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]