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Running
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Zero
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import argparse
import subprocess
from pathlib import Path
import os
import numpy as np
from skimage.io import imread, imsave
from transforms3d.quaternions import mat2quat
from colmap.database import COLMAPDatabase
from colmap.read_write_model import CAMERA_MODEL_NAMES
import open3d as o3d
# from ldm.base_utils import read_pickle
K, _, _, _, POSES = read_pickle(f'meta_info/camera-16.pkl')
H, W, NUM_IMAGES = 256, 256, 16
def extract_and_match_sift(colmap_path, database_path, image_dir):
cmd = [
str(colmap_path), 'feature_extractor',
'--database_path', str(database_path),
'--image_path', str(image_dir),
]
print(' '.join(cmd))
subprocess.run(cmd, check=True)
cmd = [
str(colmap_path), 'exhaustive_matcher',
'--database_path', str(database_path),
]
print(' '.join(cmd))
subprocess.run(cmd, check=True)
def run_triangulation(colmap_path, model_path, in_sparse_model, database_path, image_dir):
print('Running the triangulation...')
model_path.mkdir(exist_ok=True, parents=True)
cmd = [
str(colmap_path), 'point_triangulator',
'--database_path', str(database_path),
'--image_path', str(image_dir),
'--input_path', str(in_sparse_model),
'--output_path', str(model_path),
'--Mapper.ba_refine_focal_length', '0',
'--Mapper.ba_refine_principal_point', '0',
'--Mapper.ba_refine_extra_params', '0']
print(' '.join(cmd))
subprocess.run(cmd, check=True)
def run_patch_match(colmap_path, sparse_model: Path, image_dir: Path, dense_model: Path):
print('Running patch match...')
assert sparse_model.exists()
dense_model.mkdir(parents=True, exist_ok=True)
cmd = [str(colmap_path), 'image_undistorter', '--input_path', str(sparse_model), '--image_path', str(image_dir), '--output_path', str(dense_model),]
print(' '.join(cmd))
subprocess.run(cmd, check=True)
cmd = [str(colmap_path), 'patch_match_stereo','--workspace_path', str(dense_model),]
print(' '.join(cmd))
subprocess.run(cmd, check=True)
def dump_images(in_image_dir, image_dir):
for index in range(NUM_IMAGES):
img = imread(f'{in_image_dir}/{index:03}.png')
imsave(f'{str(image_dir)}/{index:03}.png', img)
def build_db_known_poses_fixed(db_path, in_sparse_path):
db = COLMAPDatabase.connect(db_path)
db.create_tables()
# insert intrinsics
with open(f'{str(in_sparse_path)}/cameras.txt', 'w') as f:
for index in range(NUM_IMAGES):
fx, fy = K[0,0], K[1,1]
cx, cy = K[0,2], K[1,2]
model, width, height, params = CAMERA_MODEL_NAMES['PINHOLE'].model_id, W, H, np.array((fx, fy, cx, cy),np.float32)
db.add_camera(model, width, height, params, prior_focal_length=(fx+fy)/2, camera_id=index+1)
f.write(f'{index+1} PINHOLE {W} {H} {fx:.3f} {fy:.3f} {cx:.3f} {cy:.3f}\n')
with open(f'{str(in_sparse_path)}/images.txt','w') as f:
for index in range(NUM_IMAGES):
pose = POSES[index]
q = mat2quat(pose[:,:3])
t = pose[:,3]
img_id = db.add_image(f"{index:03}.png", camera_id=index+1, prior_q=q, prior_t=t)
f.write(f'{img_id} {q[0]:.5f} {q[1]:.5f} {q[2]:.5f} {q[3]:.5f} {t[0]:.5f} {t[1]:.5f} {t[2]:.5f} {index+1} {index:03}.png\n\n')
db.commit()
db.close()
with open(f'{in_sparse_path}/points3D.txt','w') as f:
f.write('\n')
def patch_match_with_known_poses(in_image_dir, project_dir, colmap_path='colmap'):
Path(project_dir).mkdir(exist_ok=True, parents=True)
if os.path.exists(f'{str(project_dir)}/dense/stereo/depth_maps'): return
# output poses
db_path = f'{str(project_dir)}/database.db'
image_dir = Path(f'{str(project_dir)}/images')
sparse_dir = Path(f'{str(project_dir)}/sparse')
in_sparse_dir = Path(f'{str(project_dir)}/sparse_in')
dense_dir = Path(f'{str(project_dir)}/dense')
image_dir.mkdir(exist_ok=True,parents=True)
sparse_dir.mkdir(exist_ok=True,parents=True)
in_sparse_dir.mkdir(exist_ok=True,parents=True)
dense_dir.mkdir(exist_ok=True,parents=True)
dump_images(in_image_dir, image_dir)
build_db_known_poses_fixed(db_path, in_sparse_dir)
extract_and_match_sift(colmap_path, db_path, image_dir)
run_triangulation(colmap_path,sparse_dir, in_sparse_dir, db_path, image_dir)
run_patch_match(colmap_path, sparse_dir, image_dir, dense_dir)
# fuse
cmd = [str(colmap_path), 'stereo_fusion',
'--workspace_path', f'{project_dir}/dense',
'--workspace_format', 'COLMAP',
'--input_type', 'geometric',
'--output_path', f'{project_dir}/points.ply',]
print(' '.join(cmd))
subprocess.run(cmd, check=True)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--dir',type=str)
parser.add_argument('--project',type=str)
parser.add_argument('--name',type=str)
parser.add_argument('--colmap',type=str, default='colmap')
args = parser.parse_args()
if not os.path.exists(f'{args.project}/points.ply'):
patch_match_with_known_poses(args.dir, args.project, colmap_path=args.colmap)
mesh = o3d.io.read_triangle_mesh(f'{args.project}/points.ply',)
vn = len(mesh.vertices)
with open('colmap-results.log', 'a') as f:
f.write(f'{args.name}\t{vn}\n')
if __name__=="__main__":
main() |