You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
exercise_2/3rdparty/colmap-dev/scripts/python/export_to_visualsfm.py

163 lines
6.4 KiB

# Copyright (c) 2022, 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.
#
# Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)
# This script exports a COLMAP database to the file structure to run VisualSfM.
import os
import sys
import argparse
import sqlite3
import shutil
import gzip
import numpy as np
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--database_path", required=True)
parser.add_argument("--image_path", required=True)
parser.add_argument("--output_path", required=True)
parser.add_argument("--min_num_matches", type=int, default=15)
parser.add_argument("--binary_feature_files", type=bool, default=True)
args = parser.parse_args()
return args
def pair_id_to_image_ids(pair_id):
image_id2 = pair_id % 2147483647
image_id1 = (pair_id - image_id2) / 2147483647
return image_id1, image_id2
def main():
args = parse_args()
connection = sqlite3.connect(args.database_path)
cursor = connection.cursor()
try:
os.makedirs(args.output_path)
except:
pass
cameras = {}
cursor.execute("SELECT camera_id, params FROM cameras;")
for row in cursor:
camera_id = row[0]
params = np.fromstring(row[1], dtype=np.double)
cameras[camera_id] = params
images = {}
cursor.execute("SELECT image_id, camera_id, name FROM images;")
for row in cursor:
image_id = row[0]
camera_id = row[1]
image_name = row[2]
print("Copying image", image_name)
images[image_id] = (len(images), image_name)
if not os.path.exists(os.path.join(args.output_path, image_name)):
shutil.copyfile(os.path.join(args.image_path, image_name),
os.path.join(args.output_path, image_name))
# The magic numbers used in VisualSfM's binary file format for storing the
# feature descriptors.
sift_name = 1413892435
sift_version_v4 = 808334422
sift_eof_marker = 1179600383
for image_id, (image_idx, image_name) in images.iteritems():
print("Exporting key file for", image_name)
base_name, ext = os.path.splitext(image_name)
key_file_name = os.path.join(args.output_path, base_name + ".sift")
if os.path.exists(key_file_name):
continue
cursor.execute("SELECT data FROM keypoints WHERE image_id=?;",
(image_id,))
row = next(cursor)
if row[0] is None:
keypoints = np.zeros((0, 6), dtype=np.float32)
descriptors = np.zeros((0, 128), dtype=np.uint8)
else:
keypoints = np.fromstring(row[0], dtype=np.float32).reshape(-1, 6)
cursor.execute("SELECT data FROM descriptors WHERE image_id=?;",
(image_id,))
row = next(cursor)
descriptors = np.fromstring(row[0], dtype=np.uint8).reshape(-1, 128)
if args.binary_feature_files:
with open(key_file_name, "wb") as fid:
fid.write(struct.pack("i", sift_name))
fid.write(struct.pack("i", sift_version_v4))
fid.write(struct.pack("i", keypoints.shape[0]))
fid.write(struct.pack("i", 4))
fid.write(struct.pack("i", 128))
keypoints[:, :4].astype(np.float32).tofile(fid)
descriptors.astype(np.uint8).tofile(fid)
fid.write(struct.pack("i", sift_eof_marker))
else:
with open(key_file_name, "w") as fid:
fid.write("%d %d\n" % (keypoints.shape[0],
descriptors.shape[1]))
for r in range(keypoints.shape[0]):
fid.write("%f %f 0 0 " % (keypoints[r, 0],
keypoints[r, 1]))
fid.write(" ".join(map(str,
descriptors[r].ravel().tolist())))
fid.write("\n")
with open(os.path.join(args.output_path, "matches.txt"), "w") as fid:
cursor.execute("SELECT pair_id, data FROM two_view_geometries "
"WHERE rows>=?;", (args.min_num_matches,))
for row in cursor:
pair_id = row[0]
inlier_matches = np.fromstring(row[1],
dtype=np.uint32).reshape(-1, 2)
image_id1, image_id2 = pair_id_to_image_ids(pair_id)
image_name1 = images[image_id1][1]
image_name2 = images[image_id2][1]
fid.write("%s %s %d\n" % (image_name1, image_name2,
inlier_matches.shape[0]))
line1 = ""
line2 = ""
for i in range(inlier_matches.shape[0]):
line1 += "%d " % inlier_matches[i, 0]
line2 += "%d " % inlier_matches[i, 1]
fid.write(line1 + "\n")
fid.write(line2 + "\n")
cursor.close()
connection.close()
if __name__ == "__main__":
main()