灰度可视化前文:https://segmentfault.com/a/1190000044151630

1.灰度数值可视化

img = np.zeros([800, 800, 3], dtype=np.uint8)   for i in range(16):      for j in range(16):         x = i * 50         y = j * 50         s = j + i * 16         img[x: x + 47, y: y + 47] = s         # 图片 增加的文字 地位 字体 字体大小 字体色彩 字体粗细         cv2.putText(img, str(s), (j * 50, 47 +i * 50), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)

文字的地位断定在左下角:

2.其余款式

# h示意区域高度,w示意区域长度,l示意像素长度h, w, l = [10, 26, 50]   img = np.zeros([h*l, w*l, 3], dtype=np.uint8)   for i in range(h):      for j in range(w):         x = i * l         y = j * l         s = j + i * w         img[x: x + l - 3, y: y + l - 3] = s % 256         cv2.putText(img, str(s), (j * l, (i + 1) * l - 3), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)