text: Title: different implementations of face_align.py  (mode=arcface) results in different results 
  Body: In this repo, there are two implementations of face_align.py
  
  
  https://github.com/deepinsight/insightface/blob/master/python-package/insightface/utils/face_align.py
  
  https://github.com/deepinsight/insightface/blob/master/web-demos/src_recognition/face_align.py
  
  
  By modifying this example, 
  https://github.com/deepinsight/insightface/blob/master/examples/demo_analysis.py
  I got the following results using buffalo_l model pack.
  
  det_size was set to 320 in both cases.
  and image_size (used in estimate_norm of face_align.py) was set to 112, 224 and 256 respectively.
  (after alignment, the results were resized to 256x256 for comparison)
  
  Upper row : the results of python-package face_align.py
  Lower row : that of web-demos face_align.py 
  
  ![arc](https://github.com/deepinsight/insightface/assets/10891291/8f75d5ca-ce6d-4499-b085-ab614e696566)
  
  
  
  In mode='arcface'
  When image_size was 112 and 224, there were no differences.
  However, if 256 is used, face_align.py of python-package yields a different result.
  
  
  It seems that whether "diff_x" is used or not affects the result.
  In 256 case, face_align.py of web-demos has the correct result... right?
  
  
  In mode='None'
  All of the results are same.
  ![None](https://github.com/deepinsight/insightface/assets/10891291/94a9f2de-6c4a-4d61-a6e1-2f641d1d48a7)
  
  
  One more question,
  In which configuration, recognition Model of antelopev2 and buffalo_l were trained?
  I mean the hyperparameters to get the aligned training set (image_size of estimate_norm, det_size .. etc)
  
  
  