hardiksharma6555
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README.md
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---
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title: OCR_IITR
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app_file: new.py
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sdk: gradio
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sdk_version: 4.44.0
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---
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app.py
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import gradio as gr
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from gradio_client import Client, handle_file
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import re
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from thefuzz import fuzz
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# hugging face clients for both OCR options
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surya_ocr_client = Client("artificialguybr/Surya-OCR")
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got_ocr_client = Client("stepfun-ai/GOT_official_online_demo")
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# Global variable to store the extracted OCR text
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extracted_text = ""
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def ocr_extraction(image, ocr_model):
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global extracted_text
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if image is None:
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return "Please upload an image first."
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try:
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if ocr_model == "Surya OCR":
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client = surya_ocr_client
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result = client.predict(
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image=handle_file(image),
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langs="en",
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api_name="/ocr_workflow"
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)
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text_matches = re.findall(r"text='(.*?)'", str(result))
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extracted_text = "\n".join(text_matches)
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elif ocr_model == "GOT OCR":
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client = got_ocr_client
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result = client.predict(
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image=handle_file(image),
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got_mode="plain texts OCR",
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fine_grained_mode="box",
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ocr_color="red",
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ocr_box="Hello!!",
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api_name="/run_GOT"
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)
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extracted_text = result[0]
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else:
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return "Invalid OCR model selected."
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return extracted_text
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except Exception as e:
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return f"An error occurred: {str(e)}"
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def search_keyword(keyword, search_type):
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global extracted_text
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if not extracted_text:
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return "No OCR text found. Please extract text from an image first."
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if not keyword:
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return extracted_text
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if search_type == "Direct Search":
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highlighted_text = re.sub(f"({re.escape(keyword)})", r'<span style="background-color: yellow;">\1</span>', extracted_text, flags=re.IGNORECASE)
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else: # Nearest Search
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words = extracted_text.split()
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highlighted_words = []
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for word in words:
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if fuzz.ratio(word.lower(), keyword.lower()) >= 80: # Adjust threshold as needed
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highlighted_words.append(f'<span style="background-color: yellow;">{word}</span>')
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else:
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highlighted_words.append(word)
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highlighted_text = " ".join(highlighted_words)
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return highlighted_text
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with gr.Blocks(theme=gr.themes.Soft()) as gr_interface:
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gr.Markdown("# 📷 OCR Text Extraction and Advanced Keyword Search 🔍")
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with gr.Row():
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with gr.Column(scale=1):
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image_input = gr.Image(type="filepath", label="Upload Image")
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ocr_model_dropdown = gr.Dropdown(
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choices=["Surya OCR", "GOT OCR"],
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value="Surya OCR",
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label="Select OCR Model"
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)
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ocr_button = gr.Button("Extract Text", variant="primary")
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with gr.Column(scale=2):
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extracted_text_output = gr.Textbox(
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label="Extracted Text",
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placeholder="Text extracted from the image will appear here.",
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lines=10
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)
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with gr.Row():
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with gr.Column(scale=1):
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keyword_input = gr.Textbox(label="Enter keyword to search")
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search_type = gr.Radio(["Direct Search", "Nearest Search"], label="Search Type", value="Direct Search")
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search_button = gr.Button("Search Keyword", variant="secondary")
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with gr.Column(scale=2):
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highlighted_output = gr.HTML(label="Highlighted Text")
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ocr_button.click(
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fn=ocr_extraction,
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inputs=[image_input, ocr_model_dropdown],
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outputs=extracted_text_output
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)
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search_button.click(
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fn=search_keyword,
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inputs=[keyword_input, search_type],
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outputs=highlighted_output
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)
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gr_interface.launch(share=True)
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