video_demo.py

#! /usr/bin/env python
# coding=utf-8
#================================================================
#   Copyright (C) 2019 * Ltd. All rights reserved.
#
#   Editor      : VIM
#   File name   : video_demo.py
#   Author      : YunYang1994
#   Created date: 2019-07-12 19:36:53
#   Description :
#
#================================================================

import cv2
import time
import numpy as np
import core.utils as utils
import tensorflow as tf
from core.yolov3 import YOLOv3, decode


video_path      = "./docs/road.mp4"
# video_path      = 0
num_classes     = 80
input_size      = 416

input_layer  = tf.keras.layers.Input([input_size, input_size, 3])
feature_maps = YOLOv3(input_layer)

bbox_tensors = []
for i, fm in enumerate(feature_maps):
    bbox_tensor = decode(fm, i)
    bbox_tensors.append(bbox_tensor)

model = tf.keras.Model(input_layer, bbox_tensors)
utils.load_weights(model, "./yolov3.weights")
model.summary()
vid = cv2.VideoCapture(video_path)
while True:
    return_value, frame = vid.read()
    if return_value:
        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    else:
        raise ValueError("No image!")
    frame_size = frame.shape[:2]
    image_data = utils.image_preporcess(np.copy(frame), [input_size, input_size])
    image_data = image_data[np.newaxis, ...].astype(np.float32)

    prev_time = time.time()
    pred_bbox = model.predict_on_batch(image_data)
    curr_time = time.time()
    exec_time = curr_time - prev_time

    pred_bbox = [tf.reshape(x, (-1, tf.shape(x)[-1])) for x in pred_bbox]
    pred_bbox = tf.concat(pred_bbox, axis=0)
    bboxes = utils.postprocess_boxes(pred_bbox, frame_size, input_size, 0.3)
    bboxes = utils.nms(bboxes, 0.45, method='nms')
    image = utils.draw_bbox(frame, bboxes)

    result = np.asarray(image)
    info = "time: %.2f ms" %(1000*exec_time)
    cv2.putText(result, text=info, org=(50, 70), fontFace=cv2.FONT_HERSHEY_SIMPLEX,
                fontScale=1, color=(255, 0, 0), thickness=2)
    cv2.namedWindow("result", cv2.WINDOW_AUTOSIZE)
    result = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
    cv2.imshow("result", result)
    if cv2.waitKey(1) & 0xFF == ord('q'): break