Update app.py
Browse files
app.py
CHANGED
@@ -16,7 +16,7 @@ os.environ["TOKENIZERS_PARALLELISM"] = "false"
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#os.system('pip install -q pytesseract')
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#os.system('conda install -c conda-forge poppler')
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import streamlit as st
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-
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st.title("Bangla and English Summarizer: Upload Images/Pdf or input texts to summarize!")
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import torch
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import docx2txt
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@@ -40,7 +40,7 @@ API_URL1 = "https://api-inference.huggingface.co/models/Michael-Vptn/text-summar
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headers1 = {"Authorization": "Bearer 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"}
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API_URL2 = "https://api-inference.huggingface.co/models/gpt2"
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headers2 = {"Authorization": "Bearer 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"}
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-
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def read_pdf(file):
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# images=pdf2image.convert_from_path(file)
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# # print(type(images))
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@@ -85,7 +85,7 @@ def bansum(text):
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if "photo" not in st.session_state:
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st.session_state["photo"]="not done"
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c2, c3 = st.columns([2
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def change_photo_state():
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st.session_state["photo"]="done"
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message = st.text_input("Type your text here!")
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@@ -119,11 +119,12 @@ if st.session_state["photo"]=="done" or message:
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img = img.save("img.png")
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img = cv2.imread("img.png")
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st.text("Select the summarization type:")
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text = pytesseract.image_to_string(img, lang="ben")
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st.subheader("সারাংশ/সারমর্ম")
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bansum(text)
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if
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text=pytesseract.image_to_string(img)
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st.subheader("Summarized Text")
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engsum(text)
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@@ -135,20 +136,22 @@ if st.session_state["photo"]=="done" or message:
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img = cv2.imread("img.png")
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#text = pytesseract.image_to_string(img) if st.checkbox("Bangla") else pytesseract.image_to_string(img, lang="ben")
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st.text("Select the summarization type:")
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text = pytesseract.image_to_string(img, lang="ben")
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st.subheader("সারাংশ/সারমর্ম")
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bansum(text)
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if
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text=pytesseract.image_to_string(img)
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st.subheader("Summarized Text")
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engsum(text)
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else:
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text=None
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text = message
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-
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bansum(text)
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if
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engsum(text)
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# if st.button("English Text Generation"):
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# def query(payload):
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#os.system('pip install -q pytesseract')
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#os.system('conda install -c conda-forge poppler')
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import streamlit as st
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st.set_page_config(page_title="Summarization Tool", layout="wide", initial_sidebar_state="expanded")
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st.title("Bangla and English Summarizer: Upload Images/Pdf or input texts to summarize!")
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import torch
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import docx2txt
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headers1 = {"Authorization": "Bearer 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"}
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API_URL2 = "https://api-inference.huggingface.co/models/gpt2"
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headers2 = {"Authorization": "Bearer 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"}
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@st.cache
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def read_pdf(file):
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# images=pdf2image.convert_from_path(file)
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# # print(type(images))
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if "photo" not in st.session_state:
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st.session_state["photo"]="not done"
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c2, c3 = st.columns([2,1])
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def change_photo_state():
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st.session_state["photo"]="done"
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message = st.text_input("Type your text here!")
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img = img.save("img.png")
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img = cv2.imread("img.png")
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st.text("Select the summarization type:")
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c4, c5 = st.columns([1,1])
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if c4.button("BENGALI"):
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text = pytesseract.image_to_string(img, lang="ben")
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st.subheader("সারাংশ/সারমর্ম")
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bansum(text)
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if c5.button("ENGLISH"):
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text=pytesseract.image_to_string(img)
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st.subheader("Summarized Text")
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engsum(text)
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img = cv2.imread("img.png")
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#text = pytesseract.image_to_string(img) if st.checkbox("Bangla") else pytesseract.image_to_string(img, lang="ben")
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st.text("Select the summarization type:")
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c6, c7 = st.columns([1,1])
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if c6.button("Bangla"):
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text = pytesseract.image_to_string(img, lang="ben")
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st.subheader("সারাংশ/সারমর্ম")
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bansum(text)
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if c7.button("English"):
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text=pytesseract.image_to_string(img)
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st.subheader("Summarized Text")
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engsum(text)
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else:
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text=None
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text = message
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c8, c9 = st.columns([1,1])
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if c8.button("Bangla"):
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bansum(text)
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if c9.button("English"):
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engsum(text)
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# if st.button("English Text Generation"):
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# def query(payload):
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