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Pavani2704
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6e98be9
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Parent(s):
c7eaac7
Update app.py
Browse files
app.py
CHANGED
@@ -1,15 +1,16 @@
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import streamlit as st
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import transformers
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# Use a pipeline as a high-level helper
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from transformers import pipeline
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pipe = pipeline("summarization", model="google/pegasus-xsum")
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st.title("NLP APP")
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option = st.sidebar.selectbox(
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"Choose a task",
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("Summarization", "
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)
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if option == "Summarization":
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st.title("Text Summarization")
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@@ -19,6 +20,14 @@ if option == "Summarization":
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st.write("Summary:", pipe(text)[0]["summary_text"])
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else:
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st.write("Please enter text to summarize.")
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else:
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st.title("None")
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import streamlit as st
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import transformers
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from transformers import pipeline
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import PIL
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from PIL import Image
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pipe = pipeline("summarization", model="google/pegasus-xsum")
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agepipe = pipeline("image-classification", model="dima806/facial_age_image_detection")
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st.title("NLP APP")
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option = st.sidebar.selectbox(
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"Choose a task",
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("Summarization", "Age Detection", "Emotion Detection", "Image Generation")
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)
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if option == "Summarization":
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st.title("Text Summarization")
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st.write("Summary:", pipe(text)[0]["summary_text"])
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else:
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st.write("Please enter text to summarize.")
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elif option == "Age Detection"
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st.title("welcome to age detection app")
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uploaded_files = st.file_uploader("Choose a image file",type="jpg")
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if uploaded_files is not None:
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Image=Image.open(uploaded_files)
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st.write(agepipe(Image)[0]["label"])
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else:
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st.title("None")
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