added square_padding for crops to maintain aspect ratio

app/demo/routes.py

@@ -150,7 +150,7 @@ def face_recognition():
     for i in range(len(names)):
         print(names[i],":",db_faces_features[i].shape)
     
-    # face_recognizer.set_face_db_and_mode(faces=faces,db_faces_features=db_faces_features,distance_mode="avg",recognition_mode="repeat")
+    # face_recognizer.set_face_db_and_mode(faces=names,db_faces_features=db_faces_features,distance_mode="avg",recognition_mode="repeat")
     face_recognizer.set_face_db_and_mode(faces=names,db_faces_features=db_faces_features,distance_mode="best",recognition_mode="repeat")
     
     face_detector.image_size=get_image_size(session["demo"]['settings']['fr_mode'])

app/face_detection/helper.py

@@ -1,7 +1,9 @@
 import cv2
 import numpy as np
+from app.face_detection.inference import square_pad
 
 
+square_maker=square_pad(color=(255,255,255))
 def get_crops(img,objs_found,aligner=None,resize:tuple=None):
     img_h,img_w,_=img.shape
     all_crops=[]
@@ -17,6 +19,7 @@ def get_crops(img,objs_found,aligner=None,resize:tuple=None):
             crop=aligner.align_image(crop)
             if crop is None: continue
         if resize is not None:
+            crop=square_maker(crop)
             crop=cv2.resize(crop,resize)
         all_crops.append(crop)
     

app/face_detection/inference.py

@@ -53,16 +53,18 @@ class square_crop:
         raise NotImplementedError
 
 class square_pad:
-    def __call__(self,img,color=(0,0,0)):
+    def __init__(self,color=(0,0,0)):
+        self.color=color
+    def __call__(self,img):
         h,w=img.shape[:2]
         self.w_added,self.h_added=0,0
         if h>w:
             self.w_added=int((h-w)/2)
-            padding=(np.ones([h,self.w_added,3])*np.array(color)[None,None,:]).astype("uint8")
+            padding=(np.ones([h,self.w_added,3])*np.array(self.color)[None,None,:]).astype("uint8")
             img=np.concatenate([padding,img,padding],axis=1)
         elif w>h:
             self.h_added=int((w-h)/2)
-            padding=(np.ones([self.h_added,w,3])*np.array(color)[None,None,:]).astype("uint8")
+            padding=(np.ones([self.h_added,w,3])*np.array(self.color)[None,None,:]).astype("uint8")
             img=np.concatenate([padding,img,padding],axis=0)
         h,w=img.shape[:2]