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server.py
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server.py
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# -*- coding: utf-8 -*-
import os
import json
import time
import logging
import argparse
import cv2 as cv
from flask import Flask, Response, request, render_template, send_from_directory
from detectors import Detector
from utils import Timer, draw_tracks, select_track
from trackers import CentroidTracker, CentroidKF_Tracker, SORT, IOUTracker
app = Flask(__name__, template_folder='./')
camera, fps = None, None
height, weight = None, None
model, tracker = None, None
tracks, trk_id = None, None
target_cid = None
timer = Timer()
def rescale(x, y, h, w):
x = int(x) / int(w) * width
y = int(y) / int(h) * height
return int(x), int(y)
def shutdown_server():
func = request.environ.get('werkzeug.server.shutdown')
if func is None:
raise RuntimeError('Not running with the Werkzeug Server')
func()
print('Release camera')
camera.release()
def capture():
global tracks
while True:
timer.tic()
ok, image = camera.read()
if ok:
image, bboxes, confidences, class_ids = model.detect(image)
tracks = tracker.update(bboxes, confidences, class_ids)
updated_image = draw_tracks(image.copy(), tracks, trk_id, target_cid)
duration = timer.toc(average=True)
cv.putText(updated_image, f'Frame: {tracker.frame_count}',
(1, 15), cv.FONT_HERSHEY_PLAIN, 1, (0, 0, 255), thickness=2)
cv.putText(updated_image, f'FPS (video): {fps:.2f}',
(1, 30), cv.FONT_HERSHEY_PLAIN, 1, (0, 0, 255), thickness=2)
cv.putText(updated_image, f'FPS (tracker): {(1/duration):.2f}',
(1, 45), cv.FONT_HERSHEY_PLAIN, 1, (0, 0, 255), thickness=2)
cv.putText(updated_image, f'Selected object ID: {trk_id}',
(1, 60), cv.FONT_HERSHEY_PLAIN, 1, (0, 0, 255), thickness=2)
ret, jpeg = cv.imencode('.jpg', updated_image)
frame = jpeg.tobytes()
else:
camera.release()
break
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n'
b'Content-Length: ' + f'{len(frame)}'.encode() + b'\r\n'
b'\r\n' + frame + b'\r\n')
@app.after_request
def add_header(response):
response.headers['Access-Control-Allow-Origin'] = '*'
return response
@app.route('/video_feed')
def video_feed():
return Response(capture(), mimetype='multipart/x-mixed-replace; boundary=frame')
@app.route('/data')
def data():
global tracks, trk_id
coor = request.args.get('coor')
if coor == 'deselect':
trk_id = None
logging.debug('Deselect')
else:
x, y, h, w = coor.split(',')
x, y = rescale(x, y, h, w)
trk_id = select_track(x, y, target_cid, tracks)
logging.debug(f'Click @ ({x}/{width}, {y}/{height}) @ frame {tracker.frame_count}, target: #{trk_id}')
return json.dumps({'success': True, 'target': trk_id}), 200, {'ContentType':'application/json'}
@app.route('/shutdown', methods=['GET'])
def shutdown():
shutdown_server()
return 'Flask server shutting down...'
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Object detections in input video using YOLOv3 trained on COCO dataset')
parser.add_argument('--camera', '-c', type=str,
required=True,
help='Input source')
parser.add_argument('--model', type=str,
default='yolo_weights/yolov3.cfg',
help='Path to model definition file.')
parser.add_argument('--weights', type=str,
default='yolo_weights/yolov3.weights',
help='Path to weights file.')
parser.add_argument('--class_names', type=str,
default='yolo_weights/coco.names',
help='Path to class label file.')
parser.add_argument('--tracker', '-t', type=str,
default='IOUTracker',
help='Tracker used to track objects. Options include [\'CentroidTracker\', \'CentroidKF_Tracker\', \'IOUTracker\', \'SORT\']. Default is \'IOUTracker\'')
parser.add_argument('--conf_thres', type=float,
default=0.6,
help='Object confidence threshold.')
parser.add_argument('--nms_thres', type=float,
default=0.4,
help='IoU thresshold for non-maximum suppression.')
parser.add_argument('--yolo_input_size', type=int,
default=512)
args = parser.parse_args()
logging.basicConfig(
format='%(levelname)s, %(asctime)s, %(message)s',
datefmt='%Y-%m-%d %H:%M:%S',
level=logging.DEBUG)
if args.tracker.lower() == 'centroidtracker':
tracker = CentroidTracker(
max_lost=10, tracker_output_format='mot_challenge')
elif args.tracker.lower() == 'centroidkf_tracker':
tracker = CentroidKF_Tracker(
max_lost=10, tracker_output_format='mot_challenge',
centroid_distance_threshold=50,
process_noise_scale=0.5,
measurement_noise_scale=0.5)
elif args.tracker.lower() == 'sort':
tracker = SORT(
max_lost=10, tracker_output_format='mot_challenge',
iou_threshold=0.2,
process_noise_scale=0.5,
measurement_noise_scale=0.5)
elif args.tracker.lower() == 'ioutracker':
tracker = IOUTracker(
max_lost=10, tracker_output_format='mot_challenge',
iou_threshold=0.2,
min_detection_confidence=0.4)
else:
raise NotImplementedError
if args.camera.startswith('/'):
camera = cv.VideoCapture(args.camera, cv.CAP_V4L)
else:
camera = cv.VideoCapture(args.camera)
camera.set(cv.CAP_PROP_BUFFERSIZE, 2)
fps = camera.get(cv.CAP_PROP_FPS)
height = camera.get(cv.CAP_PROP_FRAME_HEIGHT)
width = camera.get(cv.CAP_PROP_FRAME_WIDTH)
rescale_size = 800
if height > width:
width = rescale_size / height * width
height = rescale_size
else:
height = rescale_size / width * height
width = rescale_size
model = Detector(
model=args.model,
weights=args.weights,
class_names=args.class_names,
yolo_input_size=args.yolo_input_size,
conf_thres=args.conf_thres,
nms_thres=args.nms_thres
)
config = json.load(open('config.json', 'r'))
app.run(host='0.0.0.0', port=config['flask_port'], debug=True)