Server/WebsocketServer/main.py

@@ -16,22 +16,18 @@ classNames = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "trai
               "teddy bear", "hair drier", "toothbrush"
               ]
 
-model = YOLO('yolov8m.pt')  # Load an official Detect model
+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()
-            print(f"downloaded bytes: {len(raw_data)}")
 
-            # nparr = np.frombuffer(decoded_bytes, np.uint8).reshape((480, 640, 3))
-            nparr = np.frombuffer(raw_data, dtype=np.uint8)
+            nparr = np.frombuffer(raw_data, np.uint8).reshape((480, 640, 3))
 
-            frame = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-
-            # frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
-            cv2.imshow("from_remote", frame)
+            # frame = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+            frame = cv2.cvtColor(nparr, cv2.COLOR_BGR2RGB)
 
             # Perform object detection
             results = model.track(frame, persist=True)
@@ -77,8 +73,6 @@ async def handle_connection(websocket, path):
 
             ret = lines.encode('utf-8')
 
-            cv2.waitKey(1)
-
             await websocket.send(ret)
 
     except websockets.exceptions.ConnectionClosed:

YOLO python/webcam-test.py

@@ -5,13 +5,12 @@ import cv2
 import math 
 
 # model
-# model = YOLO("yolov8x.pt")
-model = YOLO('yolov8n_full_integer_quant_edgetpu.tflite', task="detect")  # Load an official Detect model
+model = YOLO("yolov8x.pt")
 
 # start webcam
 cap = cv2.VideoCapture(0)
 cap.set(3, 640)
-cap.set(4, 640)
+cap.set(4, 480)
 
 # object classes
 classNames = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat",
@@ -29,8 +28,6 @@ classNames = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "trai
 
 while True:
     success, img = cap.read()
-    # img = cv2.resize(img, (512, 512), cv2.INTER_AREA)
-    print(f"Image dimensions: {img.shape}")
     results = model.track(img, persist=True, stream=True)
 
     # coordinates

Yolo TFLite Export/main.py

@@ -1,6 +0,0 @@
-from ultralytics import YOLO 
-
-model = YOLO("yolov8n.pt")
-
-# model.export(format="onnx", simplify=True, int8=True)
-model.export(format="engine")

joystick-controller-client

@@ -1 +1 @@
-Subproject commit 0a47c7a9583148c101652e3772cf5ecad95d3092
+Subproject commit 66acd4698fcc997099ebc1ddc6f8e5ddd0e3579c