def main(args):
image = cv.LoadImage( args.input_image)
featuremap = FeatureMap()
featuremap.read_from_file( args.input_features )
classifier = load_classifier_from_file( args.classifier )
if not classifier.is_trained():
print "Warning: using an untrained classifier. This will probably break."
label_set = LabelSet()
label_set.read_from_file( args.label_set )
window = ClickWindow( image, args.zoom_out)
while(True):
cont = update_all_windows()
if not cont:
break
if window.update_label:
click_pt = window.click_pt
closest_pt = min( featuremap.get_feature_points(),
key = lambda pt: l2_dist(pt,click_pt) )
feature = featuremap.get_feature( closest_pt )
shape = featuremap.get_shape( closest_pt )
size = featuremap.get_size( closest_pt )
label = classifier.predict_label( feature )
label_name = "None" if label==0 else label_set.get_label_name(label)
label_color = cv.RGB(0,0,0) if label==0 else label_set.get_label_color(label)
print "Predicted label: %d (%s)"%(label, label_name);
window.set_patch( closest_pt, shape, size, label_color )
window.update_label = False
def main(args):
if args.output_directory:
directory = args.output_directory
else:
directory = os.path.dirname(args.compared_image)
print "No output directory specified. Defaulting to %s"%directory
if not os.path.exists(directory):
os.makedirs(directory)
if args.output_prefix:
prefix = args.output_prefix
else:
prefix_c = os.path.splitext(os.path.basename(args.compared_image))[0]
prefix_r = os.path.splitext(os.path.basename(args.reference_image))[0]
prefix = "%s_TO_%s"%(prefix_c, prefix_r)
print "No output prefix selected. Defaulting to %s"%prefix
output_file = "%s/%s.matches"%(directory, prefix)
if not args.input_match_file:
args.input_match_file = output_file
if not args.force_overwrite and os.path.exists( args.input_match_file ):
match_set_old = MatchSet( args.compared_image, args.reference_image )
match_set_old.read_from_file( args.input_match_file )
for match in match_set_old.get_matches():
compare_pts.append(match.compare_pt)
reference_pts.append(match.reference_pt)
strengths.append(match.strength)
compared_image = cv.LoadImage( args.compared_image)
reference_image = cv.LoadImage( args.reference_image )
compare_window = ClickWindow( compared_image, args.compare_zoom_out, COMPARE)
reference_window = ClickWindow( reference_image, args.reference_zoom_out, REFERENCE)
global mode
global strength
while(True):
cont = update_all_windows()
if not cont:
break
if compare_window.click_pt and reference_window.click_pt:
compare_pts.append(compare_window.click_pt)
reference_pts.append(reference_window.click_pt)
strengths.append(strength)
compare_window.clear_click_pt()
reference_window.clear_click_pt()
if save_flag:
match_set = MatchSet(args.compared_image, args.reference_image)
for i in range( len(compare_pts) ):
match_set.add_match( compare_pts[i], reference_pts[i], strengths[i] )
match_set.save_to_file( output_file )
print "Saved to %s"%output_file
def main(args):
compared_image = cv.LoadImage( args.compared_image)
reference_image = cv.LoadImage( args.reference_image )
compared_featuremap = FeatureMap()
compared_featuremap.read_from_file( args.compared_features )
reference_featuremap = FeatureMap()
reference_featuremap.read_from_file( args.reference_features )
compare_window = ClickWindow( compared_image, args.compare_zoom_out)
reference_window = ReferenceWindow( reference_image, args.reference_zoom_out)
reference_window.move( compare_window.size()[0], 0 )
#nn_solver = pyflann.FLANN()
while(True):
cont = update_all_windows()
if not cont:
break
if compare_window.update_nn:
click_pt = compare_window.click_pt
closest_pt = min( compared_featuremap.get_feature_points(),
key = lambda pt: l2_dist(pt,click_pt) )
compared_feature = compared_featuremap.get_feature( closest_pt )
distance_map = {}
shape_map = {}
size_map = {}
for pt in reference_featuremap.get_feature_points():
distance_map[pt] = l2_dist( compared_feature,
reference_featuremap.get_feature(pt) )
shape_map[pt] = reference_featuremap.get_shape(pt)
size_map[pt] = reference_featuremap.get_size(pt)
knn = compute_knn( distance_map.keys(), lambda pt: distance_map[pt], 20 )
reference_window.set_knn( knn )
reference_window.set_distance_map( distance_map )
reference_window.set_shape_map( shape_map )
reference_window.set_size_map( size_map )
compare_window.update_nn = False
def main(args):
n_views = len(args.images)
assert len(args.features) == len(args.zoom_outs) == n_views
view_windows = []
for i in range(n_views):
image = cv.LoadImage( args.images[i] )
featuremap = FeatureMap()
featuremap.read_from_file( args.features[i] )
zoom_out = args.zoom_outs[i]
view_window = ViewWindow( image, zoom_out, featuremap, i)
view_windows.append(view_window)
#Tile
x = 0
y = 0
for win in view_windows:
if x + win.size()[0] >= SCREEN_WIDTH:
x = 0
y += win.size()[1]
