Update app.py

app.py

@@ -1,18 +1,16 @@
 import gradio as gr
 import numpy as np
 
-classifier = pipeline("image-classification", model="Deepak-05-galey/image-dataset-model")
-
-# Function to classify images into 7 classes
+# Function to classify images into 5 classes
 def image_classifier(inp):
     # Dummy classification logic
     # Generating random confidence scores for each class
-    confidence_scores = np.random.rand(7)
+    confidence_scores = np.random.rand(5)
     # Normalizing confidence scores to sum up to 1
     confidence_scores /= np.sum(confidence_scores)
     # Creating a dictionary with class labels and corresponding confidence scores
     classes = ['bike', 'cars', 'cats', 'dogs', 'flowers']
-    result = {classes[i]: confidence_scores[i] for i in range(7)}
+    result = {classes[i]: confidence_scores[i] for i in range(5)}
     return result
 
 # Creating Gradio interface