Update app.py

app.py

@@ -1,4 +1,4 @@
-import gradio as gr 
+import gradio as gr
 from transformers import TrOCRProcessor, VisionEncoderDecoderModel
 from PIL import Image
 import numpy as np
@@ -15,13 +15,13 @@ model2 = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-handwri
 # Function to extract text from handwritten images
 def extract_text(image):
     try:
-        # Convert NumPy array to PIL Image if needed
+        # Ensure input is a PIL Image
         if isinstance(image, np.ndarray):
             if len(image.shape) == 2:  # Grayscale (H, W) -> Convert to RGB
                 image = np.stack([image] * 3, axis=-1)
             image = Image.fromarray(image)
-        else:
-            image = Image.open(image).convert("RGB")  # Ensure RGB format
+        elif isinstance(image, str):  # If file path is given, open the image
+            image = Image.open(image).convert("RGB")
 
         # Maintain aspect ratio while resizing (better for OCR)
         image.thumbnail((800, 800))  
@@ -45,7 +45,7 @@ def extract_text(image):
 # Gradio UI for OCR Extraction
 iface = gr.Interface(
     fn=extract_text,
-    inputs=gr.Image(type="pil"),
+    inputs=gr.Image(type="pil"),  # Ensures input is a PIL image
     outputs="text",
     title="Handwritten OCR Extraction",
     description="Upload a handwritten image to extract text using AI OCR.",