Initial commit

README.md

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+---
+title: Market Recommendations Lite
+emoji: 👀
+colorFrom: red
+colorTo: blue
+sdk: streamlit
+sdk_version: 1.10.0
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+

app.py

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+import streamlit as st
+from transformers import pipeline
+from PIL import Image
+
+pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
+
+st.title("Hot Dog? Or Not?")
+
+file_name = st.file_uploader("Upload a hot dog candidate image")
+
+if file_name is not None:
+  col1, col2 = st.columns(2)
+
+  image = Image.open(file_name)
+  col1.image(image, use_column_width=True)
+  predictions = pipeline(image)
+
+  col2.header("Probabilities")
+  for p in predictions:
+    col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")

requirements.txt

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+faiss
+transformers
+torch