update files
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7 changed files with 87 additions and 169 deletions
86
Server/WebsocketServer/main.py
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86
Server/WebsocketServer/main.py
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import websockets
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import asyncio
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import numpy as np
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from ultralytics import YOLO
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import cv2
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classNames = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat",
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"traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat",
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"dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella",
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"handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat",
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"baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup",
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"fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli",
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"carrot", "hot dog", "pizza", "donut", "cake", "chair", "sofa", "pottedplant", "bed",
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"diningtable", "toilet", "tvmonitor", "laptop", "mouse", "remote", "keyboard", "cell phone",
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"microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors",
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"teddy bear", "hair drier", "toothbrush"
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]
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model = YOLO('yolov8s.pt') # Load an official Detect model
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async def handle_connection(websocket, path):
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print(f"Connection from: {path}")
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try:
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while True:
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raw_data = await websocket.recv()
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nparr = np.frombuffer(raw_data, np.uint8).reshape((480, 640, 3))
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# frame = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
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frame = cv2.cvtColor(nparr, cv2.COLOR_BGR2RGB)
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# Perform object detection
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results = model.track(frame, persist=True)
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for r in results:
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lines = ""
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boxes = r.boxes
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for box in boxes:
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if box.cls[0].item() == 0 and not box.id is None:
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# bounding box
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id = box.id.int().cpu().tolist()
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# x1, y1, x2, y2 = box.xyxy[0]
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# # 2.08333 = 1/480 * 1000 or normalize, then save 4 sig-figures and cast to int
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# # 1.5625 = 1/640 * 1000 or normalize, then save 4 sig-figures and cast to int
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# x1, x2, y1, y2 = int(x1), int(x2), int(y1), int(y2)
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# # put box in cam
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# cv2.rectangle(frame, (x1, y1), (x2, y2), (255, 0, 255), 3)
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# # class name
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# cls = int(box.cls[0])
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# # object details
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# org = [x1, y1]
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# org2 = [x1, y1+50]
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# font = cv2.FONT_HERSHEY_SIMPLEX
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# fontScale = 1
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# color = (255, 0, 0)
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# color_w = (255, 255, 255)
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# thickness = 2
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# cv2.putText(frame, classNames[cls], org, font, fontScale, color, thickness)
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# cv2.putText(frame, str(id), org2, font, fontScale, color_w, thickness)
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x1, y1, x2, y2 = box.xyxyn[0]
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x1, y1, x2, y2 = int(x1 * 1000), int(y1 * 1000), int(x2 * 1000), int(y2 * 1000)
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lines += f"{id} {x1}:{y1} {x2}:{y2}\n"
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# cv2.imshow('Webcam', frame)
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# if cv2.waitKey(1) == ord('q'):
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# break
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ret = lines.encode('utf-8')
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await websocket.send(ret)
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except websockets.exceptions.ConnectionClosed:
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print(f"Client disconnected: {path}")
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if __name__ == "__main__":
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start_server = websockets.serve(handle_connection, "0.0.0.0", 6543)
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asyncio.get_event_loop().run_until_complete(start_server)
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asyncio.get_event_loop().run_forever()
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7
face_tracking_demo/Cargo.lock
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7
face_tracking_demo/Cargo.lock
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# This file is automatically @generated by Cargo.
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# It is not intended for manual editing.
