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)