https://github.com/zainlatif/rat_detection_cnn_image
🐭 rat detection using cnn this beginner-level computer vision project uses a convolutional neural network (cnn) to classify images as containing a rat or not. built in jupyter notebook with tensorflow and keras, it uses a pre-trained dataset and allows you to test custom images by placing them in a testing_folder.
https://github.com/zainlatif/rat_detection_cnn_image
animal-detection cnn deep-learning jupyter-notebook object-detection python rat-detection tensorflow
Last synced: 2 months ago
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🐭 rat detection using cnn this beginner-level computer vision project uses a convolutional neural network (cnn) to classify images as containing a rat or not. built in jupyter notebook with tensorflow and keras, it uses a pre-trained dataset and allows you to test custom images by placing them in a testing_folder.
- Host: GitHub
- URL: https://github.com/zainlatif/rat_detection_cnn_image
- Owner: zainlatif
- Created: 2025-05-31T11:57:35.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-21T05:51:40.000Z (about 1 year ago)
- Last Synced: 2025-06-21T06:29:55.406Z (about 1 year ago)
- Topics: animal-detection, cnn, deep-learning, jupyter-notebook, object-detection, python, rat-detection, tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 90.4 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Rat Detection CNN
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.
## Project Structure
- `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.
## Setup Instructions
1. Clone the repository:
```
git clone
```
2. Navigate to the project directory:
```
cd Rat_Detection_CNN
```
3. Install the required packages:
```
pip install -r requirements.txt
```
## Usage
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.
## License
This project is licensed under the MIT License.