Adding new model

src/train.py

@@ -114,4 +114,6 @@ def train():
     
     print(f"Best val acc: {top_val_acc} | Best train acc: {top_train_acc} | Epoch: {checkpoint_index}")
 
-train()
+# Path: src/train.py
+if __name__ == "__main__":
+    train()

visualize_data.ipynb

@@ -187,7 +187,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.9.16"
   },
   "vscode": {
    "interpreter": {

webcam_view.py

@@ -20,16 +20,23 @@ cap = cv2.VideoCapture(0)
 
 keypoints = []
 
-spoter_model = SPOTER(num_classes=5, hidden_dim=len(LANDMARKS) *2)
-spoter_model.load_state_dict(torch.load('models/spoter_56.pth'))
+spoter_model = SPOTER(num_classes=12, hidden_dim=len(LANDMARKS) *2)
+spoter_model.load_state_dict(torch.load('models/spoter_57.pth'))
 
 m = {
     0: "A",
     1: "B",
     2: "C",
     3: "D",
-    4: "E"
-}
+    4: "E",
+    5: "F",
+    6: "G",
+    7: "H",
+    8: "I",
+    9: "J",
+    10: "K",
+    11: "L",
+} 
 
 while True:
     # Read a frame from the webcam
@@ -117,6 +124,9 @@ while True:
     mp_drawing.draw_landmarks(frame, results.right_hand_landmarks, mp_holistic.HAND_CONNECTIONS)
     mp_drawing.draw_landmarks(frame, results.pose_landmarks, mp_holistic.POSE_CONNECTIONS)
 
+    # frame to rgb
+    frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
+
     # Show the frame
     cv2.imshow('MediaPipe Hands', frame)