moaaz12-web / cattle-detection-using-yolov8 Goto Github PK

Clone the repository:

git clone https://github.com/moaaz12-web/Cattle-detection-.git
cd cattle-image-recognition

Install dependencies:

pip install -r requirements.txt

Download weights for Alexnet:

Before running the application, download the AlexNet model weights from the drive link and place it in the working directory
https://drive.google.com/file/d/1PnKTyFy9yBtaossFSwrRGsb5S6CPVhEK/view?usp=sharing

Run the application:

python tk.py

Upload an image through the interface, and witness the advanced image processing workflow:

• The user-uploaded image undergoes a series of processing functions.
• The processed image is sent to the AlexNet model, providing a string output indicating the presence of a cow in the image.
• Subsequently, the image is forwarded to the YOLOv8 model, specifically trained on a cattle dataset.
• YOLOv8 counts the number of cattle in the image and overlays bounding boxes to visually indicate their locations.
• The entire process is seamlessly displayed on the Tkinter interface, offering a comprehensive and interactive user experience.