Create prediction.py

prediction.py

@@ -0,0 +1,12 @@
+from tensorflow.keras.preprocessing import image
+import numpy as np
+
+def predict_class(model, image_path):
+    img = image.load_img(image_path, target_size=(100, 100))
+    img_array = image.img_to_array(img)
+    img_array = np.expand_dims(img_array, axis=0)
+    predictions = model.predict(img_array)
+    predicted_index = np.argmax(predictions[0])
+    classes = ['Banano', 'Durazno', 'Fresa', 'Guanabana', 'Guayaba', 'Kiwi', 'Limon', 'Lulo', 'Mandarina', 'Mango', 'Manzana', 'Manzana Verde', 'Melon', 'Mora', 'Naranja']
+    predicted_class = classes[predicted_index]
+    return predicted_class