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import os

import sys

import argparse

import urllib.request

import subprocess

def download_file(url, file_path, max_retries=3):

if os.path.exists(file_path):

return

print(f"Downloading {url} to {file_path}")

for retry in range(max_retries):

try:

urllib.request.urlretrieve(url, file_path)

return

except Exception as exc:

print(

f"Failed to download {url} (trial={retry+1}) to {file_path} due to {exc}"

)

def check_small_errors_or_exit(

dataset_name,

max_rotation_error,

max_proj_center_error,

expected_num_images,

errors_csv_path,

):

print(f"Evaluating errors for {dataset_name}")

error = False

with open(errors_csv_path, "r") as fid:

num_images = 0

for line in fid:

line = line.strip()

if len(line) == 0 or line.startswith("#"):

continue

rotation_error, proj_center_error = map(float, line.split(","))

num_images += 1

if rotation_error > max_rotation_error:

print("Exceeded rotation error threshold:", rotation_error)

error = True

if proj_center_error > max_proj_center_error:

print(

"Exceeded projection center error threshold:",

proj_center_error,

)

error = True

if num_images != expected_num_images:

print("Unexpected number of images:", num_images)

error = True

if error:

sys.exit(1)

def process_dataset(args, dataset_name):

print("Processing dataset:", dataset_name)

workspace_path = os.path.join(

os.path.realpath(args.workspace_path), dataset_name

)

os.makedirs(workspace_path, exist_ok=True)

dataset_archive_path = os.path.join(workspace_path, f"{dataset_name}.7z")

download_file(

f"https://www.eth3d.net/data/{dataset_name}_dslr_undistorted.7z",

dataset_archive_path,

)

subprocess.check_call(

["7zz", "x", "-y", f"{dataset_name}.7z"], cwd=workspace_path

)

# Find undistorted parameters of first camera and initialize all images with it.

with open(

os.path.join(

workspace_path,

f"{dataset_name}/dslr_calibration_undistorted/cameras.txt",

),

"r",

) as fid:

for line in fid:

if not line.startswith("#"):

first_camera_data = line.split()

camera_model = first_camera_data[1]

assert camera_model == "PINHOLE"

camera_params = first_camera_data[4:]

assert len(camera_params) == 4

break

# Count the number of expected images in the GT.

expected_num_images = 0

with open(

os.path.join(

workspace_path,

f"{dataset_name}/dslr_calibration_undistorted/images.txt",

),

"r",

) as fid:

for line in fid:

if not line.startswith("#") and line.strip():

expected_num_images += 1

# Each image uses two consecutive lines.

assert expected_num_images % 2 == 0

expected_num_images /= 2

# Run automatic reconstruction pipeline.

subprocess.check_call(

[

os.path.realpath(args.colmap_path),

"automatic_reconstructor",

"--image_path",

f"{dataset_name}/images/",

"--workspace_path",

workspace_path,

"--use_gpu",

"1" if args.use_gpu else "0",

"--num_threads",

str(args.num_threads),

"--quality",

"low",

"--camera_model",

"PINHOLE",

"--camera_params",

",".join(camera_params),

],

cwd=workspace_path,

)

# Compare reconstructed model to GT model.

subprocess.check_call(

[

os.path.realpath(args.colmap_path),

"model_comparer",

"--input_path1",

"sparse/0",

"--input_path2",

f"{dataset_name}/dslr_calibration_undistorted/",

"--output_path",

".",

"--alignment_error",

"proj_center",

"--max_proj_center_error",

str(args.max_proj_center_error),

],

cwd=workspace_path,

)

# Ensure discrepancy between reconstructed model and GT is small.

check_small_errors_or_exit(

dataset_name,

args.max_rotation_error,

args.max_proj_center_error,

expected_num_images,

os.path.join(workspace_path, "errors.csv"),

)

def parse_args():

parser = argparse.ArgumentParser()

parser.add_argument("--dataset_names", required=True)

parser.add_argument("--workspace_path", required=True)

parser.add_argument("--colmap_path", required=True)

parser.add_argument("--use_gpu", default=True, action="store_true")

parser.add_argument("--use_cpu", dest="use_gpu", action="store_false")

parser.add_argument("--num_threads", type=int, default=-1)

parser.add_argument("--quality", default="medium")

parser.add_argument("--max_rotation_error", type=float, default=1.0)

parser.add_argument("--max_proj_center_error", type=float, default=0.1)

return parser.parse_args()

def main():

args = parse_args()

for dataset_name in args.dataset_names.split(","):

process_dataset(args, dataset_name.strip())

if __name__ == "__main__":

main()