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import numpy as np
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import matplotlib.pyplot as plt
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import calc_way
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import get_data
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import calc_slope_line
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import cv2
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import model
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model = model.Model()
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alpha = model.alpha
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beta = model.beta
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img_path = r'C:\Users\Administrator\Desktop\BYD\20250520\frame__9600_2_yolo.jpg'
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txt_name = "C:\\Users\\Administrator\\Desktop\\BYD\\20250520\\frame_9600_2.jpg_zuobiao.txt"
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output_image = "9600_2.jpg"
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x_bot, y_bot, x_top, y_top = get_data.get_data(txt_name)
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x_bot = np.array(x_bot)
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y_bot = np.array(y_bot)
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x_top = np.array(x_top)
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y_top = np.array(y_top)
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slope_top, intercept_top ,r2 = calc_slope_line.linear_regression(x_top,y_top)
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x_zero, y_zero = calc_way.calc_zeros()
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x_zero = np.array(x_zero)
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y_zero = np.array(y_zero)
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slope_zero, intercept_zero,r2_zero = calc_slope_line.linear_regression(x_zero,y_zero)
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# 绘制原始数据
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plt.scatter(x_zero,y_zero, color='blue', label='orgin')
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# 绘制拟合线
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y_pred = slope_zero * x_zero + intercept_zero
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plt.plot(x_zero, y_pred, color='red', label='fix')
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plt.xlabel('X')
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plt.ylabel('Y')
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plt.legend()
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plt.show()
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# # 绘制原始数据
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# plt.scatter(x_top,y_top, color='blue', label='orgin')
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#
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# # 绘制拟合线
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# y_pred = slope_top * x_top + intercept_top
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# plt.plot(x_top, y_pred, color='red', label='fix')
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#
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# plt.xlabel('X')
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# plt.ylabel('Y')
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# plt.legend()
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# plt.show()
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# 1. 读取图像（替换为你的图片路径）
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image = cv2.imread(img_path) # 默认读取BGR格式
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# 检查图像是否成功加载
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if image is None:
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print("Error: 无法读取图像，请检查路径！")
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exit()
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point1 = (int(x_zero[0]), int(960-y_zero[0]))
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point2 = (int(x_zero[-1]), int(960-y_zero[-1]))
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cv2.line(image, point1, point2, (0, 255, 0), 1)
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Z = 0
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for i in range(len(x_bot)):
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k = calc_slope_line.get_k(alpha,beta,x_bot[i],y_bot[i])
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print(f"第{i+1}个点的斜率为：{k}")
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b = calc_slope_line.get_b(x_bot[i],y_bot[i],k)
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print(f"第{i+1}个点的截距为：{b}")
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x = (intercept_top - b) / (k - slope_top)
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y = k * x + b
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print(f"第{i+1}个点的坐标为为：{x_bot[i],y_bot[i]}")
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print(f"第{i+1}个点对应的上沿点为：{x,y}")
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Zw = calc_way.calc_height(x_bot[i],y_bot[i], x, y, alpha, beta)
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Xw, Yw = calc_way.calc_distance(x_bot[i],y_bot[i], alpha, beta)
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print(f"第{i+1}个点的坐标为为：{Xw, Yw }")
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point1 = (x_bot[i], 960-y_bot[i])
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point2 = (int(x), 960-int(y))
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cv2.line(image, point1, point2, (0, 255, 0), 1)
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# text = f"Xw,Yw:{int(Xw),int(Yw)},Zw:{int(Zw)}"
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# position = (x_bot[i], 960-y_bot[i]) # 文字左下角坐标 (x, y)
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# font = cv2.FONT_HERSHEY_SIMPLEX # 字体类型
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# font_scale = 1 # 字体大小
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# color = (0, 255, 255) # 黄色（BGR格式）
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# thickness = 1 # 文字粗细
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# cv2.putText(image, text, position, font, font_scale, color, thickness, cv2.LINE_AA)
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print("路沿高度", Zw)
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Z = Z + Zw
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print(f"平均路沿高度为：{Z/len(x_bot)}")
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text = f"avg_height:{Z/len(x_bot)}"
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position = (50, 200) # 文字左下角坐标 (x, y)
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font = cv2.FONT_HERSHEY_SIMPLEX # 字体类型
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font_scale = 1 # 字体大小
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color = (0, 255, 255) # 黄色（BGR格式）
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thickness = 1 # 文字粗细
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# 3. 在图像上绘制文字
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cv2.putText(image, text, position, font, font_scale, color, thickness, cv2.LINE_AA)
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cv2.imshow("Image with Line", image)
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cv2.waitKey(0) # 按任意键关闭窗口
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cv2.destroyAllWindows()
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cv2.imwrite(output_image, image) |
