import cv2

# 1.读取一张深度图
depth_img = cv2.imread("Dataset_depth/images/train/1112_0-rgb.png", cv2.IMREAD_UNCHANGED)
print(depth_img.shape)
cv2.imshow("depth", depth_img)  # (960, 1280)
print(depth_img)

# 读取一张rgb的图片做对比
input_path = "Dataset_rgb/images/train/1112_0-rgb.jpeg"
object_image = cv2.imread(input_path, cv2.IMREAD_UNCHANGED)
print(object_image.shape)
print(object_image)

# 2.转换深度图, 将深度图转换为[0-255]范围更直观的表示形式显示
depth_normalized = cv2.convertScaleAbs(depth_img, alpha=255.0 / depth_img.max())

# 3.显示深度图
cv2.imshow("depth_normalized", depth_normalized)
cv2.waitKey()

打印结果：

深度图：

shape: (960, 1280)
img:
[[0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 ...
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]
 [0 0 0 ... 0 0 0]]

RGB图：

shape: (960, 1280, 3)
img:
[[[17 21 16]
  [17 21 16]
  [18 22 17]
  ...
  [14 17 15]
  [15 18 16]
  [15 18 16]]

 [[16 20 15]
  [16 20 15]
  [17 21 16]
  ...
  [15 18 16]
  [15 18 16]
  [15 18 16]]

 [[16 20 15]
  [16 20 15]
  [17 21 16]
  ...
  [15 18 16]
  [15 18 16]
  [15 18 16]]

 ...

 [[11 14 12]
  [11 14 12]
  [11 14 12]
  ...
  [10 10 10]
  [11 11 11]
  [11 11 11]]

 [[12 15 13]
  [12 15 13]
  [12 15 13]
  ...
  [10 10 10]
  [11 11 11]
  [11 11 11]]

 [[12 15 13]
  [12 15 13]
  [12 15 13]
  ...
  [11 11 11]
  [11 11 11]
  [11 11 11]]]

图片显示：