Create app.py

app.py

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+import gradio as gr
+from paddleocr import PaddleOCR
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Initialize PaddleOCR
+ocr = PaddleOCR(use_angle_cls=True, lang='en')
+
+# Load GPT-NeoX model and tokenizer
+model_name = "EleutherAI/gpt-neox-20b"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+def ocr_and_correct(text):
+    # Function to correct text using GPT-NeoX
+    inputs = tokenizer(text, return_tensors="pt")
+    outputs = model.generate(**inputs)
+    corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return corrected_text
+
+def process_image(image):
+    # Perform OCR on the image
+    result = ocr.ocr(image, cls=True)
+    
+    # Extract and join the text from OCR results
+    extracted_text = " ".join([line[1][0] for line in result])
+    
+    # Correct the extracted text
+    corrected_text = ocr_and_correct(extracted_text)
+    
+    return corrected_text
+
+# Gradio interface
+iface = gr.Interface(fn=process_image, inputs="image", outputs="text")
+
+iface.launch()