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149 lines
4.5 KiB
149 lines
4.5 KiB
import cv2
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import numpy as np
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# 全局变量
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points = [] # 存储选择的四个点
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img = None # 存储原始图像
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img_copy = None # 用于绘制的图像副本
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def mouse_callback(event, x, y, flags, param):
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"""鼠标回调函数，用于选择四个点"""
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global img_copy, points
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if event == cv2.EVENT_LBUTTONDOWN:
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if len(points) < 4:
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points.append((x, y))
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print(f"已选择点 {len(points)}: ({x}, {y})")
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# 在图像上绘制点
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cv2.circle(img_copy, (x, y), 5, (0, 255, 0), -1)
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# 如果已经选择了4个点，绘制连线
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if len(points) == 4:
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# 按照上、右、下、左的顺序连接点
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for i in range(4):
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cv2.line(img_copy, points[i], points[(i + 1) % 4], (0, 255, 0), 2)
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# 标记每个点的位置
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cv2.putText(img_copy, "Top", points[0], cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
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cv2.putText(img_copy, "Right", points[1], cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
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cv2.putText(img_copy, "Bottom", points[2], cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
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cv2.putText(img_copy, "Left", points[3], cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
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cv2.imshow("Select Points", img_copy)
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def perspective_transform(image, src_points):
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"""执行透视变换"""
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# 将点排序为上、右、下、左
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top, right, bottom, left = src_points
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# 计算新图像的宽度（取左右边的最大值）
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width_a = np.linalg.norm(np.array(right) - np.array(left))
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width_b = np.linalg.norm(np.array(top) - np.array(bottom))
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max_width = max(int(width_a), int(width_b))
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# 计算新图像的高度（取上下边的最大值）
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height_a = np.linalg.norm(np.array(bottom) - np.array(top))
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height_b = np.linalg.norm(np.array(right) - np.array(left))
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max_height = max(int(height_a), int(height_b))
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# 定义目标点
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dst = np.array([
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[0, 0], # 左上角
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[max_width - 1, 0], # 右上角
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[max_width - 1, max_height - 1], # 右下角
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[0, max_height - 1] # 左下角
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], dtype="float32")
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# 转换源点数组为numpy数组
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src = np.array([top, right, bottom, left], dtype="float32")
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# 计算透视变换矩阵
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M = cv2.getPerspectiveTransform(src, dst)
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# 执行透视变换
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warped = cv2.warpPerspective(image, M, (max_width, max_height))
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return warped
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def k_perspective_transform(image, src_points):
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"""执行透视变换"""
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# 将点排序为上、右、下、左
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top, right, bottom, left = src_points
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# 计算新图像的宽度（取左右边的最大值）
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sub_zy = np.array(right) - np.array(left)
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sub_sx = np.array(top) - np.array(bottom)
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sub_x=sub_sx[0]/2
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print("x差值",sub_sx[0])
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sub_y = sub_zy[1] / 2
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print("y差值", sub_sx[0])
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# 定义目标点
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dst = np.array([
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[top[0]-sub_x, top[1]], # 左上角
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[right[0], right[1]- sub_y], # 左上角
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[bottom[0]+sub_x, bottom[1]], # 左上角
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[left[0] , left[1]+ sub_y], # 左上角
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], dtype="float32")
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# 转换源点数组为numpy数组
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src = np.array([top, right, bottom, left], dtype="float32")
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# 计算透视变换矩阵
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M = cv2.getPerspectiveTransform(src, dst)
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print(f"矩阵M={M}")
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# 执行透视变换
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warped = cv2.warpPerspective(image, M, (1050, 900))
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return warped
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def main():
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global img, img_copy, points
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# 读取图像
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img = cv2.imread("images/trans/subRawImg.jpg")
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if img is None:
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print("无法加载图像，请检查路径是否正确")
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return
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img_copy = img.copy()
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# 创建窗口并设置鼠标回调
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cv2.namedWindow("Select Points")
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cv2.setMouseCallback("Select Points", mouse_callback)
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print("请按顺序点击选择四个点：上、右、下、左")
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print("选择完成后按任意键继续...")
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while True:
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cv2.imshow("Select Points", img_copy)
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key = cv2.waitKey(1) & 0xFF
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# 如果已经选择了4个点，按任意键继续
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if len(points) == 4:
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break
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# 执行透视变换
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warped = k_perspective_transform(img, points)
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# 显示结果
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cv2.imshow("Original Image", img)
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cv2.imshow("Transformed", warped)
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output_path="images/trans/_4point.jpg"
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cv2.imwrite(output_path, warped)
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print(f"图像已保存到 {output_path}")
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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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