def detect_image():
filepaths = save_files(request.files)
output_paths = []
for file in filepaths:
image = Image(file)
image.detect_features()
output_filename = os.path.join(OUTPUT_IMAGE_PATH, str(uuid.uuid4()) + "_kps.jpg")
output = image.draw_keypoints(output_filename, orientation=True, gray=True)
output_paths.append(output_filename[output_filename.find("/static"):])
print output_paths
return json.dumps({"output_paths": output_paths})
def main(args):
if len(args) < 2:
print_help()
exit()
parser = argparse.ArgumentParser()
parser.add_argument('mode', default=None, type=str)
parser.add_argument('manual_identifier', default=None, nargs='?', type=str)
parser.add_argument('-i', default=[], action='append', nargs='?', type=str)
parser.add_argument('-f', default=None, type=str)
parser.add_argument('-o', default='output.jpg', type=str)
parser.add_argument('--scene_output', default=None,
type=str) #type=argparse.FileType('w'))
parser.add_argument('--projection_output', default=None,
type=str) #type=argparse.FileType('w'))
parser.add_argument('--silent', action='store_true')
parser.add_argument('--cv', action='store_true')
args = parser.parse_args(args[1:])
# current_dir = os.path.dirname(os.path.realpath(__file__))
current_dir = os.getcwd()
if args.f:
files = filter(
lambda x: any([i in x.lower() for i in ACCEPTED_FILETYPES]),
os.listdir(args.f))
files = map(lambda x: os.path.join(args.f, x), files)
args.i += files
args.i = map(lambda x: os.path.join(current_dir, x), args.i)
mode = args.mode
if mode == 'detect':
if not args.silent:
print 'Detecting images: {}'.format(", ".join(args.i))
print 'Outputting to: {}'.format(args.o)
# if there is more than one output image
if len(args.i) > 1:
for x in range(len(args.i)):
image = Image(args.i[x])
image.detect_features()
output = image.draw_keypoints(CVFuncs.addPostToPath(args.o, x),
orientation=True,
gray=True)
else:
image = Image(args.i[0])
image.detect_features()
output = image.draw_keypoints(args.o, orientation=True, gray=True)
elif mode == 'match':
if not args.silent:
print 'Matching images: {}'.format(", ".join(args.i))
print 'Outputting to: {}'.format(args.o)
imList = []
for imageLocation in args.i:
image1 = Image(imageLocation)
image1.detect_features()
imList.append(image1)
for x in range(0, len(imList)):
for y in range(x + 1, len(imList)):
points1, points2, matches = CVFuncs.findMatchesKnn(imList[x],
imList[y],
filter=True,
ratio=True)
# if there is more than one output image
if len(imList) > 2:
CVFuncs.drawMatches(
imList[x], imList[y], matches,
CVFuncs.addPostToPath(args.o,
str(x) + "-" + str(y)))
else:
CVFuncs.drawMatches(imList[x], imList[y], matches, args.o)
elif mode == 'triangulate':
if not args.silent:
print 'Triangulating images: {}'.format(args.i)
if args.scene_output:
print 'Outputting scene to: {}'.format(args.scene_output)
if args.projection_output:
print 'Outputting projections to: {}'.format(
args.projection_output)
track = TrackCreator(args.i)
track.triangulateImages(scene_file=args.scene_output,
projections_file=args.projection_output,
silent=args.silent)
elif mode == 'manual_pts':
manual_location = args.manual_identifier
triangulateManual.triangulateManualAndOutput(
args.i[0],
args.i[1],
manual_location,
output_file=args.scene_output,
projections_file=args.projection_output)
def main(args):
if len(args) < 2:
print_help()
exit()
parser = argparse.ArgumentParser()
parser.add_argument("mode", default=None, type=str)
parser.add_argument("manual_identifier", default=None, nargs="?", type=str)
parser.add_argument("-i", default=[], action="append", nargs="?", type=str)
parser.add_argument("-f", default=None, type=str)
parser.add_argument("-o", default="output.jpg", type=str)
parser.add_argument("--scene_output", default=None, type=str) # type=argparse.FileType('w'))
parser.add_argument("--projection_output", default=None, type=str) # type=argparse.FileType('w'))
parser.add_argument("--silent", action="store_true")
parser.add_argument("--cv", action="store_true")
args = parser.parse_args(args[1:])
# current_dir = os.path.dirname(os.path.realpath(__file__))
current_dir = os.getcwd()
if args.f:
files = filter(lambda x: any([i in x.lower() for i in ACCEPTED_FILETYPES]), os.listdir(args.f))
files = map(lambda x: os.path.join(args.f, x), files)
args.i += files
args.i = map(lambda x: os.path.join(current_dir, x), args.i)
mode = args.mode
if mode == "detect":
if not args.silent:
print "Detecting images: {}".format(", ".join(args.i))
print "Outputting to: {}".format(args.o)
# if there is more than one output image
if len(args.i) > 1:
for x in range(len(args.i)):
image = Image(args.i[x])
image.detect_features()
output = image.draw_keypoints(CVFuncs.addPostToPath(args.o, x), orientation=True, gray=True)
else:
image = Image(args.i[0])
image.detect_features()
output = image.draw_keypoints(args.o, orientation=True, gray=True)
elif mode == "match":
if not args.silent:
print "Matching images: {}".format(", ".join(args.i))
print "Outputting to: {}".format(args.o)
imList = []
for imageLocation in args.i:
image1 = Image(imageLocation)
image1.detect_features()
imList.append(image1)
for x in range(0, len(imList)):
for y in range(x + 1, len(imList)):
points1, points2, matches = CVFuncs.findMatchesKnn(imList[x], imList[y], filter=True, ratio=True)
# if there is more than one output image
if len(imList) > 2:
CVFuncs.drawMatches(
imList[x], imList[y], matches, CVFuncs.addPostToPath(args.o, str(x) + "-" + str(y))
)
else:
CVFuncs.drawMatches(imList[x], imList[y], matches, args.o)
elif mode == "triangulate":
if not args.silent:
print "Triangulating images: {}".format(args.i)
if args.scene_output:
print "Outputting scene to: {}".format(args.scene_output)
if args.projection_output:
print "Outputting projections to: {}".format(args.projection_output)
track = TrackCreator(args.i)
track.triangulateImages(
scene_file=args.scene_output, projections_file=args.projection_output, silent=args.silent
)
elif mode == "manual_pts":
manual_location = args.manual_identifier
triangulateManual.triangulateManualAndOutput(
args.i[0],
args.i[1],
manual_location,
output_file=args.scene_output,
projections_file=args.projection_output,
)
