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62 lines
1.8 KiB
62 lines
1.8 KiB
import cv2
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import numpy as np
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import 标靶识别 as ie
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def perspective_transformation(image):
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if image is None:
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print("Error: Unable to load image.")
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exit()
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# 定义源图像中的四个点
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src_points = np.float32([
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[4, 16], # 左上角
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[795, 14], # 右上角
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[1027, 736], # 右下角
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[181, 856] # 左下角
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])
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# 定义目标图像中的四个点 # 1050 * 900
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dst_points = np.float32([
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[4, 16], # 左上角
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[795, 14], # 右上角
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[795, 850], # 右下角
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[4, 850] # 左下角
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])
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# 计算透视变换矩阵
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M = cv2.getPerspectiveTransform(src_points, dst_points)
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print(f"原矩阵={M}")
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# 逆矩阵
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inverse_matrix = np.linalg.inv(M)
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print(f"逆矩阵={inverse_matrix}")
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# 应用透视变换
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transformed_image = cv2.warpPerspective(image, M, (1050, 900))
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# 应用透视变换
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inv_transformed_image = cv2.warpPerspective(transformed_image, inverse_matrix, (1050, 900))
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# 显示原始图像和变换后的图像
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cv2.imshow("Original Image", image)
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cv2.imshow("Trans Image", transformed_image)
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cv2.imshow("iTrans Image", inv_transformed_image)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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def sub_img():
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# 读取图像
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image = cv2.imread("images/target/need_trans.jpg")
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if image is None:
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print("Error: Unable to load image.")
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exit()
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# 1050 * 900
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startPoint = [550, 700]
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endPoint = [1600, 1600]
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# 绘制标靶区域
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# 检测
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subImg = ie.extract_sub_image(image, startPoint, endPoint)
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# cv2.imshow("subImg", subImg)
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# cv2.waitKey(0)
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# cv2.destroyAllWindows()
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return subImg
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if __name__ == '__main__':
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img=sub_img()
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perspective_transformation(img)
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