Update app.py

app.py

@@ -45,23 +45,29 @@ transform = transforms.Compose([
 ])
 
 def predict(image):
-    # Check if the input contains a base64-encoded string
-    if isinstance(image, dict) and image.get("data"):
-        try:
-            image_data = base64.b64decode(image["data"])
-            image = Image.open(BytesIO(image_data))
-        except Exception as e:
-            return f"Error decoding base64 image: {e}"
+    try:
+        # Debugging: Print the received image
+        print(f"Received image: {image}")
 
-    elif isinstance(image, str):
-        try:
-            response = requests.get(image)
-            image = Image.open(BytesIO(response.content))
-        except Exception as e:
-            return f"Error fetching image from URL: {e}"
+        # Check if the input contains a base64-encoded string
+        if isinstance(image, dict) and image.get("data"):
+            try:
+                image_data = base64.b64decode(image["data"])
+                image = Image.open(BytesIO(image_data))
+                print(f"Decoded base64 image: {image}")
+            except Exception as e:
+                return f"Error decoding base64 image: {e}"
 
-    # Apply transformations
-    try:
+        # Check if the input is a URL
+        elif isinstance(image, str) and image.startswith("http"):
+            try:
+                response = requests.get(image)
+                image = Image.open(BytesIO(response.content))
+                print(f"Fetched image from URL: {image}")
+            except Exception as e:
+                return f"Error fetching image from URL: {e}"
+
+        # Apply transformations
         image = transform(image).unsqueeze(0)
         image = image.to(torch.device("cuda" if torch.cuda.is_available() else "cpu"))