MinaGabriel/video_http_stream_yolo_flask.py

## video_http_stream_yolo_flask.py
import time
from absl import app, flags, logging
from absl.flags import FLAGS
import cv2
import tensorflow as tf
from yolov3_tf2.models import (
    YoloV3, YoloV3Tiny
)
from yolov3_tf2.dataset import transform_images
from yolov3_tf2.utils import draw_outputs

from flask import Flask, render_template, Response

app = Flask(__name__)


@app.route('/')
def index():
    # rendering web page
    # this ill constantly call url_for:
    return render_template('index.html')


def gen():
    physical_devices = tf.config.experimental.list_physical_devices('GPU')
    for physical_device in physical_devices:
        tf.config.experimental.set_memory_growth(physical_device, True)

    yolo = YoloV3(classes=80)

    yolo.load_weights('./checkpoints/yolov3.tf')
    logging.info('weights loaded')

    class_names = [c.strip() for c in open('./data/coco.names').readlines()]
    logging.info('classes loaded')

    times = []

    vid = cv2.VideoCapture('http://192.168.68.122:8080/')

    while True:
        _, frame = vid.read()

        # if frame is None:
        #     logging.warning("Empty Frame")
        #     time.sleep(0.1)
        #     continue

        img_in = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        img_in = tf.expand_dims(img_in, 0)
        img_in = transform_images(img_in, 416)

        t1 = time.time()
        boxes, scores, classes, nums = yolo.predict(img_in)
        t2 = time.time()
        times.append(t2 - t1)
        times = times[-20:]

        frame = draw_outputs(frame, (boxes, scores, classes, nums), class_names)
        frame = cv2.putText(frame, "Time: {:.2f}ms".format(sum(times) / len(times) * 1000), (0, 30),
                            cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 2)

        _, jpeg = cv2.imencode('.jpg', frame)
        new_frame = jpeg.tobytes()
        yield (b'--frame\r\n'
               b'Content-Type: image/jpeg\r\n\r\n' + new_frame + b'\r\n\r\n')


@app.route('/video_feed')
def video_feed():
    return Response(gen(),
                    mimetype='multipart/x-mixed-replace; boundary=frame')


if __name__ == "__main__":
    app.run(host='192.168.68.126', port='5000', debug=True)


    ###############HTML PAGE########################

    <!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="utf-8">
    <meta name="viewport"
          content="width=device-width, initial-scale=1, user-scalable=yes">

    <link href="/static/css/style.css" rel="stylesheet">
    <title></title>
</head>
<body>
<h1>Detection</h1>
<img id="bg" src="{{ url_for('video_feed') }}">

</body>
</html>
	import time
	from absl import app, flags, logging
	from absl.flags import FLAGS
	import cv2
	import tensorflow as tf
	from yolov3_tf2.models import (
	YoloV3, YoloV3Tiny
	)
	from yolov3_tf2.dataset import transform_images
	from yolov3_tf2.utils import draw_outputs

	from flask import Flask, render_template, Response

	app = Flask(__name__)


	@app.route('/')
	def index():
	# rendering web page
	# this ill constantly call url_for:
	return render_template('index.html')


	def gen():
	physical_devices = tf.config.experimental.list_physical_devices('GPU')
	for physical_device in physical_devices:
	tf.config.experimental.set_memory_growth(physical_device, True)

	yolo = YoloV3(classes=80)

	yolo.load_weights('./checkpoints/yolov3.tf')
	logging.info('weights loaded')

	class_names = [c.strip() for c in open('./data/coco.names').readlines()]
	logging.info('classes loaded')

	times = []

	vid = cv2.VideoCapture('http://192.168.68.122:8080/')

	while True:
	_, frame = vid.read()

	# if frame is None:
	# logging.warning("Empty Frame")
	# time.sleep(0.1)
	# continue

	img_in = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
	img_in = tf.expand_dims(img_in, 0)
	img_in = transform_images(img_in, 416)

	t1 = time.time()
	boxes, scores, classes, nums = yolo.predict(img_in)
	t2 = time.time()
	times.append(t2 - t1)
	times = times[-20:]

	frame = draw_outputs(frame, (boxes, scores, classes, nums), class_names)
	frame = cv2.putText(frame, "Time: {:.2f}ms".format(sum(times) / len(times) * 1000), (0, 30),
	cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 2)

	_, jpeg = cv2.imencode('.jpg', frame)
	new_frame = jpeg.tobytes()
	yield (b'--frame\r\n'
	b'Content-Type: image/jpeg\r\n\r\n' + new_frame + b'\r\n\r\n')


	@app.route('/video_feed')
	def video_feed():
	return Response(gen(),
	mimetype='multipart/x-mixed-replace; boundary=frame')


	if __name__ == "__main__":
	app.run(host='192.168.68.126', port='5000', debug=True)


	###############HTML PAGE########################

	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="utf-8">
	<meta name="viewport"
	content="width=device-width, initial-scale=1, user-scalable=yes">

	<link href="/static/css/style.css" rel="stylesheet">
	<title></title>
	</head>
	<body>
	<h1>Detection</h1>
	<img id="bg" src="{{ url_for('video_feed') }}">

	</body>
	</html>