Update app.py

app.py

@@ -24,11 +24,25 @@ transform = transforms.Compose([
 
 # Prediction function
 def predict(image: Image.Image):
-    tensor = transform(image).unsqueeze(0)
-    with torch.no_grad():
-        logits = model(tensor).logits
-        predicted = torch.argmax(logits, dim=1).item()
-        return config.id2label[str(predicted)]
+    try:
+        print("🔍 Received image:", image)
+
+        tensor = transform(image).unsqueeze(0)  # Add batch dimension
+        print("📦 Transformed tensor shape:", tensor.shape)
+
+        with torch.no_grad():
+            logits = model(tensor).logits
+            predicted = torch.argmax(logits, dim=1).item()
+            print("✅ Prediction index:", predicted)
+
+            label = config.id2label[str(predicted)]
+            print("🏷️ Label:", label)
+        return label
+
+    except Exception as e:
+        print("❌ Prediction error:", e)
+        return "خطأ"
+
 
 # ✅ Prediction interface
 gr.Interface(