Update app.py

app.py

@@ -12,14 +12,8 @@ import numpy as np
 # Load the trained model
 model = load_model('cat_classifier_model.h5')
 
-# Function to predict whether an image contains a cat
-def predict_cat(image_content):
-    # Convert image content to PIL Image
-    img = Image.open(BytesIO(image_content))
-    img = img.convert('RGB')
-    img = img.resize((224, 224))
-
-    img_array = np.array(img)
+def predict_cat(image_pil):
+    img_array = np.array(image_pil)
     img_array = np.expand_dims(img_array, axis=0)
     img_array = img_array / 255.0  # Rescale to values between 0 and 1 (same as during training)
 
@@ -32,7 +26,7 @@ def predict_cat(image_content):
 # Create a Gradio interface
 iface = gr.Interface(
     fn=predict_cat,
-    inputs=gr.Image(type='file', label='Upload an image of a tablet'),
+    inputs=gr.Image(type='pil', label='Upload an image of a tablet'),
     outputs='text'
 )