YOLOv7Detector 0.0.4

A simple Wrapper for YOLOv7

An unofficial wrapper of the yolov7 project.

It is very simple, and has only one function: calculateDetections(). Currently it only supports images, on CPU.

Installation

The package is hosted on pypi, so you can install it with pip:

pip install YOLOv7Detector

Usage

You must download a model from the yolov7 project page, and place it in the root directory of this project. Then you can use the following code to run inference on an image:

from YOLOv7Detector import Detector as det
from PIL import Image


def main():
    # Initialize the YOLO inference object
    detector = det(weights_path='yolov7.pt', conf_thres=0.7, iou_thres=0.45, img_size=640)

    # Load the image
    image = Image.open('test_images/test_4.jpg')

    download_path = 'test_images/test_4_result.jpg'  # Leave as None if not needed

    dets = detector.calculateDetections(image, view_img=True, download_path=download_path)

    print(dets)


if __name__ == '__main__':
    main()

This returns a list of dictionaries, each dictionary is formatted as follows:

{
    'class': 'person', 
    'confidence': 0.966009259223938, 
    'bbox': [31.0, 144.0, 469.0, 653.0]
}

where bbox is a list of [x1, y1, x2, y2] coordinates of the bounding box. With view_img=True, the image with bounding boxes will be displayed as such: