Spaces:
No application file
No application file
import gradio as gr | |
from transformers import AutoModel, AutoTokenizer | |
import os | |
import re | |
# Load the model and tokenizer from local path | |
# Assuming your model and tokenizer are stored in '/content/model' directory in Colab | |
model_path = 'pranavdaware/web_ocr' | |
# Load the model and tokenizer from the local directory | |
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True) | |
model = AutoModel.from_pretrained(model_path, trust_remote_code=True, low_cpu_mem_usage=True, device_map='cuda', use_safetensors=True) | |
model = model.eval().cuda() | |
# Function to extract text using OCR | |
def ocr_processing(image_file): | |
try: | |
# Perform OCR on the uploaded image | |
result = model.chat(tokenizer, image_file, ocr_type='ocr') | |
return result | |
except Exception as e: | |
return str(e) | |
# Function to search for keywords in extracted text | |
def search_keyword(ocr_text, keyword): | |
try: | |
# Use regex to search for the keyword and highlight matches | |
matches = re.findall(rf"({keyword})", ocr_text, re.IGNORECASE) | |
if matches: | |
highlighted_text = re.sub(rf"({keyword})", r'<mark>\1</mark>', ocr_text, flags=re.IGNORECASE) | |
return highlighted_text | |
else: | |
return f"No matches found for '{keyword}' in the extracted text." | |
except Exception as e: | |
return str(e) | |
# Gradio interface | |
def main(): | |
# Gradio app layout | |
with gr.Blocks() as demo: | |
gr.Markdown("# OCR and Keyword Search Application") | |
with gr.Row(): | |
with gr.Column(): | |
image_input = gr.Image(type="filepath", label="Upload your image") | |
keyword_input = gr.Textbox(label="Enter keyword to search") | |
ocr_output = gr.Textbox(label="OCR Output") | |
search_output = gr.HTML(label="Search Results") | |
# Button for OCR processing | |
process_button = gr.Button("Process Image for OCR") | |
# Connect the OCR processing function to the button | |
process_button.click( | |
fn=ocr_processing, | |
inputs=image_input, | |
outputs=ocr_output | |
) | |
# Button for keyword search | |
search_button = gr.Button("Search Keyword in OCR Text") | |
# Connect the search function to the button | |
search_button.click( | |
fn=search_keyword, | |
inputs=[ocr_output, keyword_input], | |
outputs=search_output | |
) | |
# Launch the Gradio demo | |
demo.launch() | |
if __name__ == "__main__": | |
main() | |