实现 load_and_transform_depth_data

To reproduce the SUNRGBD results, one has to convert the raw depth data to standardized disparity in the following steps: 1. Convert raw depth (uint16) to meters following the official SUN RGBD toolbox read3dPoints.m Toolbox 2. Convert depth to disparity using correct camera intrinsics. Following the response of @imisra with different baselines for each camera. Focal length for each sample can be obtained from the intrinsics.txt file. 3. Depth standardization by finding the mean and std of the disparity values across the training split. I find these values with the compute_depth_mean_std implementation from RGBD-Seg dataset_base.py. This yields me the following mean and std values: mean: 24.82968 std: 14.40078 Which can be used to normalize (depending on the raw or refined mode) as follows (based on preprocessing.py Normalize):