Added epoch 200 and real time detection

rpi/board-detector/paths.py

@@ -1,3 +1,3 @@
-model_path = "C:/Users/Laurent/Desktop/board-mate/rpi/assets/models/epoch-130.pt"
+model_path = "C:/Users/Laurent/Desktop/board-mate/rpi/assets/models/epoch-200.pt"
 #img_path = "./test/4.jpg"
 img_path = "../training/datasets/unified/train/images/WIN_20221220_11_27_27_Pro_jpg.rf.4f01cb68c8944ef1c4c7dc57847b4cd3.jpg"

rpi/board-detector/realtime_detect.py

@@ -0,0 +1,41 @@
+from ultralytics import YOLO
+from paths import *  # make sure model_path is defined here
+import cv2
+
+if __name__ == "__main__":
+
+    print("Initializing model...")
+    model = YOLO(model_path)
+
+    print("Initializing camera...")
+    cap = cv2.VideoCapture(0)
+    cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
+    cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
+    cap.set(cv2.CAP_PROP_FPS, 30)
+
+    print("Initialized")
+    if not cap.isOpened():
+        print("Error: Could not open camera")
+        exit()
+
+    cv2.namedWindow("Predictions", cv2.WINDOW_NORMAL)
+
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            print("Error: Failed to grab frame")
+            break
+
+        # Optional: resize frame to improve YOLO performance
+        # frame = cv2.resize(frame, (416, 416))
+
+        results = model.predict(source=frame, conf=0.5)
+
+        annotated_frame = results[0].plot()  # annotated frame as NumPy array
+
+        cv2.imshow("Predictions", annotated_frame)
+        cv2.resizeWindow("Predictions", 640, 640)
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+    cap.release()
+    cv2.destroyAllWindows()