def plot_kp(img, mode='string'):
img = ImageObject(img)
img = image_module.convert_to_pgm(img)
img = make_keypoints(img)
loc, desc = get_descriptors(img)
im = get_image_as_array(img)
sift.plot_features(im,loc)
image_module.remove_temp_files_img(img)
def get_kpm_string(img1,img2,mode='string',less=0, from_index=-1, to_index=-1):
img1 = ImageObject(img1)
img2 = ImageObject(img2)
i1,i2,m,q,mp = get_kpm(img1,img2, mode,less, from_index, to_index)
image_module.remove_temp_files_img(img1)
image_module.remove_temp_files_img(img2)
return i1,i2,m,q,mp
def plot_kpm(img1,img2,mode='string',less=0, from_index=-1, to_index=-1):
if mode == 'string':
img1 = ImageObject(img1)
img2 = ImageObject(img2)
im1, im2, matchscores,qom,MatchPercent = get_kpm(img1,img2, mode,less, from_index, to_index)
loc1, desc1 = get_descriptors(img1)
loc2, desc2 = get_descriptors(img2)
sift.plot_matches(im1,im2,loc1,loc2,matchscores)
image_module.remove_temp_files_img(img1)
image_module.remove_temp_files_img(img2)
def delete_short_scenes(self,fps,program_mode):
# tul rovid sceneket(clusterek) torlom a clusterek kozul
MIN_SCENE_LENGTH = None
if program_mode == 'scenes':
MIN_SCENE_LENGTH = settings.MIN_SCENE_LENGTH_MODE_SCENECUT
elif program_mode == 'joined':
MIN_SCENE_LENGTH = settings.MIN_SCENE_LENGTH_MODE_JOINCUT
flags_delete = []
for clCounter, cluster in enumerate(self.clusters):
if len(cluster)>0:
orderNum1 = cluster[0].get_only_num()
orderNum2 = cluster[-1].get_only_num()
time_diff_msec = int(orderNum2 - orderNum1)*(1.0/eval_float(fps))*1000.0
# print MIN_SCENE_LENGTH*1000.0
if MIN_SCENE_LENGTH*1000.0 >= time_diff_msec: flags_delete.append(clCounter)
for del_num in reversed(flags_delete):
for img in self.clusters[del_num]:
remove_temp_files_img(img)
# remove_file_img(img)
del self.clusters[del_num]
