Update app.py

app.py

@@ -8,6 +8,7 @@ import numpy as np
 from scipy import ndimage
 from PIL import Image
 import matplotlib.pyplot as plt
+import cv2
 model = load_model('Densenet.h5')
 model.load_weights("pretrained_model.h5")
 layer_name = 'conv5_block16_concat'
@@ -63,11 +64,14 @@ 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
+    zoom_factor = 1.2 
+    zoomed_img = cv2.resize(img_array, (0, 0), fx=zoom_factor, fy=zoom_factor)
+
+# Crop the zoomed image to maintain the original size
+    zoomed_img = zoomed_img[:224, :224, :]# 20% zoom
     
-    img_array = np.expand_dims(img_array, axis=0)
+    img_array = np.expand_dims(zoomed_img, axis=0)
     img_array = preprocess_input(img_array)
-    img_array = ndimage.zoom(img_array, zoom_factor, order=1)
 
 
     predictions1 = model.predict(img_array)