detection_demo.py

#================================================================
#
#   File name   : detection_demo.py
#   Author      : PyLessons
#   Created date: 2020-07-27
#   Website     : https://pylessons.com/
#   GitHub      : https://github.com/pythonlessons/TensorFlow-2.x-YOLOv3
#   Description : object detection image and video example
#
#================================================================
import os
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
import cv2
import numpy as np
import tensorflow as tf
#from yolov3.yolov3 import Create_Yolov3
from yolov3.yolov4 import Create_Yolo
from yolov3.utils import load_yolo_weights, detect_image, detect_video, detect_realtime
from yolov3.configs import *

if YOLO_TYPE == "yolov4":
    Darknet_weights = YOLO_V4_TINY_WEIGHTS if TRAIN_YOLO_TINY else YOLO_V4_WEIGHTS
if YOLO_TYPE == "yolov3":
    Darknet_weights = YOLO_V3_TINY_WEIGHTS if TRAIN_YOLO_TINY else YOLO_V3_WEIGHTS

image_path   = "./IMAGES/kite.jpg"
video_path   = "./IMAGES/test.mp4"

yolo = Create_Yolo(input_size=YOLO_INPUT_SIZE)
load_yolo_weights(yolo, Darknet_weights) # use Darknet weights

#detect_image(yolo, image_path, '', input_size=YOLO_INPUT_SIZE, show=True, rectangle_colors=(255,0,0))
detect_video(yolo, video_path, '', input_size=YOLO_INPUT_SIZE, show=True, rectangle_colors=(255,0,0))
#detect_realtime(yolo, '', input_size=YOLO_INPUT_SIZE, show=True, rectangle_colors=(255, 0, 0))