# Copyright (c) 2018, ETH Zurich and UNC Chapel Hill.
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)

import numpy as np
import pylab as plt


def read_array(path):
    with open(path, "rb") as fid:
        width, height, channels = np.genfromtxt(fid, delimiter="&", max_rows=1,
                                                usecols=(0, 1, 2), dtype=int)
        fid.seek(0)
        num_delimiter = 0
        byte = fid.read(1)
        while True:
            if byte == b"&":
                num_delimiter += 1
                if num_delimiter >= 3:
                    break
            byte = fid.read(1)
        array = np.fromfile(fid, np.float32)
    array = array.reshape((width, height, channels), order="F")
    return np.transpose(array, (1, 0, 2)).squeeze()


def main():
    # Read depth and normal maps corresponding to the same image.
    depth_map = read_array(
        "path/to/dense/stereo/depth_maps/image1.jpg.photometric.bin")
    normal_map = read_array(
        "path/to/dense/stereo/normal_maps/image1.jpg.photometric.bin")

    # Visualize the depth map.
    min_depth, max_depth = np.percentile(depth_map, [5, 95])
    depth_map[depth_map < min_depth] = min_depth
    depth_map[depth_map > max_depth] = max_depth
    plt.imshow(depth_map)
    plt.show()


if __name__ == "__main__":
    main()
