Spaces:
Paused
Paused
File size: 4,401 Bytes
c9e6420 6bd383d a73d961 6bd383d 3c0821a a73d961 61e3677 3c0821a 61e3677 3c0821a 61e3677 3c0821a a73d961 61e3677 3c0821a 6bd383d 3c0821a 61e3677 3c0821a 61e3677 3c0821a c9e6420 2ab0f0e b04b188 2ab0f0e c681352 c9e6420 4b3f925 61e3677 a73d961 2ab0f0e a73d961 2ab0f0e a73d961 2ab0f0e a73d961 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 |
import gradio as gr
import subprocess
import uuid
import os
import requests
def get_pdf(pdf_link):
# Generate a unique filename
unique_filename = f"input/downloaded_paper_{uuid.uuid4().hex}.pdf"
# Send a GET request to the PDF link
response = requests.get(pdf_link)
if response.status_code == 200:
# Save the PDF content to a local file
with open(unique_filename, 'wb') as pdf_file:
pdf_file.write(response.content)
print("PDF downloaded successfully.")
else:
print("Failed to download the PDF.")
return unique_filename #.split('/')[-1][:-4]
def nougat_ocr(file_name):
#unique_filename = f"/content/output/downloaded_paper_{uuid.uuid4().hex}.pdf"
# Command to run
cli_command = [
'nougat',
#'--out', unique_filename,
'--out', 'output',
'pdf', f'{file_name}',
'--checkpoint', 'nougat'
]
# Run the command and capture its output
#completed_process =
subprocess.run(cli_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
return #unique_filename
def predict(pdf_file, pdf_link):
if pdf_file is None:
if pdf_link == '':
print("No file is uploaded and No link is provided")
return "No data provided. Upload a pdf file or provide a pdf link and try again!"
else:
print(f'pdf_link is - {pdf_link}')
file_name = get_pdf(pdf_link)
print(f'file_name is - {file_name}')
else:
file_name = pdf_file.name
print(file_name)
pdf_name = pdf_file.name.split('/')[-1].split('.')[0]
print(pdf_name)
# Call nougat
nougat_ocr(file_name)
#print("BACKKKK")
# Open the file for reading
file_name = file_name.split('/')[-1][:-4]
with open(f'output/{file_name}.mmd', 'r') as file:
content = file.read()
return content
def nougat_ocr1(file_name):
print('******* inside nougat_ocr *******')
# CLI Command to run
cli_command = [
'nougat',
'--out', 'output',
'pdf', f'{file_name}',
'--checkpoint', 'nougat'
]
# Run the command and get .mmd file in an output folder
subprocess.run(cli_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
return
def predict1(pdf_file):
print('******* inside predict *******')
print(f"temporary file - {pdf_file.name}")
pdf_name = pdf_file.name.split('/')[-1].split('.')[0]
print(f"pdf file name - {pdf_name}")
#! Get prediction for a PDF using nougat
nougat_ocr(pdf_file.name)
print("BAACCKKK")
# Open the multimarkdown (.mmd) file for reading
with open(f'output/{pdf_name}.mmd', 'r') as file:
content = file.read()
return content
def process_example(pdf_file,pdf_link):
ocr_content = predict(pdf_file,pdf_link)
return ocr_content
css = """
#mkd {
height: 500px;
overflow: auto;
border: 1px solid #ccc;
}
"""
with gr.Blocks(css=css) as demo:
gr.HTML("<h1><center>Nougat: Neural Optical Understanding for Academic Documents<center><h1>")
gr.HTML("<h3><center>Lukas Blecher et al. <a href='https://arxiv.org/pdf/2308.13418.pdf' target='_blank'>Paper</a>, <a href='https://facebookresearch.github.io/nougat/'>Project</a><center></h3>")
with gr.Row():
mkd = gr.Markdown('<h4><center>Upload a PDF</center></h4>',scale=1)
mkd = gr.Markdown('<h4><center><i>OR</i></center></h4>',scale=1)
mkd = gr.Markdown('<h4><center>Provide a PDF link</center></h4>',scale=1)
with gr.Row(equal_height=True):
pdf_file = gr.File(label='PDF📃', file_count='single', scale=1)
pdf_link = gr.Textbox(placeholder='Enter an Arxiv link here', label='PDF link🔗🌐', scale=1)
with gr.Row():
btn = gr.Button('Run NOUGAT🍫')
clr = gr.Button('Clear🚿')
parsed_output = gr.Markdown(elem_id='mkd', value='📃🔤OCR Output')
btn.click(predict, [pdf_file, pdf_link], parsed_output )
clr.click(lambda : (gr.update(value=None),
gr.update(value=None),
gr.update(value=None)),
[],
[pdf_file, pdf_link, parsed_output]
)
gr.Examples(
[["input/nougat.pdf", ""], [None, "https://arxiv.org/pdf/2308.08316.pdf"]],
inputs = [pdf_file, pdf_link],
outputs = parsed_output,
fn=process_example,
cache_examples=True,
label='Click on any Examples below to get Nougat OCR results quickly:'
)
demo.queue()
demo.launch(debug=True)
|