print(" &&& finalprocess") time_ = time.time() finalprocess = Postprocessing(image, deepclasifier.vector_boxes) print(" &&& Time finalprocess elapsed : " + str(time.time() - time_) + " Seconds") print(" ") ''' pointed_image = finalprocess.container[0] boxed_image = finalprocess.image_drawed[0] ''' """ TEMPORAL """ image_draw = finalprocess.Draw_results(image, finalprocess.bboxes_after_nms) """ Generate Report """ print(" &&& Report information") time_ = time.time() geo_manager.pixel_conversion(finalprocess.bboxes_after_nms) print(" &&& Time Generate coord_array elapsed : " + str(time.time() - time_) + " Seconds") print(" ") Total_time = time.time() - image_time manager.Generate(name, paths[1], Total_time, len(finalprocess.bboxes_after_nms)) manager.Generate_csv(geo_manager.coord_array, name) print(" ") finish = input(" Push any key to finish ") #exit()
if flag_cfp: """ Reclasification point """ flag_reclas = deepclasifier.reclasification(subset_image) if flag_reclas: """ Object Check Detector """ deepclasifier.check_detector(point, box, score) bar.update(item) print(time.time() - curr) except KeyboardInterrupt: break Total_time = time.time() - image_time """ Postprocessing """ finalprocess = Postprocessing(image.copy(), deepclasifier.vector_boxes) count = finalprocess.counter pointed_image = finalprocess.container[0] boxed_image = finalprocess.image_drawed[0] """ Generate report """ manager.Generate(name, paths[1], Total_time, count, boxed_image, pointed_image) manager.Generate_csv(deepclasifier.vector_boxes, name) finish = input("Push any key to finish ") #exit()