tdnathmlenthusiast commited on
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a5d0684
1 Parent(s): 728ab01

required files for OCR tool

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Files changed (4) hide show
  1. .gitattributes +35 -35
  2. README.md +14 -12
  3. app.py +111 -0
  4. requirements.txt +11 -0
.gitattributes CHANGED
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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.model filter=lfs diff=lfs merge=lfs -text
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+ *.msgpack filter=lfs diff=lfs merge=lfs -text
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+ *.npy filter=lfs diff=lfs merge=lfs -text
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+ *.npz filter=lfs diff=lfs merge=lfs -text
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+ *.onnx filter=lfs diff=lfs merge=lfs -text
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+ *.parquet filter=lfs diff=lfs merge=lfs -text
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+ *.pb filter=lfs diff=lfs merge=lfs -text
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+ *.pickle filter=lfs diff=lfs merge=lfs -text
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+ *.pkl filter=lfs diff=lfs merge=lfs -text
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+ *.pt filter=lfs diff=lfs merge=lfs -text
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+ *.pth filter=lfs diff=lfs merge=lfs -text
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+ *.safetensors filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tar filter=lfs diff=lfs merge=lfs -text
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README.md CHANGED
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- ---
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- title: OCR For Hindi English
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- emoji: 🐠
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- colorFrom: indigo
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- colorTo: gray
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- sdk: gradio
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- sdk_version: 4.44.0
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- app_file: app.py
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- pinned: false
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- ---
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-
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
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+ ---
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+ title: Ocr Gradio(Developed by Tirtha Debnath, Bangladesh)
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+ emoji: 🐢
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+ colorFrom: blue
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+ colorTo: red
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+ sdk: gradio
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+ sdk_version: 4.44.0
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+ app_file: app.py
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+ pinned: false
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+ license: mit
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+ short_description: IIT Roorkee
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+ ---
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+
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
app.py ADDED
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+ # import all required libraries after doing research
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+ import gradio as gr
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+ from PIL import Image
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+ from surya.ocr import run_ocr # dedicated GOT_OCR_2.0 for hindi languages
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+ from surya.model.detection.model import load_model as load_det_model, load_processor as load_det_processor
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+ from surya.model.recognition.model import load_model as load_rec_model
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+ from surya.model.recognition.processor import load_processor as load_rec_processor
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+ import re # recognized hindi encoded pattern
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+ from transformers import AutoModel, AutoTokenizer
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+ import torch
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+ import tempfile
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+ import os
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+
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+ # device = "cuda"
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+ device = 'cuda' if torch.cuda.is_available() else 'cpu'
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+ print(device)
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+ # load_desirable_model
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+ got_model_name = 'tdnathmlenthusiast/got-ocr-2.0-modified-hindi-version'
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+
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+ det_processor, det_model = load_det_processor(), load_det_model()
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+ det_model.to(device)
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+ rec_model, rec_processor = load_rec_model(), load_rec_processor()
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+ rec_model.to(device)
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+
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+ # tokenized to extract individual character
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+ tokenizer = AutoTokenizer.from_pretrained(
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+ got_model_name, trust_remote_code=True, device_map=device)
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+ got_model = AutoModel.from_pretrained(
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+ got_model_name, trust_remote_code=True, low_cpu_mem_usage=True, device_map=device, use_safetensors=True)
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+ got_model = got_model.eval().to(device)
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+
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+
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+ # function to extract hindi & english
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+ def extract_hindi(text):
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+ # Unicode range for Devanagari script
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+ hindi_pattern = re.compile(r'[\u0900-\u097F]+')
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+ hindi_words = hindi_pattern.findall(text)
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+ return ' '.join(hindi_words)
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+
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+
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+ def process_image(image):
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+ with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_file:
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+ image.save(temp_file.name)
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+ temp_file_path = temp_file.name
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+
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+ image = Image.open(temp_file_path)
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+ image = image.convert("RGB")
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+
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+ langs = ["hi"]
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+ surya_predictions = run_ocr(
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+ [image], [langs], det_model, det_processor, rec_model, rec_processor)
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+
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+ surya_text_list = re.findall(r"text='(.*?)'", str(surya_predictions[0]))
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+ surya_text = '\n'.join(surya_text_list)
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+ surya_text = extract_hindi(surya_text)
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+
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+ got_res = got_model.chat(tokenizer, temp_file_path, ocr_type='ocr')
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+
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+ combined_text = f"<h2> Hindi Text (Surya OCR) </h2> <br>{surya_text}<br> <br> <h2> English Text (GOT OCR) </h2> <br> {got_res}"
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+
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+ if os.path.exists(temp_file_path):
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+ os.remove(temp_file_path)
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+
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+ return combined_text
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+
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+ # code to search words like documents
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+
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+
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+ def highlight_search(text, query):
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+ if query:
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+ pattern = re.compile(re.escape(query), re.IGNORECASE)
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+ highlighted_text = pattern.sub(
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+ lambda m: f"<span style='background-color: limegreen;'>{m.group(0)}</span>", text)
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+ return highlighted_text
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+ return text
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+
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+
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+ with gr.Blocks() as ocr_interface:
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+ gr.Markdown("# OCR Application for Hindi & English")
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+ gr.Markdown(
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+ "Upload an image for OCR processing.(Takes a little bit time or sometimes a lot due to the limitation of the resources)")
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+
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+ with gr.Row():
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+ with gr.Column():
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+ image_input = gr.Image(
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+ type="pil", label="Upload an Image(Hindi/English/Hindi+English)")
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+ run_ocr_button = gr.Button("Run OCR")
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+
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+ with gr.Column():
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+ output_text = gr.HTML(label="Extracted Text in Hindi & English")
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+ query_input = gr.Textbox(
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+ label="Search in extracted text", placeholder="Type to search...")
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+ search_button = gr.Button("Search")
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+
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+ def process_and_display(image):
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+ combined_text = process_image(image)
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+ return combined_text
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+
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+ def search_text(combined_text, query):
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+ highlighted = highlight_search(combined_text, query)
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+ return highlighted
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+
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+ run_ocr_button.click(fn=process_and_display,
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+ inputs=image_input, outputs=output_text)
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+
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+ search_button.click(fn=search_text, inputs=[
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+ output_text, query_input], outputs=output_text)
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+
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+ ocr_interface.launch()
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+
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+ # Developed by Tirtha Debnath.
requirements.txt ADDED
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+ streamlit
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+ Pillow
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+ surya-ocr
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+ torch
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+ transformers
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+ tiktoken
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+ torchvision
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+ verovio
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+ accelerate
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+ rapidfuzz
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+ gradio