win.move(x,y)
x += win.size()[0]
while(True):
cont = update_all_windows()
if not cont:
break
def main(args):
output_files = []
compared_images = []
compared_windows = []
for i,compared_image_file in enumerate(args.compared_images):
if args.output_directory:
directory = args.output_directory
else:
directory = os.path.dirname(args.compared_images[0])
print "No output directory specified. Defaulting to %s"%directory
if not os.path.exists(directory):
os.makedirs(directory)
if args.output_prefix:
prefix = args.output_prefix
else:
prefix_c = os.path.splitext(os.path.basename(args.compared_images[i]))[0]
prefix_r = os.path.splitext(os.path.basename(args.reference_image))[0]
prefix = "%s_TO_%s"%(prefix_c, prefix_r)
print "No output prefix selected. Defaulting to %s"%prefix
output_file = "%s/%s.matches"%(directory, prefix)
output_files.append(output_file)
compared_image = cv.LoadImage( args.compared_images[i])
compared_images.append(compared_image)
compared_window = ClickWindow( compared_image, args.compared_zoom_out, i)
compared_windows.append(compared_window)
compared_pts.append({})
if args.input_points_file:
point_set = PointSet()
point_set.read_from_file( args.input_points_file )
for i,pt in enumerate(point_set.get_points()):
reference_pts[i] = pt
reference_image = cv.LoadImage( args.reference_image )
reference_window = ClickWindow( reference_image, args.reference_zoom_out, -1)
update_all_windows()
# Tile
y = reference_window.size()[1]
x = 0
for win in compared_windows:
if x + win.size()[0] >= SCREEN_WIDTH:
x = 0
y += win.size()[1]
print "Moving window %d to %f,%f"%(win.id,x,y)
win.move(x,y)
x += win.size()[0]
global mode
global selected_index
while(True):
cont = update_all_windows()
if not cont:
break
if reference_window.click_pt:
print "Updating reference_window click_pt"
key = safe_max(reference_pts.keys())+1
reference_pts[key] = reference_window.click_pt
selected_index = key
reference_window.clear_click_pt()
for i,compared_window in enumerate(compared_windows):
if compared_window.click_pt and selected_index > -1:
print selected_index
compared_pts[i][selected_index] = compared_window.click_pt
compared_window.clear_click_pt()
if save_flag:
for i in range(len(compared_windows)):
match_set = MatchSet(args.compared_images[i], args.reference_image)
for k in compared_pts[i].keys():
match_set.add_match( compared_pts[i][k], reference_pts[k], 1 )
match_set.save_to_file( output_files[i] )
print "Saved to %s"%output_files[i]
def main(args):
output_files = []
compared_images = []
compared_windows = []
for i, compared_image_file in enumerate(args.compared_images):
if args.output_directory:
directory = args.output_directory
else:
directory = os.path.dirname(args.compared_images[0])
print "No output directory specified. Defaulting to %s" % directory
if not os.path.exists(directory):
os.makedirs(directory)
if args.output_prefix:
prefix = args.output_prefix
else:
prefix_c = os.path.splitext(os.path.basename(args.compared_images[i]))[0]
prefix_r = os.path.splitext(os.path.basename(args.reference_image))[0]
prefix = "%s_TO_%s" % (prefix_c, prefix_r)
print "No output prefix selected. Defaulting to %s" % prefix
output_file = "%s/%s.matches" % (directory, prefix)
output_files.append(output_file)
compared_image = cv.LoadImage(args.compared_images[i])
compared_images.append(compared_image)
compared_window = ClickWindow(compared_image, args.compared_zoom_out, i)
compared_windows.append(compared_window)
compared_pts.append({})
if args.input_points_file:
point_set = PointSet()
point_set.read_from_file(args.input_points_file)
for i, pt in enumerate(point_set.get_points()):
reference_pts[i] = pt
reference_image = cv.LoadImage(args.reference_image)
reference_window = ClickWindow(reference_image, args.reference_zoom_out, -1)
update_all_windows()
# Tile
y = reference_window.size()[1]
x = 0
for win in compared_windows:
if x + win.size()[0] >= SCREEN_WIDTH:
x = 0
y += win.size()[1]
print "Moving window %d to %f,%f" % (win.id, x, y)
win.move(x, y)
x += win.size()[0]
global mode
global selected_index
while True:
cont = update_all_windows()
if not cont:
break
if reference_window.click_pt:
print "Updating reference_window click_pt"
key = safe_max(reference_pts.keys()) + 1
reference_pts[key] = reference_window.click_pt
selected_index = key
reference_window.clear_click_pt()
for i, compared_window in enumerate(compared_windows):
if compared_window.click_pt and selected_index > -1:
print selected_index
compared_pts[i][selected_index] = compared_window.click_pt
compared_window.clear_click_pt()
if save_flag:
for i in range(len(compared_windows)):
match_set = MatchSet(args.compared_images[i], args.reference_image)
for k in compared_pts[i].keys():
match_set.add_match(compared_pts[i][k], reference_pts[k], 1)
match_set.save_to_file(output_files[i])
print "Saved to %s" % output_files[i]
