Update app.py

app.py

@@ -1,32 +1,29 @@
 import gradio as gr
-from transformers import TrOCRProcessor, VisionEncoderDecoderModel
 from PIL import Image
-import numpy as np
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
 
 # Load the processor and model
-processor = TrOCRProcessor.from_pretrained('microsoft/trocr-large-handwritten')
-model = VisionEncoderDecoderModel.from_pretrained('microsoft/trocr-large-handwritten')
+processor = TrOCRProcessor.from_pretrained("microsoft/trocr-large-handwritten")
+model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-large-handwritten")
 
+# Define the function to recognize handwriting
 def recognize_handwriting(image):
-    if isinstance(image, dict):
-        image = image["image"]
-    pil_image = Image.fromarray(image).convert("RGB")
-    pixel_values = processor(images=pil_image, return_tensors="pt").pixel_values
+    pixel_values = processor(images=image, return_tensors="pt").pixel_values
     generated_ids = model.generate(pixel_values)
     generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
     return generated_text
 
-# Gradio interface
-image_input = gr.Image(tool="editor", type="numpy", label="Draw or Upload an Image")
-output_text = gr.Textbox(label="Recognized Text")
-
-iface = gr.Interface(
-    fn=recognize_handwriting,
-    inputs=image_input,
-    outputs=output_text,
-    title="Handwriting Recognition",
-    description="Draw or upload an image of handwritten text, and the model will recognize the text.",
-    live=True,
-)
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Handwriting Recognition")
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(tool="editor", type="numpy", label="Draw or Upload an Image")
+            recognize_button = gr.Button("Recognize Handwriting")
+        with gr.Column():
+            output_text = gr.Textbox(label="Recognized Text")
+    
+    recognize_button.click(fn=recognize_handwriting, inputs=image_input, outputs=output_text)
 
-iface.launch()
+# Launch the Gradio app
+demo.launch()