Create app.py

app.py

@@ -0,0 +1,19 @@
+from transformers import pipeline
+
+classifier = pipeline("image-classification", model="KayDee03/Fruits-model")
+
+import numpy as np
+
+# Function to classify images into 4 classes
+def image_classifier(inp):
+    confidence_scores = np.random. rand(4)
+    confidence_scores /= np.sum(confidence_scores)
+    classes = ['Avocado', 'Banana', 'Guava', 'Mango']
+    result = {classes[i]: confidence_scores[i] for i in range(4)}
+    return result
+
+import gradio as gr
+# Creating Gradio interface
+demo = gr.Interface(fn=image_classifier, inputs="image", outputs="label")
+demo. launch()
+