Coding-图像处理-在图片上显示矩形框

• 显示矩形框

显示矩形框

import cv2

def draw_boxes_on_image(image_path, label_path, class_dict, output_path=None):
    """
    Reads an image and its corresponding YOLO format label file, then draws the boxes on the image.
    
    :param image_path: Path to the image file.
    :param label_path: Path to the YOLO format label file.
    :param class_dict: Dictionary mapping class names to their ids.
    :param output_path: Optional path to save the annotated image.
    :return: Annotated image as numpy array.
    """
    # Load the image
    image = cv2.imread(image_path)
    height, width, _ = image.shape
    
    # Read the label file
    with open(label_path, 'r') as f:
        lines = f.readlines()
    
    # Draw boxes for each object in the label file
    for line in lines:
        parts = line.strip().split()
        class_id = int(parts[0])
        x_center, y_center, box_width, box_height = map(float, parts[1:])
        
        # Convert normalized coordinates back to pixel values
        x_min = int((x_center - box_width / 2) * width)
        y_min = int((y_center - box_height / 2) * height)
        x_max = int((x_center + box_width / 2) * width)
        y_max = int((y_center + box_height / 2) * height)
        
        # Get the class name
        class_name = next(key for key, value in class_dict.items() if value == class_id)
        
        # Draw the bounding box
        cv2.rectangle(image, (x_min, y_min), (x_max, y_max), (0, 255, 0), 2)
        
        # Add the class name on top of the box
        cv2.putText(image, class_name, (x_min, y_min - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
    
    # Optionally save the image
    if output_path is not None:
        cv2.imwrite(output_path, image)
    
    return image

# Example usage:
class_dict = {'dog': 0, 'cat': 1}
image_path = 'jpg\\1.jpg'
label_path = 'txt\\1.txt'
output_path = 'annotated_image.jpg'
annotated_image = draw_boxes_on_image(image_path, label_path, class_dict, output_path)