Update app.py

app.py

@@ -8,12 +8,9 @@ pipe = pipeline("image-classification", model="trpakov/vit-face-expression", top
 # Streamlit app
 st.title("Emotion Recognition with vit-face-expression")
 
-# Slider for adjusting image size
-image_size = st.slider('Adjust the image size', min_value=50, max_value=500, value=200)
-
 # Slider example
-x = st.slider('Select a value')
-st.write(f"{x} squared is {x * x}")
+#x = st.slider('Select a value')
+#st.write(f"{x} squared is {x * x}")
 
 # Upload images
 uploaded_images = st.file_uploader("Upload images", type=["jpg", "png"], accept_multiple_files=True)
@@ -41,7 +38,7 @@ if st.button("Predict Emotions") and selected_images:
             predicted_class = results[i][0]["label"]
             predicted_emotion = predicted_class.split("_")[-1].capitalize()
             col = col1 if i == 0 else col2
-            col.image(selected_images[i], caption=f"Predicted emotion: {predicted_emotion}", use_column_width=True, width=image_size)
+            col.image(selected_images[i], caption=f"Predicted emotion: {predicted_emotion}", use_column_width=True)
             col.write(f"Emotion Scores: {predicted_emotion}: {results[i][0]['score']:.4f}")
             # Use the index to get the corresponding filename
             col.write(f"Original File Name: {uploaded_images[i].name}")  
@@ -64,10 +61,8 @@ if st.button("Predict Emotions") and selected_images:
         for i, (image, result) in enumerate(zip(selected_images, results)):
             predicted_class = result[0]["label"]
             predicted_emotion = predicted_class.split("_")[-1].capitalize()
-            st.image(image, caption=f"Predicted emotion: {predicted_emotion}", use_column_width=True, width=image_size)
+            st.image(image, caption=f"Predicted emotion: {predicted_emotion}", use_column_width=True)
             st.write(f"Emotion Scores for #{i+1} Image")
             st.write(f"{predicted_emotion}: {result[0]['score']:.4f}")
             # Use the index to get the corresponding filename
             st.write(f"Original File Name: {uploaded_images[i].name if i < len(uploaded_images) else 'Unknown'}")
-
-