added some working files

.gitignore

@@ -1,3 +1,7 @@
+runs/*
+*.pt
+*.mp4
+
 # ---> Python
 # Byte-compiled / optimized / DLL files
 __pycache__/

Server/sockets_controller.py

@@ -41,6 +41,8 @@ async def handle_client(websocket, path):
                 await update_from_packet(command)
     except websockets.exceptions.ConnectionClosed:
         print("Connection closed with: ", websocket.remote_address)
+    except Exception as e:
+        print(f"There was an error: {e}")
     finally:
         print("closing websocket")
         del socket_connections[websocket]

YOLO python/basic-tracking.py

@@ -0,0 +1,14 @@
+from ultralytics import YOLO 
+
+
+# Load an official or custom model
+# model = YOLO('yolov8n.pt')  # Load an official Detect model
+model = YOLO('yolov8s.pt')  # Load an official Detect model
+# model = YOLO('yolov8n-seg.pt')  # Load an official Segment model
+# model = YOLO('yolov8n-pose.pt')  # Load an official Pose model
+# model = YOLO('path/to/best.pt')  # Load a custom trained model
+
+
+# Run inference on 'bus.jpg' with arguments
+for i in model.predict('D:\Projects\FaceTrackingCamerav3\YOLO python\kevin-center-camera-position.mp4', show=True, save=True, save_frames=True, save_txt=True, conf=0.5, stream=True):
+    continue

YOLO python/dataset/detect.yaml

@@ -0,0 +1,6 @@
+train: images/train
+val: images/val
+test: images/test
+
+names:
+  0: Person

YOLO python/webcam-test.py

@@ -0,0 +1,67 @@
+# source from https://dipankarmedh1.medium.com/real-time-object-detection-with-yolo-and-webcam-enhancing-your-computer-vision-skills-861b97c78993
+
+from ultralytics import YOLO
+import cv2
+import math 
+
+# model
+model = YOLO("yolov8x.pt")
+
+# start webcam
+cap = cv2.VideoCapture(0)
+cap.set(3, 640)
+cap.set(4, 480)
+
+# object classes
+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"
+              ]
+
+
+while True:
+    success, img = cap.read()
+    results = model.track(img, persist=True, stream=True)
+
+    # coordinates
+    for r in results:
+        boxes = r.boxes
+
+        for box in boxes:
+            # bounding box
+            x1, y1, x2, y2 = box.xyxy[0]
+            x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2) # convert to int values
+
+            # put box in cam
+            cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 255), 3)
+
+            # confidence
+            confidence = math.ceil((box.conf[0]*100))/100
+            print("Confidence --->",confidence)
+
+            # class name
+            cls = int(box.cls[0])
+            print("Class name -->", classNames[cls])
+
+            # object details
+            org = [x1, y1]
+            font = cv2.FONT_HERSHEY_SIMPLEX
+            fontScale = 1
+            color = (255, 0, 0)
+            thickness = 2
+
+            cv2.putText(img, classNames[cls], org, font, fontScale, color, thickness)
+
+    cv2.imshow('Webcam', img)
+    if cv2.waitKey(1) == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()

face_tracking_demo/Cargo.lock

@@ -0,0 +1,7 @@
+# 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

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

face_tracking_demo/src/opencv_main.rs

@@ -0,0 +1,61 @@
+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

@@ -0,0 +1,94 @@
+
+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 f809c1dd283cc049d652338fb438de65abe40cfc
+Subproject commit 852e23dc7c92f80bf59f679803fb6344942bc138