### 使用 Python 和 OpenCV 绘制带刻度坐标的图像 为了实现这一目标，可以利用 `cv2.putText` 函数来添加文字标签作为坐标轴上的刻度标记。下面是一个完整的例子，该例子不仅展示了如何创建一个简单的热力图，还说明了怎样向此图中加入 X 轴和 Y 轴的刻度。 ```python import numpy as np import random import cv2 # 初始化数据矩阵并填充随机值 vals = [] pos = [] for i in range(1000): vals.append(random.uniform(5.0, 200.0)) pos.append(random.randint(0, 10000)) mat = [0] * 10000 for i, p in enumerate(pos): mat[p] = vals[i] mat = np.array(mat).reshape((100, 100)).astype(np.uint8) # 应用颜色映射表到灰度图像上得到伪彩色效果 heatmap_img = cv2.applyColorMap(mat, cv2.COLORMAP_JET)[^1] height, width = heatmap_img.shape[:2] # 设置字体参数用于绘制文本 font = cv2.FONT_HERSHEY_SIMPLEX font_scale = 0.4 thickness = 1 color = (255, 255, 255) # 白色 # 添加X轴和Y轴的刻度线以及对应的数值标注 step_size = int(width / 10) for x in range(step_size, width + step_size, step_size): cv2.line(heatmap_img, (x, height), (x, height - 5), color, thickness=1) text_x = str(int(x / step_size)) ((text_width, text_height), _) = cv2.getTextSize(text_x, font, fontScale=font_scale, thickness=thickness) cv2.rectangle(heatmap_img, (x - int(text_width/2), height - 7), (x + int(text_width/2), height - 7 - text_height - 4), (0, 0, 0), -1) cv2.putText(heatmap_img, text_x, (x - int(text_width/2), height - 7 - int(text_height/2)), font, fontScale=font_scale, color=color, thickness=thickness) step_size_y = int(height / 10) for y in range(step_size_y, height + step_size_y, step_size_y): cv2.line(heatmap_img, (0, y), (5, y), color, thickness=1) text_y = str(int(y / step_size_y)) ((_, text_height), _) = cv2.getTextSize(text_y, font, fontScale=font_scale, thickness=thickness) cv2.rectangle(heatmap_img, (0, y - int(text_height/2)), (-int(text_width)-4, y + int(text_height/2)), (0, 0, 0), -1) cv2.putText(heatmap_img, text_y, (-int(text_width)-4, y + int(text_height/2)), font, fontScale=font_scale, color=color, thickness=thickness) # 显示最终结果 cv2.imshow('Heatmap with Axis Ticks', heatmap_img) cv2.imwrite('./figures/test_with_ticks.png', heatmap_img) cv2.waitKey(0) cv2.destroyAllWindows() ``` 上述代码片段首先构建了一个二维数组表示的数据集，并通过调用 `cv2.applyColorMap()` 方法将其转换成具有视觉吸引力的颜色编码形式。接着，在生成的图片基础上增加了水平方向(X轴)和垂直方向(Y轴)的一系列短线条代表刻度位置，并附上了相应的数字标签以便识别具体的坐标值。