Create app.py

app.py

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+import streamlit as st
+from PIL import Image
+import torch
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+
+# Load model and extractor
+model = AutoModelForImageClassification.from_pretrained("best.pt")
+extractor = AutoFeatureExtractor.from_pretrained("best.pt")
+
+st.title('Smoke Detection App')
+
+uploaded_image = st.file_uploader("Choose an image...", type="jpg")
+
+if uploaded_image is not None:
+    image = Image.open(uploaded_image)
+    st.image(image, caption='Uploaded Image.', use_column_width=True)
+    st.write("")
+    st.write("Classifying...")
+
+    inputs = extractor(images=image, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model(**inputs)
+    predictions = torch.argmax(outputs.logits, dim=1)
+
+    if predictions.item() == 1:
+        st.write("Smoke detected!")
+    else:
+        st.write("No smoke detected.")