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#!/usr/bin/env python

# Copyright (c) 2023, ETH Zurich and UNC Chapel Hill.

# All rights reserved.

#

# Redistribution and use in source and binary forms, with or without

# modification, are permitted provided that the following conditions are met:

#

# * Redistributions of source code must retain the above copyright

# notice, this list of conditions and the following disclaimer.

#

# * Redistributions in binary form must reproduce the above copyright

# notice, this list of conditions and the following disclaimer in the

# documentation and/or other materials provided with the distribution.

#

# * Neither the name of ETH Zurich and UNC Chapel Hill nor the names of

# its contributors may be used to endorse or promote products derived

# from this software without specific prior written permission.

#

# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"

# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE

# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE

# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE

# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR

# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF

# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS

# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN

# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)

# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE

# POSSIBILITY OF SUCH DAMAGE.

import argparse

import numpy as np

import os

import struct

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 write_array(array, path):

"""

see: src/mvs/mat.h

void Mat<T>::Write(const std::string& path)

"""

assert array.dtype == np.float32

if len(array.shape) == 2:

height, width = array.shape

channels = 1

elif len(array.shape) == 3:

height, width, channels = array.shape

else:

assert False

with open(path, "w") as fid:

fid.write(str(width) + "&" + str(height) + "&" + str(channels) + "&")

with open(path, "ab") as fid:

if len(array.shape) == 2:

array_trans = np.transpose(array, (1, 0))

elif len(array.shape) == 3:

array_trans = np.transpose(array, (1, 0, 2))

else:

assert False

data_1d = array_trans.reshape(-1, order="F")

data_list = data_1d.tolist()

endian_character = "<"

format_char_sequence = "".join(["f"] * len(data_list))

byte_data = struct.pack(

endian_character + format_char_sequence, *data_list

)

fid.write(byte_data)

def parse_args():

parser = argparse.ArgumentParser()

parser.add_argument(

"-d", "--depth_map", help="path to depth map", type=str, required=True

)

parser.add_argument(

"-n", "--normal_map", help="path to normal map", type=str, required=True

)

parser.add_argument(

"--min_depth_percentile",

help="minimum visualization depth percentile",

type=float,

default=5,

)

parser.add_argument(

"--max_depth_percentile",

help="maximum visualization depth percentile",

type=float,

default=95,

)

args = parser.parse_args()

return args

def main():

args = parse_args()

if args.min_depth_percentile > args.max_depth_percentile:

raise ValueError(

"min_depth_percentile should be less than or equal "

"to the max_depth_perceintile."

)

# Read depth and normal maps corresponding to the same image.

if not os.path.exists(args.depth_map):

raise FileNotFoundError("File not found: {}".format(args.depth_map))

if not os.path.exists(args.normal_map):

raise FileNotFoundError("File not found: {}".format(args.normal_map))

depth_map = read_array(args.depth_map)

normal_map = read_array(args.normal_map)

min_depth, max_depth = np.percentile(

depth_map, [args.min_depth_percentile, args.max_depth_percentile]

)

depth_map[depth_map < min_depth] = min_depth

depth_map[depth_map > max_depth] = max_depth

import pylab as plt

# Visualize the depth map.

plt.figure()

plt.imshow(depth_map)

plt.title("depth map")

# Visualize the normal map.

plt.figure()

plt.imshow(normal_map)

plt.title("normal map")

plt.show()

if __name__ == "__main__":

main()