def main():
parser = argparse.ArgumentParser(description="Calibrate using keypoint matches");
parser.add_argument('pattern_key_fname', type=str, help='reference pattern keypoint file')
parser.add_argument('num_frames', type=int, help='Number of scene frames')
parser.add_argument('scene_key_fmt', type=str, help='Printf-formatted string representing keypoint files from N scene frames')
parser.add_argument('match_fmt', type=str, help='Printf-formatted string representing keypoint match files')
parser.add_argument('example_image', type=str, help='Example image to get dimensions from')
parser.add_argument('out_fname', type=str, help='filename for intrinsic calibrated camera')
parser.add_argument('--min_matches', default=20, type=str, help='omit frames with fewer than N matches')
args = parser.parse_args()
pattern_keys = feat.read_features(args.pattern_key_fname)[0];
fnames = [(args.scene_key_fmt % x, args.match_fmt % x) for x in range(1,args.num_frames+1)]
fnames = [x for x in fnames if os.path.isfile(x[0])]
if len(fnames) == 0:
print "No matching keypoint files"
exit(1)
missing = next((x[1] for x in fnames if not os.path.isfile(x[1])), None)
if missing is not None:
print "File not found: %s" % missing
exit(1)
[frame_fnames, match_fnames] = zip(*fnames)
print "reading keypoint from %d frames" % len(frame_fnames)
frames_keys = [feat.read_features(x)[0] for x in frame_fnames]
print "reading matches from %d frames" % len(match_fnames)
frames_matches = [feat.read_matches(x) for x in match_fnames]
img = cv2.imread(args.example_image)
img_size = (img.shape[1], img.shape[0]);
[obj_pts, image_pts] = to_calibration_data(frames_matches, pattern_keys, frames_keys, args.min_matches)
cam = calibrate_intrinsic(obj_pts, image_pts, img_size)
calib.write_intrinsic_camera(args.out_fname, cam);
def read_matches(num_cams, num_frames, fmt, sparse):
return read_cams_frames_(num_cams, num_frames, fmt, lambda x: [My_match(m) for m in feat.read_matches(x)], sparse)
def main():
parser = argparse.ArgumentParser(
description="Calibrate using keypoint matches")
parser.add_argument('pattern_key_fname',
type=str,
help='reference pattern keypoint file')
parser.add_argument('num_frames', type=int, help='Number of scene frames')
parser.add_argument(
'scene_key_fmt',
type=str,
help=
'Printf-formatted string representing keypoint files from N scene frames'
)
parser.add_argument(
'match_fmt',
type=str,
help='Printf-formatted string representing keypoint match files')
parser.add_argument('example_image',
type=str,
help='Example image to get dimensions from')
parser.add_argument('out_fname',
type=str,
help='filename for intrinsic calibrated camera')
parser.add_argument('--min_matches',
default=20,
type=str,
help='omit frames with fewer than N matches')
args = parser.parse_args()
pattern_keys = feat.read_features(args.pattern_key_fname)[0]
fnames = [(args.scene_key_fmt % x, args.match_fmt % x)
for x in range(1, args.num_frames + 1)]
fnames = [x for x in fnames if os.path.isfile(x[0])]
if len(fnames) == 0:
print "No matching keypoint files"
exit(1)
missing = next((x[1] for x in fnames if not os.path.isfile(x[1])), None)
if missing is not None:
print "File not found: %s" % missing
exit(1)
[frame_fnames, match_fnames] = zip(*fnames)
print "reading keypoint from %d frames" % len(frame_fnames)
frames_keys = [feat.read_features(x)[0] for x in frame_fnames]
print "reading matches from %d frames" % len(match_fnames)
frames_matches = [feat.read_matches(x) for x in match_fnames]
img = cv2.imread(args.example_image)
img_size = (img.shape[1], img.shape[0])
[obj_pts, image_pts] = to_calibration_data(frames_matches, pattern_keys,
frames_keys, args.min_matches)
cam = calibrate_intrinsic(obj_pts, image_pts, img_size)
calib.write_intrinsic_camera(args.out_fname, cam)
def read_matches(num_cams, num_frames, fmt, sparse):
return read_cams_frames_(
num_cams, num_frames, fmt,
lambda x: [My_match(m) for m in feat.read_matches(x)], sparse)
#!/usr/bin/env python
from sys import argv
import features_ as feat
import cv2
if len(argv) < 6:
print "Usage: show_matches img_1 img_2 keypoints_1 keypoints_2 matches"
exit(1)
img1 = cv2.imread(argv[1], 0)
img2 = cv2.imread(argv[2], 0)
kp1 = feat.read_features(argv[3])[0]
kp2 = feat.read_features(argv[4])[0]
matches = feat.read_matches(argv[5])
matched_img = feat.draw_matches(img1, img2, kp1, kp2, matches)
cv2.imshow("Matches", matched_img)
cv2.waitKey()
