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import gradio as gr | |
import pytesseract | |
import cv2 | |
import os | |
def process(files, lang: str = 'eng') -> str: | |
results = [] | |
for file in files: | |
try: | |
img = cv2.imread(file) | |
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) | |
_, threshold_img = cv2.threshold(gray, 127, 255, cv2.THRESH_TOZERO) | |
result = pytesseract.image_to_string(threshold_img, lang=lang) | |
results.append(result) | |
except Exception as e: | |
results.append(f"Error processing {file}: {str(e)}") | |
finally: | |
os.remove(file) | |
return "\n\n".join(results) | |
# Get available languages for pytesseract | |
langs = pytesseract.get_languages() | |
# Define the Gradio interface using gr.Files to allow multiple file uploads | |
interface = gr.Interface( | |
fn=process, | |
inputs=[ | |
gr.Files(label="Upload Images", file_count="multiple", type="filepath"), | |
gr.Dropdown(label="Select Language", choices=langs, type="value") | |
], | |
outputs="text", | |
css="footer {visibility: hidden}", | |
title="Optical Character Recognition | Batch Image To Text", | |
article=""" | |
<p style='text-align: center;'> | |
</p> | |
""" | |
) | |
# Launch the interface | |
interface.launch(show_api=False) | |