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version = 3
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[[package]]
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name = "face_tracking_demo"
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version = "0.1.0"
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[package]
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name = "face_tracking_demo"
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version = "0.1.0"
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edition = "2021"
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[dependencies]
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use opencv::{
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core, highgui, prelude::*, video::{self, TrackerDaSiamRPN_Params}, videoio
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};
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fn main() -> opencv::Result<()> {
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let window = "window";
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highgui::named_window(window, highgui::WINDOW_AUTOSIZE)?;
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// let mut cam = opencv::videoio::VideoCapture::new(0, opencv::videoio::CAP_ANY)?; // 0 is the default camera
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let mut cap = videoio::VideoCapture::from_file(r"C:\Users\nicho\Desktop\tmp\test-vid.mp4", videoio::CAP_ANY)?;
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let opened = opencv::videoio::VideoCapture::is_opened(&cap)?;
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if !opened {
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panic!("Unable to open default camera!");
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}
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let mut frame = core::Mat::default();
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// let mut tracker = opencv::video::TrackerMIL::create(opencv::video::TrackerMIL_Params::default().unwrap())?;
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let mut tracker = opencv::video::TrackerDaSiamRPN::create(&opencv::video::TrackerDaSiamRPN_Params::default().unwrap())?;
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// let mut tracker = opencv::video::TrackerGOTURN::create(&opencv::video::TrackerGOTURN_Params::default().unwrap())?;
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// let mut tracker = opencv::video::TrackerNano::create(&opencv::video::TrackerNano_Params::default().unwrap())?;
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// let mut tracker = opencv::tracking::TrackerKCF::create()
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// let mut tracker = opencv::alphamat
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let mut bounding_box = core::Rect::new(0, 0, 0, 0);
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let mut update_tracker = false;
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let mut frame_counter: u64 = 0;
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loop {
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// cam.read(&mut frame)?;
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cap.read(&mut frame)?;
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if !update_tracker {
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bounding_box = highgui::select_roi(window, &frame, false, false, true)?;
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let _ = tracker.init(&frame, bounding_box);
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update_tracker = true;
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}
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let key = highgui::wait_key(10)?;
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if key > 0 {
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if key == 27 {
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break; // 'ESC' to quit
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} else if key == 32 {
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// 'SPACE' to select an object to track
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}
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}
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if update_tracker && frame_counter % 3 == 0 {
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let _ = tracker.update(&frame, &mut bounding_box);
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}
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frame_counter += 1;
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println!("box is: {}, {}", bounding_box.x, bounding_box.y);
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opencv::imgproc::rectangle(&mut frame, bounding_box, core::Scalar::new(255.0, 0.0, 0.0, 0.0), 2, 8, 0)?;
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if frame.size()?.width > 0 {
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highgui::imshow(window, &mut frame)?;
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}
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}
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Ok(())
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}
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import cv2
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import sys
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(major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')
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if __name__ == '__main__' :
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# Set up tracker.
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# Instead of MIL, you can also use
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tracker_types = ['BOOSTING', 'MIL','KCF', 'TLD', 'MEDIANFLOW', 'GOTURN', 'MOSSE', 'CSRT']
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tracker_type = tracker_types[2]
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if int(minor_ver) < 3:
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tracker = cv2.Tracker_create(tracker_type)
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else:
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if tracker_type == 'BOOSTING':
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tracker = cv2.TrackerBoosting_create()
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if tracker_type == 'MIL':
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tracker = cv2.TrackerMIL_create()
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if tracker_type == 'KCF':
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tracker = cv2.TrackerKCF_create()
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if tracker_type == 'TLD':
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tracker = cv2.TrackerTLD_create()
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if tracker_type == 'MEDIANFLOW':
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tracker = cv2.TrackerMedianFlow_create()
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if tracker_type == 'GOTURN':
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tracker = cv2.TrackerGOTURN_create()
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if tracker_type == 'MOSSE':
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tracker = cv2.TrackerMOSSE_create()
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if tracker_type == "CSRT":
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tracker = cv2.TrackerCSRT_create()
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# Read video
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video = cv2.VideoCapture("videos/chaplin.mp4")
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# Exit if video not opened.
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if not video.isOpened():
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print("Could not open video")
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sys.exit()
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# Read first frame.
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ok, frame = video.read()
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if not ok:
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print('Cannot read video file')
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sys.exit()
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# Define an initial bounding box
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bbox = (287, 23, 86, 320)
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# Uncomment the line below to select a different bounding box
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bbox = cv2.selectROI(frame, False)
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# Initialize tracker with first frame and bounding box
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ok = tracker.init(frame, bbox)
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while True:
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# Read a new frame
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ok, frame = video.read()
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if not ok:
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break
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# Start timer
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timer = cv2.getTickCount()
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# Update tracker
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ok, bbox = tracker.update(frame)
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# Calculate Frames per second (FPS)
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fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer);
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# Draw bounding box
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if ok:
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# Tracking success
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p1 = (int(bbox[0]), int(bbox[1]))
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p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3]))
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cv2.rectangle(frame, p1, p2, (255,0,0), 2, 1)
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else :
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# Tracking failure
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cv2.putText(frame, "Tracking failure detected", (100,80), cv2.FONT_HERSHEY_SIMPLEX, 0.75,(0,0,255),2)
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# Display tracker type on frame
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cv2.putText(frame, tracker_type + " Tracker", (100,20), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50),2);
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# Display FPS on frame
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cv2.putText(frame, "FPS : " + str(int(fps)), (100,50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50), 2);
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# Display result
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cv2.imshow("Tracking", frame)
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# Exit if ESC pressed
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k = cv2.waitKey(1) & 0xff
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if k == 27 : break
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@ -1 +1 @@
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Subproject commit 3cb560093c6de5794cb654a46fb6dd12c8377042
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Subproject commit e59025f645b13236cfd88e5f5e77b6692a3fc690
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