105 lines
2.2 KiB
Python
105 lines
2.2 KiB
Python
import cv2
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import numpy as np
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# ========================
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# 配置
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# ========================
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IMAGE_PATH = "22.png"
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CANNY_LOW = 60
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CANNY_HIGH = 150
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# 判定“近似水平”的阈值
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MAX_SLOPE = 0.2 # |dy/dx| < 0.2 认为是水平
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# ========================
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def main():
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img = cv2.imread(IMAGE_PATH)
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if img is None:
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raise RuntimeError("图片读取失败")
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h, w = img.shape[:2]
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# 1. 灰度
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# 2. 模糊（非常关键，压制粗糙纹理）
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blur = cv2.GaussianBlur(gray, (7, 7), 0)
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# 3. Canny
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edges = cv2.Canny(blur, CANNY_LOW, CANNY_HIGH)
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# 4. 找轮廓（只用来拿点）
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contours, _ = cv2.findContours(
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edges, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE
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)
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horizontal_points = []
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# 5. 筛选“近似水平”的边缘点
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for cnt in contours:
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if len(cnt) < 50:
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continue
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pts = cnt.squeeze()
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if pts.ndim != 2:
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continue
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x = pts[:, 0]
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y = pts[:, 1]
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dx = x.max() - x.min()
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dy = y.max() - y.min()
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if dx < 100: # 太短的不要
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continue
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slope = dy / (dx + 1e-6)
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if slope < MAX_SLOPE:
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horizontal_points.append(pts)
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if not horizontal_points:
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print("❌ 没找到合适的水平边")
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return
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# 6. 合并所有候选点
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all_pts = np.vstack(horizontal_points)
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# 7. 选“最靠上的那一条”
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# 方法：按 y 排序，取 y 最小的一部分
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all_pts = all_pts[all_pts[:, 1].argsort()]
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# 取前 20% 作为“上沿候选”
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top_n = int(len(all_pts) * 0.2)
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top_edge_pts = all_pts[:top_n]
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# 8. 用最小二乘拟合直线 y = ax + b
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xs = top_edge_pts[:, 0]
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ys = top_edge_pts[:, 1]
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a, b = np.polyfit(xs, ys, 1)
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# 9. 画线
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x0, x1 = 0, w - 1
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y0 = int(a * x0 + b)
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y1 = int(a * x1 + b)
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vis = img.copy()
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cv2.line(vis, (x0, y0), (x1, y1), (0, 0, 255), 2)
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# 可视化点
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for p in top_edge_pts[::20]:
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cv2.circle(vis, tuple(p), 1, (0, 255, 0), -1)
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cv2.imshow("edges", edges)
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cv2.imshow("top plate edge", vis)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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if __name__ == "__main__":
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main()
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