update files

Server/WebsocketServer/main.py

@@ -0,0 +1,86 @@
+import websockets
+import asyncio
+import numpy as np
+from ultralytics import YOLO
+import cv2
+
+classNames = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat",
+              "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat",
+              "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella",
+              "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat",
+              "baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup",
+              "fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli",
+              "carrot", "hot dog", "pizza", "donut", "cake", "chair", "sofa", "pottedplant", "bed",
+              "diningtable", "toilet", "tvmonitor", "laptop", "mouse", "remote", "keyboard", "cell phone",
+              "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors",
+              "teddy bear", "hair drier", "toothbrush"
+              ]
+
+model = YOLO('yolov8s.pt')  # Load an official Detect model
+
+async def handle_connection(websocket, path):
+    print(f"Connection from: {path}")
+    try: 
+        while True:
+            raw_data = await websocket.recv()
+
+            nparr = np.frombuffer(raw_data, np.uint8).reshape((480, 640, 3))
+
+            # frame = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+            frame = cv2.cvtColor(nparr, cv2.COLOR_BGR2RGB)
+
+            # Perform object detection
+            results = model.track(frame, persist=True)
+
+            for r in results:
+                lines = ""
+                boxes = r.boxes
+                for box in boxes:
+                    if box.cls[0].item() == 0 and not box.id is None:
+                        # bounding box
+                        id = box.id.int().cpu().tolist()
+                        # x1, y1, x2, y2 = box.xyxy[0]
+                        # #  2.08333 = 1/480 * 1000 or normalize, then save 4 sig-figures and cast to int
+                        # #  1.5625 = 1/640 * 1000 or normalize, then save 4 sig-figures and cast to int
+
+                        # x1, x2, y1, y2 = int(x1), int(x2), int(y1), int(y2)
+
+                        # # put box in cam
+                        # cv2.rectangle(frame, (x1, y1), (x2, y2), (255, 0, 255), 3)
+
+                        # # class name
+                        # cls = int(box.cls[0])
+
+                        # # object details
+                        # org = [x1, y1]
+                        # org2 = [x1, y1+50]
+                        # font = cv2.FONT_HERSHEY_SIMPLEX
+                        # fontScale = 1
+                        # color = (255, 0, 0)
+                        # color_w = (255, 255, 255)
+                        # thickness = 2
+
+                        # cv2.putText(frame, classNames[cls], org, font, fontScale, color, thickness)
+                        # cv2.putText(frame, str(id), org2, font, fontScale, color_w, thickness)
+
+                        x1, y1, x2, y2 = box.xyxyn[0]
+                        x1, y1, x2, y2 = int(x1 * 1000), int(y1 * 1000), int(x2 * 1000), int(y2 * 1000)
+                        lines += f"{id} {x1}:{y1} {x2}:{y2}\n"
+
+                # cv2.imshow('Webcam', frame)
+                # if cv2.waitKey(1) == ord('q'):
+                #     break
+
+            ret = lines.encode('utf-8')
+
+            await websocket.send(ret)
+
+    except websockets.exceptions.ConnectionClosed:
+        print(f"Client disconnected: {path}")
+
+
+if __name__ == "__main__":
+    start_server = websockets.serve(handle_connection, "0.0.0.0", 6543)
+    asyncio.get_event_loop().run_until_complete(start_server)
+
+    asyncio.get_event_loop().run_forever()

face_tracking_demo/Cargo.lock

@@ -1,7 +0,0 @@
-# This file is automatically @generated by Cargo.
-# It is not intended for manual editing.
-version = 3
-
-[[package]]
-name = "face_tracking_demo"
-version = "0.1.0"

face_tracking_demo/Cargo.toml

@@ -1,6 +0,0 @@
-[package]
-name = "face_tracking_demo"
-version = "0.1.0"
-edition = "2021"
-
-[dependencies]

