Update app.py

app.py

@@ -1,42 +1,42 @@
-# import torch
-# from transformers import Pix2StructForConditionalGeneration, Pix2StructProcessor
-# import gradio as gr
-# from PIL import Image
+import torch
+ from transformers import Pix2StructForConditionalGeneration, Pix2StructProcessor
+ import gradio as gr
+ from PIL import Image
 
 # # Load model and processor
-# model_name = "google/pix2struct-docvqa-large"
-# model = Pix2StructForConditionalGeneration.from_pretrained(model_name)
-# processor = Pix2StructProcessor.from_pretrained(model_name)
+ model_name = "google/pix2struct-docvqa-large"
+ model = Pix2StructForConditionalGeneration.from_pretrained(model_name)
+ processor = Pix2StructProcessor.from_pretrained(model_name)
 
-# def process_image(image_path):
-#     try:
-#         # Load the image
-#         image = Image.open(image_path).convert("RGB")
+ def process_image(image_path):
+     try:
+         # Load the image
+         image = Image.open(image_path).convert("RGB")
 
-#         # Prepare the input
-#         inputs = processor(images=image, text="What does this image say?", return_tensors="pt")
+         # Prepare the input
+         inputs = processor(images=image, text="What does this image say?", return_tensors="pt")
 
-#         # Generate prediction
-#         output = model.generate(**inputs)
+         # Generate prediction
+         output = model.generate(**inputs)
 
 #         # Decode the output
-#         solution = processor.decode(output[0], skip_special_tokens=True)
-#         return solution
+         solution = processor.decode(output[0], skip_special_tokens=True)
+         return solution
 
-#     except Exception as e:
-#         return f"Error processing image: {str(e)}"
+     except Exception as e:
+         return f"Error processing image: {str(e)}"
 
-# def predict(image):
-#     """Handles image input for Gradio."""
-#     return process_image(image)
+ def predict(image):
+     """Handles image input for Gradio."""
+     return process_image(image)
 
 # # Gradio app
-# iface = gr.Interface(
-#     fn=predict,
-#     inputs=gr.Image(type="filepath"),
-#     outputs="text",
-#     title="Image Text Solution"
-# )
-
-# if __name__ == "__main__":
-#     iface.launch()
+ iface = gr.Interface(
+     fn=predict,
+     inputs=gr.Image(type="filepath"),
+     outputs="text",
+     title="Image Text Solution"
+ )
+
+ if __name__ == "__main__":
+     iface.launch()