Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Update app.py #6

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
+121 −61
Open

Update app.py #6

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
182 changes: 121 additions & 61 deletions app.py
View file
Original file line number Diff line number Diff line change
@@ -6,12 +6,21 @@
import pytesseract
from pytesseract import Output
from PIL import Image
from flask import Flask, render_template, request
from flask import Flask, render_template, request ,redirect , url_for , session
from flask_session import Session
# from flask_session import FileSystemSessionInterface
import PyPDF2
from io import BytesIO
import uuid
import os

nltk.download('words')
nltk.download('punkt')
nltk.download('stopwords')

UPLOAD_FOLDER = 'uploads'


# nltk.download('words')
# nltk.download('punkt')
# nltk.download('stopwords')

def preprocess_text(text):
text = re.sub(r'[^\w\s]', '', text)
@@ -52,89 +61,140 @@ def readable_summary(text):
# Specify the Tesseract executable path
pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'


app = Flask(__name__)

# nltk.download('words')
# nltk.download('punkt')
# nltk.download('stopwords')
app.secret_key ='supra_me'

def extract_text_from_pdf(pdf_file):
text = ""
pdf_reader = PdfFileReader(pdf_file)
pdf_reader = PyPDF2.PdfFileReader(pdf_file)
for page_number in range(pdf_reader.numPages):
page = pdf_reader.getPage(page_number)
text += page.extractText()
return text

@app.route('/')
def index():
return render_template('index.html')
return render_template('index.ejs')

@app.route('/process_file', methods=['POST'])
def process_file():
session['questions']=[]
session['answers']=[]

# Get the choice of the user (image or pdf)
file_type = request.form['file_type']

session['file_type'] = file_type

if file_type == 'image':
# Example: Get the uploaded image file
uploaded_file = request.files['file']

# Perform OCR on the image
with Image.open(uploaded_file) as image:
txt = pytesseract.image_to_string(image)

elif file_type == 'pdf':
name=uploaded_file.filename
if uploaded_file.filename == '':
return 'No selected file', 400
file_id = str(uuid.uuid4()) # Generate a unique ID for the file
file_path = os.path.join(UPLOAD_FOLDER, file_id)
uploaded_file.save(file_path)
session['file_path'] = file_path
# print(uploaded_file)



if file_type == 'pdf':
# Example: Get the uploaded PDF file
uploaded_file = request.files['file']

name=uploaded_file.filename
if uploaded_file.filename == '':
return 'No selected file', 400
file_id = str(uuid.uuid4()) # Generate a unique ID for the file
file_path = os.path.join(UPLOAD_FOLDER, file_id)
uploaded_file.save(file_path)
session['file_path'] = file_path
print(name)
return redirect(url_for('quest',filename=name))

@app.route('/quest/<filename>',methods=['GET'])
def quest(filename):
# Extract text from the PDF using PyPDF2
pdf_reader = PyPDF2.PdfReader(uploaded_file)

# Get the number of pages in the PDF
num_pages =num_pages = len(pdf_reader.pages)

# Initialize an empty string to store the extracted text
txt = ""

# Iterate through all pages
for page_num in range(num_pages):
# Get the page
page = pdf_reader.pages[page_num]

# Extract text from the page
etext = page.extract_text()

# Append the text to the result string
txt+=etext

sample_text = txt
# Preprocess text using the loaded function
preprocessed_text = preprocess_text(sample_text)

# Divide documents into sentences using the loaded function
sentences = divide_documents(preprocessed_text)

# Generate summaries using the loaded function
summaries = generate_summaries(sentences)

# Check if the user wants to view the summary
show_summary = request.form.get('show_summary')

if show_summary:
# Use the loaded function to generate a readable summary
summary = readable_summary(sample_text)
else:
summary = None

# Example: Get the question from the user
user_question = request.form['question']

# Use the loaded QA pipeline
answer = qa_pipeline(question=user_question, context=sample_text)

# Render the result on the webpage
return render_template('result.html', question=user_question, answer=answer['answer'], summary=summary)
# print("Meowwww")

return render_template("question.ejs",filename=filename)
# uploaded_file

@app.route('/quest/<filename>',methods=['POST'])
def upload(filename):
print("broo")
items=session.get('questions')
print("Session before appending:", items)
print('hello')
file_path = session.get('file_path')

if file_path is None or not os.path.exists(file_path):
return "File not found", 400

if session.get('file_type') == 'pdf':
with open(file_path, 'rb') as file:
file_data = file.read()
pdf_reader = PyPDF2.PdfReader(BytesIO(file_data))

# Get the number of pages in the PDF
num_pages =num_pages = len(pdf_reader.pages)

# Initialize an empty string to store the extracted text
txt = ""

# Iterate through all pages
for page_num in range(num_pages):
# Get the page
page = pdf_reader.pages[page_num]

# Extract text from the page
etext = page.extract_text()

# Append the text to the result string
txt+=etext

if session.get('file_type') == 'image':
# Perform OCR on the image
with Image.open(file_path) as image:
txt = pytesseract.image_to_string(image)

sample_text = txt
if sample_text == '':
sample_text = "No answers found"
# Preprocess text using the loaded function
preprocessed_text = preprocess_text(sample_text)

# Divide documents into sentences using the loaded function
sentences = divide_documents(preprocessed_text)

# Generate summaries using the loaded function
summaries = generate_summaries(sentences)

# Check if the user wants to view the summary
show_summary = request.form.get('show_summary')

if show_summary:
# Use the loaded function to generate a readable summary
summary = readable_summary(sample_text)
else:
summary = None

# Example: Get the question from the user
user_question = request.form['question']
session['questions'].append(user_question)
session.modified = True
print("Session after appending:", session.get('questions'))
# Use the loaded QA pipeline
answer = qa_pipeline(question=user_question, context=sample_text)
session['answers'].append(answer['answer'])

# Render the result on the webpage
return render_template('question.ejs', question=session.get('questions'), answer=session.get('answers'), summary=summary,filename=filename,len=len(session.get('questions')))

if __name__ == '__main__':
app.run(debug=True)