76 lines
2.2 KiB
Python
76 lines
2.2 KiB
Python
import cv2
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import numpy as np
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def extract_green_polygons(image_path):
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# 1. 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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print("无法读取图片")
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return []
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# 获取图片尺寸
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height, width = img.shape[:2]
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# 定义目标坐标系范围
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target_w, target_h = 1465, 715
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# 2. 转换颜色空间到 HSV 以便提取绿色
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hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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# 定义绿色的 HSV 范围
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lower_green = np.array([35, 20, 200])
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upper_green = np.array([85, 255, 255])
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# 3. 创建掩膜 (Mask)
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mask = cv2.inRange(hsv, lower_green, upper_green)
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# 4. 图像形态学处理
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kernel = np.ones((3,3), np.uint8)
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mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
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mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
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# 5. 查找轮廓
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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polygons = []
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for i, contour in enumerate(contours):
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# 过滤掉太小的区域
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if cv2.contourArea(contour) < 100:
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continue
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points = []
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# 6. 坐标转换
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for point in contour:
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px, py = point[0]
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# 【修改点1】：这里显式转换成 float()，去除 numpy 类型包裹
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# X 轴转换: 线性缩放
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new_x = float((px / width) * target_w)
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# Y 轴转换: 图像坐标系 -> 笛卡尔坐标系
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new_y = float(((height - py) / height) * target_h)
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# 保留两位小数
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points.append((round(new_x, 2), round(new_y, 2)))
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polygons.append({
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"id": i,
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"vertex_count": len(points),
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"coordinates": points
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})
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return polygons
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# --- 使用说明 ---
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results = extract_green_polygons("golden_gate_bridge.png")
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if not results:
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print("未找到多边形或图片读取失败")
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else:
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for poly in results:
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print(f"--- 多边形 ID: {poly['id']} (顶点数: {poly['vertex_count']}) ---")
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# 【修改点2】：遍历坐标列表，每行输出两个数字 (x y)
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for x, y in poly['coordinates']:
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print(f"{x}, {y}")
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print("") # 每个多边形之间空一行，方便区分 |