71 lines
2.3 KiB
Python
71 lines
2.3 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import cv2
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import numpy as np
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import os
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import argparse
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def analyze_sky_ratio(image_path, threshold=200, debug=False):
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"""
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分析图片中白色天空占整个图片的比例
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参数:
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image_path: 图片路径
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threshold: 灰度阈值，用于区分天空和非天空区域，默认为200（较亮的像素）
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debug: 是否显示处理过程中的图像，用于调试
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返回:
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sky_ratio: 天空占比（0-1之间的浮点数）
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"""
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# 读取图片
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img = cv2.imread(image_path)
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if img is None:
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raise ValueError(f"无法读取图片: {image_path}")
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# 转换为灰度图
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# 使用阈值分割天空区域（天空通常是图像中较亮的部分）
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_, sky_mask = cv2.threshold(gray, threshold, 255, cv2.THRESH_BINARY)
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# 计算天空区域占比
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total_pixels = gray.shape[0] * gray.shape[1]
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sky_pixels = np.sum(sky_mask == 255)
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sky_ratio = sky_pixels / total_pixels
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# 调试模式：显示处理过程图像
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if debug:
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# 创建可视化结果
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# 原图
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cv2.imshow('Original Image', img)
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# 灰度图
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cv2.imshow('Grayscale Image', gray)
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# 天空掩码
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cv2.imshow('Sky Mask', sky_mask)
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# 在原图上标记天空区域
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result = img.copy()
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result[sky_mask == 255] = [0, 255, 255] # 用黄色标记天空区域
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cv2.imshow('Sky Detection Result', result)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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return sky_ratio
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def main():
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parser = argparse.ArgumentParser(description='分析图片中天空区域占比')
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parser.add_argument('image_path', help='图片路径')
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parser.add_argument('--threshold', type=int, default=200, help='天空区域的灰度阈值（0-255），默认为200')
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parser.add_argument('--debug', action='store_true', help='显示处理过程图像')
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args = parser.parse_args()
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try:
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sky_ratio = analyze_sky_ratio(args.image_path, args.threshold, args.debug)
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print(f"天空区域占比: {sky_ratio:.2%}")
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except Exception as e:
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print(f"错误: {e}")
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if __name__ == "__main__":
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main()
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