Update app.py

app.py

@@ -1,48 +1,25 @@
 import streamlit as st
 from transformers import pipeline
 from PIL import Image
-import numpy as np
-from transformers import AutoFeatureExtractor, AutoModelForImageClassification
+classifier = pipeline("image-classification", model="google/vit-base-patch16-224")
+def get_img_from_url(url):
+    return Image.open(requests.get(url, stream=True).raw)
 
-classifier = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")
 def main():
-    st.title("text-classification")
+    st.title("Yelp review")
 
     with st.form("text_field"):
-        uploaded_file = st.file_uploader("Upload Files",type=['png','jpeg','jpg'])
+        text = st.text_area('enter some text:')
+        url = st.text_input("URL to some image", "https://images.livemint.com/img/2022/08/01/600x338/Cat-andriyko-podilnyk-RCfi7vgJjUY-unsplash_1659328989095_1659328998370_1659328998370.jpg")
+        img = get_img_from_url(url)
+        # clicked==True only when the button is clicked
         clicked = st.form_submit_button("Submit")
         if clicked:
-            uploaded_file = st.file_uploader("Upload Files",type=['png','jpeg','jpg'])
-    
-            if uploaded_file!=None:
+          results = classifier([text])
+          st.json(results)
+
+
 
-                img=Image.open(uploaded_file)
-        
-                extractor = AutoFeatureExtractor.from_pretrained("yangy50/garbage-classification")
-                model = AutoModelForImageClassification.from_pretrained("yangy50/garbage-classification")
-        
-                inputs = extractor(img,return_tensors="pt")
-                outputs = model(**inputs)
-                label_num=outputs.logits.softmax(1).argmax(1)
-                label_num=label_num.item()
-        
-                st.write("The prediction class is:")
-        
-                if label_num==0:
-                    st.write("cardboard")
-                elif label_num==1:
-                    st.write("glass")
-                elif label_num==2:
-                    st.write("metal")
-                elif label_num==3:
-                    st.write("paper")
-                elif label_num==4:
-                    st.write("plastic")
-                else:
-                    st.write("trash")
-        
-                st.image(img)
-                   
     
 if __name__ == "__main__":
     main()