Update app.py

app.py

@@ -5,6 +5,7 @@ import gradio as gr
 from tensorflow.keras.preprocessing.image import load_img, img_to_array
 from tensorflow.keras.applications.densenet import preprocess_input, decode_predictions
 import numpy as np 
+from scipy import ndimage
 from PIL import Image
 import matplotlib.pyplot as plt
 model = load_model('Densenet.h5')
@@ -64,6 +65,11 @@ def classify_image(img):
     mean = np.mean(img_array, axis=(0, 1))
     std = np.std(img_array, axis=(0, 1))
     img_array = (img_array - mean) / std
+    zoom_factor = 1.2  # 20% zoom
+    img_array = ndimage.zoom(img_array, zoom_factor)
+
+# Crop the zoomed image to maintain the original size
+zoomed_img = zoomed_img[:224, :224, :]
 
 
     predictions1 = model.predict(img_array)