Update app.py

app.py

@@ -1,19 +1,9 @@
 import gradio as gr 
-from transformers import pipeline
-import gradio as gr 
 import pandas as pd 
 from ultralytics import YOLO
 from skimage import data
 from PIL import Image
  
-pipe = pipeline("text-classification")
-def clf(text):
-    result = pipe(text)
-    label = result[0]['label']
-    score = result[0]['score']
-    res = {label:score,'POSITIVE' if label=='NEGATIVE' else 'NEGATIVE': 1-score}
-    return res 
- 
 model = YOLO('yolov8n-cls.pt')
 def predict(img):
     result = model.predict(source=img)
@@ -23,8 +13,7 @@ def predict(img):
     df = df.sort_values('probs',ascending=False)
     res = dict(zip(df['names'],df['probs']))
     return res
-demo = gr.Interface(fn=clf, inputs="text", outputs="label")
+gr.close_all() 
 demo = gr.Interface(fn = predict,inputs = gr.Image(type='pil'), outputs = gr.Label(num_top_classes=5), 
                     examples = ['cat.jpeg','people.jpeg','coffee.jpeg'])
-gr.close_all()
-demo.launch(share=True)
+demo.launch()