sanjay-29-29 / yolov5_object_detection

YOLOv5 Object Detection

This repository contains a Python script for performing object detection using the YOLOv5 model. It captures video frames from a webcam and overlays bounding boxes on detected objects, counting the number of detections for a specific class and displaying an alert message if a threshold is met.

Prerequisites

Before running the code, ensure you have the following dependencies installed:

• Python 3.x
• OpenCV (opencv-python)
• PyTorch (torch)
• NumPy (numpy)

Installation

1. Clone or download this repository to your local machine.

git clone https://github.com/PattasuBalu/yolo_object_detection.git

2. Navigate to the cloned repository folder:

cd yolo_object_detection

3. Install the required packages by running:

pip install -r requirements.txt

4. Open the Python script alerting_and_count.py and make the following adjustments:

   • Update the weights_path variable to point to the location of your custom YOLOv5 model weights.(mostly a .pt file)
   • Ensure your webcam is accessible via camera index 0, or change the index if needed.

5. Save the script and run it using:

python alerting_and_count.py