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#!/usr/bin/env python3
# Copyright (C) 2024-present Naver Corporation. All rights reserved.
# Licensed under CC BY-NC-SA 4.0 (non-commercial use only).
#
# --------------------------------------------------------
# Preprocessing code for the StaticThings3D dataset
# dataset at https://github.com/lmb-freiburg/robustmvd/blob/master/rmvd/data/README.md#staticthings3d
# 1) Download StaticThings3D in /path/to/StaticThings3D/
# with the script at https://github.com/lmb-freiburg/robustmvd/blob/master/rmvd/data/scripts/download_staticthings3d.sh
# --> depths.tar.bz2 frames_finalpass.tar.bz2 poses.tar.bz2 frames_cleanpass.tar.bz2 intrinsics.tar.bz2
# 2) unzip everything in the same /path/to/StaticThings3D/ directory
# 5) python datasets_preprocess/preprocess_staticthings3d.py --StaticThings3D_dir /path/to/tmp/StaticThings3D/
# --------------------------------------------------------
import os
import os.path as osp
import re
from tqdm import tqdm
import numpy as np
os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
import cv2
import path_to_root # noqa
from dust3r.utils.parallel import parallel_threads
from dust3r.datasets.utils import cropping # noqa
def get_parser():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--StaticThings3D_dir', required=True)
parser.add_argument('--precomputed_pairs', required=True)
parser.add_argument('--output_dir', default='data/staticthings3d_processed')
return parser
def main(db_root, pairs_path, output_dir):
all_scenes = _list_all_scenes(db_root)
# crop images
args = [(db_root, osp.join(split, subsplit, seq), camera, f'{n:04d}', output_dir)
for split, subsplit, seq in all_scenes for camera in ['left', 'right'] for n in range(6, 16)]
parallel_threads(load_crop_and_save, args, star_args=True, front_num=1)
# verify that all images are there
CAM = {b'l': 'left', b'r': 'right'}
pairs = np.load(pairs_path)
for scene, seq, cam1, im1, cam2, im2 in tqdm(pairs):
seq_path = osp.join('TRAIN', scene.decode('ascii'), f'{seq:04d}')
for cam, idx in [(CAM[cam1], im1), (CAM[cam2], im2)]:
for ext in ['clean', 'final']:
impath = osp.join(output_dir, seq_path, cam, f"{idx:04n}_{ext}.jpg")
assert osp.isfile(impath), f'missing an image at {impath=}'
print(f'>> Saved all data to {output_dir}!')
def load_crop_and_save(db_root, relpath_, camera, num, out_dir):
relpath = osp.join(relpath_, camera, num)
if osp.isfile(osp.join(out_dir, relpath + '.npz')):
return
os.makedirs(osp.join(out_dir, relpath_, camera), exist_ok=True)
# load everything
intrinsics_in = readFloat(osp.join(db_root, 'intrinsics', relpath_, num + '.float3'))
cam2world = np.linalg.inv(readFloat(osp.join(db_root, 'poses', relpath + '.float3')))
depthmap_in = readFloat(osp.join(db_root, 'depths', relpath + '.float3'))
img_clean = cv2.cvtColor(cv2.imread(osp.join(db_root, 'frames_cleanpass',
relpath + '.png'), cv2.IMREAD_COLOR), cv2.COLOR_BGR2RGB)
img_final = cv2.cvtColor(cv2.imread(osp.join(db_root, 'frames_finalpass',
relpath + '.png'), cv2.IMREAD_COLOR), cv2.COLOR_BGR2RGB)
# do the crop
assert img_clean.shape[:2] == (540, 960)
assert img_final.shape[:2] == (540, 960)
(clean_out, final_out), depthmap, intrinsics_out, R_in2out = _crop_image(
intrinsics_in, (img_clean, img_final), depthmap_in, (512, 384))
# write everything
clean_out.save(osp.join(out_dir, relpath + '_clean.jpg'), quality=80)
final_out.save(osp.join(out_dir, relpath + '_final.jpg'), quality=80)
cv2.imwrite(osp.join(out_dir, relpath + '.exr'), depthmap)
# New camera parameters
cam2world[:3, :3] = cam2world[:3, :3] @ R_in2out.T
np.savez(osp.join(out_dir, relpath + '.npz'), intrinsics=intrinsics_out, cam2world=cam2world)
def _crop_image(intrinsics_in, color_image_in, depthmap_in, resolution_out=(512, 512)):
image, depthmap, intrinsics_out = cropping.rescale_image_depthmap(
color_image_in, depthmap_in, intrinsics_in, resolution_out)
R_in2out = np.eye(3)
return image, depthmap, intrinsics_out, R_in2out
def _list_all_scenes(path):
print('>> Listing all scenes')
res = []
for split in ['TRAIN']:
for subsplit in 'ABC':
for seq in os.listdir(osp.join(path, 'intrinsics', split, subsplit)):
res.append((split, subsplit, seq))
print(f' (found ({len(res)}) scenes)')
assert res, f'Did not find anything at {path=}'
return res
def readFloat(name):
with open(name, 'rb') as f:
if (f.readline().decode("utf-8")) != 'float\n':
raise Exception('float file %s did not contain <float> keyword' % name)
dim = int(f.readline())
dims = []
count = 1
for i in range(0, dim):
d = int(f.readline())
dims.append(d)
count *= d
dims = list(reversed(dims))
data = np.fromfile(f, np.float32, count).reshape(dims)
return data # Hxw or CxHxW NxCxHxW
if __name__ == '__main__':
parser = get_parser()
args = parser.parse_args()
main(args.StaticThings3D_dir, args.precomputed_pairs, args.output_dir)
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