Upload app.py

app.py

@@ -11,8 +11,8 @@ css = "footer {display: none !important;}"
 
 # sample images
 examples = [
-    ["", None, "images/1.jpg"],
-    ["", None, "images/sample-handwritten-2.PNG"]
+    ["", "images/1.jpg", "images/1.jpg"],
+    ["", "images/sample-handwritten-2.PNG", "images/sample-handwritten-2.PNG"]
 ]
 
 #you can load any model from huggingface
@@ -22,16 +22,27 @@ model = VisionEncoderDecoderModel.from_pretrained('microsoft/trocr-large-handwri
 # prediction function for handwritting
 def predict(ImageUrl,imgDraw,imgUplod):
 
+  image = None
   #fetch the image from url or handwritten canvas or the uplaoded image
-  if ImageUrl :
-    image = Image.open(requests.get(ImageUrl, stream=True).raw).convert("RGB")
-  elif imgDraw :
+  if ImageUrl:
+    try:
+        image = Image.open(requests.get(ImageUrl, stream=True).raw).convert("RGB")
+    except:
+        return "Error: Invalid Image URL"
+  # Prioritize uploaded image if it exists
+  elif imgUplod is not None:
+    image = imgUplod.convert("RGB")
+  # Fallback to the drawing canvas
+  elif imgDraw is not None:
     # Handle Gradio 4+ sketchpad returning a dictionary
     if isinstance(imgDraw, dict) and "composite" in imgDraw:
-        imgDraw = imgDraw["composite"]
-    image = imgDraw.convert("RGB")
-  else :
-    image = imgUplod.convert("RGB")
+        if imgDraw["composite"] is not None:
+            image = imgDraw["composite"].convert("RGB")
+    elif not isinstance(imgDraw, dict):
+        image = imgDraw.convert("RGB")
+        
+  if image is None:
+      return "Please provide an image via URL, Sketchpad, or Upload."
 
   #predict the image using microsoft/trocr-large-handwritten model loaded earlier
   pixel_values = processor(images=image, return_tensors="pt").pixel_values