image resizing for big images

app.py

@@ -12,6 +12,7 @@ from PIL import Image
 def process_image(img):
     cv2_face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 
                                              'haarcascade_frontalface_default.xml')
+    img = resize_img(img)
     img, _ = annotate_objects_in_image(img, 
                                        cv2_face_cascade, 
                                        model.labeldict, 
@@ -20,7 +21,6 @@ def process_image(img):
     return(img)
 
 def annotate_objects_in_image(img, obj_cascade, labeldict, model):
-    #img = cv2.flip(img, 1)
     gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
     objects = obj_cascade.detectMultiScale(gray, 1.1, 4)
     model_result = ""
@@ -44,6 +44,13 @@ def predict_emotion_from_image (face_raw, labeldict, model):
     emotion = labeldict[prediction]
     return (emotion)
 
+def resize_img(img):
+    if img.shape[0]> 960:
+        img_AR = img.shape[0]/img.shape[1]
+        #print(f'img shape: {img.shape}; aspect ratio: {img_AR}')
+        img = cv2.resize(img, (640, int(np.round(640*img_AR))))
+    return img
+
 class ModelClass:
     def __init__(self,name='EDA_CNN.h5'):
         self.name = name