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Kingston Yip
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Parent(s):
7179214
apptest;
Browse files
app.py
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import streamlit as st
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from transformers import pipeline
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from PIL import Image
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pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
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st.title("Hot Dog? Or Not?")
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file_name = st.file_uploader("Upload a hot dog candidate image")
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if file_name is not None:
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# import streamlit as st
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# from transformers import pipeline
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# from PIL import Image
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# pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
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# st.title("Hot Dog? Or Not?")
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# file_name = st.file_uploader("Upload a hot dog candidate image")
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# if file_name is not None:
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# col1, col2 = st.columns(2)
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# image = Image.open(file_name)
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# col1.image(image, use_column_width=True)
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# predictions = pipeline(image)
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# col2.header("Probabilities")
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# for p in predictions:
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# col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")
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import streamlit as st
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from transformers import pipeline
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pipe = pipeline(task="sentiment-analysis")
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st.title("Toxic Tweets Analyzer")
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text = st.text_area("Enter your tweet here, or submit to test the default tweets")
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if text == "Enter your tweet here, or submit to test the default tweets":
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data = [
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"PICKLE YE",
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"I'm nice at ping pong"
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"My eyes are now wide open and now realize I've been used to spread messages I don't believe in. I am distancing myself from politics and completely focusing on being creative !!!",
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"There are so many lonely emojis",
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]
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st.json([pipe(d) for d in data])
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else:
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out = pipe(text)
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st.json(out)
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