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| import gradio as gr | |
| from transformers import pipeline | |
| import easyocr | |
| from PIL import Image | |
| # Load the NLP model for text simplification | |
| simplify_model = pipeline("summarization", model="t5-small") | |
| # Initialize EasyOCR reader | |
| reader = easyocr.Reader(["en"]) | |
| def process_image(image): | |
| """ | |
| Extract text from an uploaded image using EasyOCR and simplify it. | |
| """ | |
| # Convert image to text using EasyOCR | |
| results = reader.readtext(image, detail=0) | |
| text = " ".join(results) | |
| if not text.strip(): | |
| return "No text detected in the image. Please upload a clear image of the text." | |
| # Simplify the extracted text | |
| simplified_text = simplify_model(text, max_length=50, min_length=10, do_sample=False)[0]["summary_text"] | |
| return simplified_text | |
| # Create a Gradio interface | |
| interface = gr.Interface( | |
| fn=process_image, | |
| inputs="image", | |
| outputs="text", | |
| title="Simplify Book Content", | |
| description="Upload a photo of a book page to get a simplified explanation in simple English.", | |
| ) | |
| # Launch the app | |
| if __name__ == "__main__": | |
| interface.launch() | |