The depth values stored in 16bit png files range from approximately 2k to 43k. What are these values? How can I interpret metric distance (mm) from these values? @anitarau
Created by Alwyn Mathew alwynmathew The raw images are 16-bits which is the source of all these confusions. Converting to 8-bit fixes the issues.
Is this the correct way to read the depth files? @anitarau
```
depth = PIL.Image("/path/to/depth/file.png")
depth = np.array(depth) # depth values in approx [2k, 43k]
depth_norm = (depth - np.min(depth)) / (np.max(depth) - np.min(depth)) # normalized depth values in [0, 1]
depth_acutal = depth_norm * 20 # depth values in [0, 20]
```
Normalization will not be correct if `np.max(depth)` and `np.min(depth)` varies from file to file.
@alwynmathew Yes, that's correct! @anitarau Thank you. Does this same depth scaling apply to http://cmic.cs.ucl.ac.uk/ColonoscopyDepth/ too? Depth values correspond to [0,20] cm? Thanks for your question! @alwynmathew the depth should be read as greyscale images in a [0,1] range. These values will correspond to [0,20] cm. The camera poses are also given in cm. @fjia the depth values do in fact correspond to a metric in the real world. The data is extracted from a computer tomography scan that preserves scale. I think in colonoscopy - single camera, the depth is not perfect as 3D stereo reconstruction, they are depth value with scaling factors, so the distance maybe not in mm physical metric.