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import gradio as gr
import tensorflow as tf
import requests
import os
import numpy as np
import pandas as pd
import huggingface_hub
from huggingface_hub import Repository
from datetime import datetime
import scipy.ndimage.interpolation as inter
import datasets
from datasets import load_dataset, Image
from PIL import Image
from paddleocr import PaddleOCR
from doctr.io import DocumentFile
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
os.environ["TF_FORCE_GPU_ALLOW_GROWTH"] = "true"
from doctr.models import ocr_predictor
ocr_model = ocr_predictor(pretrained=True)
"""
Perform OCR with doctr
"""
def ocr_with_doctr(file):
text_output = ''
# Load the document
doc = DocumentFile.from_pdf(file)
# Perform OCR
result = ocr_model(doc)
# Extract text from OCR result
for page in result.pages:
for block in page.blocks:
for line in block.lines:
text_output += " ".join([word.value for word in line.words]) + "\n"
return text_output
"""
Paddle OCR
"""
def ocr_with_paddle(img):
finaltext = ''
ocr = PaddleOCR(lang='en', use_angle_cls=True, use_gpu=False)
# img_path = 'exp.jpeg'
result = ocr.ocr(img)
for i in range(len(result[0])):
text = result[0][i][1][0]
finaltext += ' '+ text
return finaltext
def generate_ocr(Method, file):
text_output = ''
if isinstance(file, bytes): # Handle file uploaded as bytes
file = io.BytesIO(file)
if file.name.endswith('.pdf'):
# Perform OCR on the PDF using doctr
text_output = ocr_with_doctr(file)
else:
# Handle image file
img_np = np.array(Image.open(file))
text_output = generate_text_from_image(Method, img_np)
return text_output
def generate_text_from_image(Method, img):
text_output = ''
if Method == 'PaddleOCR':
text_output = ocr_with_paddle(img)
return text_output
import gradio as gr
image_or_pdf = gr.File(label="Upload an image or PDF")
method = gr.Radio(["PaddleOCR"], value="PaddleOCR")
output = gr.Textbox(label="Output")
demo = gr.Interface(
generate_ocr,
[method, image_or_pdf],
output,
title="Optical Character Recognition",
css=".gradio-container {background-color: lightgray} #radio_div {background-color: #FFD8B4; font-size: 40px;}",
article="""<p style='text-align: center;'>Feel free to give us your thoughts on this demo and please contact us at
<a href="mailto:[email protected]" target="_blank">[email protected]</a>
<p style='text-align: center;'>Developed by: <a href="https://www.pragnakalp.com" target="_blank">Pragnakalp Techlabs</a></p>"""
)
demo.launch(share=True)
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