: The file where the trained model is saved.

• rat_detection.ipynb: A Jupyter notebook that includes:

  • Code for training the CNN model.
  • Evaluation of the model's performance.
  • Making predictions on new images.

1. Clone the repository:

   git clone <repository-url> 

2. Navigate to the project directory:

   cd Rat_Detection_CNN 

3. Install the required packages:

   pip install -r requirements.txt 

1. Open the rat_detection.ipynb notebook in Jupyter.
2. Follow the instructions in the notebook to train the model and evaluate its performance.
3. Use the trained model to make predictions on new images.

This project is licensed under the MIT License.