Update app.py

app.py

@@ -6,7 +6,15 @@ from sklearn.tree import DecisionTreeClassifier
 from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, GradientBoostingClassifier
 import joblib
 import pickle
-
+def load_image(image_path):
+    """
+    Load image from file path and convert to numpy array
+    """
+    with Image.open(image_path).convert('L') as img:
+        img = img.resize((28,28))
+        img = np.array(img)
+    return img
+    
 def fashion_MNIST_prediction(test_image, model='KNN'):
     test_image_flatten = test_image.reshape((-1, 28*28))
     fashion_mnist = tf.keras.datasets.fashion_mnist
@@ -51,7 +59,14 @@ def fashion_MNIST_prediction(test_image, model='KNN'):
 
     else:
         return "Invalid Model Selection"
-    
+        ###
+    def predict(image_path, model):
+    test_image = load_image(image_path)
+    label, prediction = fashion_MNIST_prediction(test_image, model)
+    return label, prediction
+
+image_paths = ['Ankle boot.jpg', 'bag.jpg', 'dress.jpg', 't-shirt.jpg']
+###
 input_image = gr.inputs.Image(shape=(28, 28), image_mode='L')
 input_model = gr.inputs.Dropdown(['KNN', 'DecisionTreeClassifier', 'RandomForestClassifier', 'AdaBoostClassifier', 'GradientBoostingClassifier'])