Add app.py

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from tensorflow.keras.models import load_model
+from PIL import Image
+import numpy as np
+
+model = load_model('pokemon_classifier_model.keras') 
+
+def predict_image(img):
+    img = img.resize((224, 224)) 
+    img = np.array(img)
+    img = img / 255.0  
+    img = np.expand_dims(img, axis=0)  
+
+    prediction = model.predict(img)  
+    labels = ['Pikachu', 'Sandshrew', 'Squirtle']  
+    return {labels[i]: float(prediction[0][i]) for i in range(len(labels))}
+
+iface = gr.Interface(fn=predict_image,
+                     inputs=gr.inputs.Image(shape=(224, 224)),
+                     outputs=gr.outputs.Label(num_top_classes=3),
+                     title="Pokémon Classifier",
+                     description="Upload an image of Pikachu, Sandshrew, or Squirtle and the classifier will predict which one it is.")
+
+iface.launch()