face_tracking_demo/src/opencv_main.rs

@@ -1,61 +0,0 @@
-use opencv::{
-    core, highgui, prelude::*, video::{self, TrackerDaSiamRPN_Params}, videoio
-};
-
-fn main() -> opencv::Result<()> {
-    let window = "window";
-    highgui::named_window(window, highgui::WINDOW_AUTOSIZE)?;
-
-    // let mut cam = opencv::videoio::VideoCapture::new(0, opencv::videoio::CAP_ANY)?;  // 0 is the default camera
-    let mut cap = videoio::VideoCapture::from_file(r"C:\Users\nicho\Desktop\tmp\test-vid.mp4", videoio::CAP_ANY)?;
-    let opened = opencv::videoio::VideoCapture::is_opened(&cap)?;
-    if !opened {
-        panic!("Unable to open default camera!");
-    }
-
-    let mut frame = core::Mat::default();
-    // let mut tracker = opencv::video::TrackerMIL::create(opencv::video::TrackerMIL_Params::default().unwrap())?;
-    let mut tracker = opencv::video::TrackerDaSiamRPN::create(&opencv::video::TrackerDaSiamRPN_Params::default().unwrap())?;
-    // let mut tracker = opencv::video::TrackerGOTURN::create(&opencv::video::TrackerGOTURN_Params::default().unwrap())?;
-    // let mut tracker = opencv::video::TrackerNano::create(&opencv::video::TrackerNano_Params::default().unwrap())?;
-    // let mut tracker = opencv::tracking::TrackerKCF::create()
-    // let mut tracker = opencv::alphamat
-    let mut bounding_box = core::Rect::new(0, 0, 0, 0);
-    let mut update_tracker = false;
-    let mut frame_counter: u64 = 0;
-
-    loop {
-        // cam.read(&mut frame)?;
-        cap.read(&mut frame)?;
-
-        if !update_tracker {
-            bounding_box = highgui::select_roi(window, &frame, false, false, true)?;
-            let _ = tracker.init(&frame, bounding_box);
-            update_tracker = true;
-        }
-
-        let key = highgui::wait_key(10)?;
-
-        if key > 0 {
-            if key == 27 {
-                break;  // 'ESC' to quit
-            } else if key == 32 {
-                // 'SPACE' to select an object to track
-            }
-        }
-
-        if update_tracker && frame_counter % 3 == 0 {
-            let _ = tracker.update(&frame, &mut bounding_box);
-        }
-        frame_counter += 1;
-
-        println!("box is: {}, {}", bounding_box.x, bounding_box.y);
-        opencv::imgproc::rectangle(&mut frame, bounding_box, core::Scalar::new(255.0, 0.0, 0.0, 0.0), 2, 8, 0)?;
-
-        if frame.size()?.width > 0 {
-            highgui::imshow(window, &mut frame)?;
-        }
-    }
-
-    Ok(())
-}

face_tracking_demo/test.py

@@ -1,94 +0,0 @@
-
-import cv2
-import sys
- 
-(major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')
- 
-if __name__ == '__main__' :
- 
-    # Set up tracker.
-    # Instead of MIL, you can also use
- 
-    tracker_types = ['BOOSTING', 'MIL','KCF', 'TLD', 'MEDIANFLOW', 'GOTURN', 'MOSSE', 'CSRT']
-    tracker_type = tracker_types[2]
- 
-    if int(minor_ver) < 3:
-        tracker = cv2.Tracker_create(tracker_type)
-    else:
-        if tracker_type == 'BOOSTING':
-            tracker = cv2.TrackerBoosting_create()
-        if tracker_type == 'MIL':
-            tracker = cv2.TrackerMIL_create()
-        if tracker_type == 'KCF':
-            tracker = cv2.TrackerKCF_create()
-        if tracker_type == 'TLD':
-            tracker = cv2.TrackerTLD_create()
-        if tracker_type == 'MEDIANFLOW':
-            tracker = cv2.TrackerMedianFlow_create()
-        if tracker_type == 'GOTURN':
-            tracker = cv2.TrackerGOTURN_create()
-        if tracker_type == 'MOSSE':
-            tracker = cv2.TrackerMOSSE_create()
-        if tracker_type == "CSRT":
-            tracker = cv2.TrackerCSRT_create()
- 
-    # Read video
-    video = cv2.VideoCapture("videos/chaplin.mp4")
- 
-    # Exit if video not opened.
-    if not video.isOpened():
-        print("Could not open video")
-        sys.exit()
- 
-    # Read first frame.
-    ok, frame = video.read()
-    if not ok:
-        print('Cannot read video file')
-        sys.exit()
-     
-    # Define an initial bounding box
-    bbox = (287, 23, 86, 320)
- 
-    # Uncomment the line below to select a different bounding box
-    bbox = cv2.selectROI(frame, False)
- 
-    # Initialize tracker with first frame and bounding box
-    ok = tracker.init(frame, bbox)
- 
-    while True:
-        # Read a new frame
-        ok, frame = video.read()
-        if not ok:
-            break
-         
-        # Start timer
-        timer = cv2.getTickCount()
- 
-        # Update tracker
-        ok, bbox = tracker.update(frame)
- 
-        # Calculate Frames per second (FPS)
-        fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer);
- 
-        # Draw bounding box
-        if ok:
-            # Tracking success
-            p1 = (int(bbox[0]), int(bbox[1]))
-            p2 = (int(bbox[0] + bbox[2]), int(bbox[1] + bbox[3]))
-            cv2.rectangle(frame, p1, p2, (255,0,0), 2, 1)
-        else :
-            # Tracking failure
-            cv2.putText(frame, "Tracking failure detected", (100,80), cv2.FONT_HERSHEY_SIMPLEX, 0.75,(0,0,255),2)
- 
-        # Display tracker type on frame
-        cv2.putText(frame, tracker_type + " Tracker", (100,20), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50),2);
-     
-        # Display FPS on frame
-        cv2.putText(frame, "FPS : " + str(int(fps)), (100,50), cv2.FONT_HERSHEY_SIMPLEX, 0.75, (50,170,50), 2);
- 
-        # Display result
-        cv2.imshow("Tracking", frame)
- 
-        # Exit if ESC pressed
-        k = cv2.waitKey(1) & 0xff
-        if k == 27 : break

joystick-controller-client

@@ -1 +1 @@
-Subproject commit 3cb560093c6de5794cb654a46fb6dd12c8377042
+Subproject commit e59025f645b13236cfd88e5f5e77b6692a3fc690