Update app.py

app.py

@@ -55,14 +55,19 @@ def split_board_into_squares(board_img):
     return squares
 
 def predict_board(squares):
-    predictions = []
+    batch = []
     for square in squares:
         img = cv2.resize(square, (64, 64))
-        img = tf.keras.applications.efficientnet.preprocess_input(img)
-        img = np.expand_dims(img, axis=0)
-        pred = model.predict(img, verbose=0)
-        class_idx = np.argmax(pred)
-        confidence = np.max(pred)
+        img = tf.keras.applications.efficientnet.preprocess_input(
+            img.astype(np.float32)
+        )
+        batch.append(img)
+    batch = np.array(batch)
+    preds = model.predict(batch, verbose=0)
+    predictions = []
+    for i in range(len(preds)):
+        class_idx = np.argmax(preds[i])
+        confidence = np.max(preds[i])
         predictions.append({
             "class": CLASS_NAMES[class_idx],
             "confidence": float(confidence)