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()
