DeepFace Based Batch Face Similarity Sorting Gradio APP For Windows, RunPod and Massed Compute - 1-Click to Install - Uses TensorFlow GPU - Very Fast

A batch face similarity sorting Gradio APP that utilizes DeepFace library - Extremely useful to sort AI generated images according to their

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Latest zip file : sort_by_similarity_v9.zip

22 July 2025 Update v9

Installer updated and errors fixed

23 June 2025 Update v8

• New option Use Best Match (Minimum Distance) added

• Printed messages on CMD significantly improved

• Multi-threading logic improved

• GPU usage logic improved

16 June 2025 Update

• Now supports RTX 5000 series GPUs too

• Now you can sort sub folders too

• This APP is based on DeepFace

  • https://github.com/serengil/deepface

• It is fully multi-threaded and higher batch size increase your processing speed

• Make sure to have accurately installed CUDA and cuDNN for TensorFlow library to use your GPU or else it will be ultra slow

• It uses minimal amount of VRAM so should work on every GPU pretty much

• What this APP does is that, it takes source images folder, target images folder and optionally extracted faces folder

• Then it calculates every target image similarity / distance to the source images individually (if multiple source images used it averages them) and at the end sort all target images according to their similarity / distance

• When you use more than 1 image in source images folder, it will sort according to the average of the source images but be careful it will increase processing time linearly since each image compared with each target image

• If few images gives error at first run, you can run again and it usually fixes error occurred images - i am still not sure why this happens - probably related to DeepFace library

• This app can be extremely useful to sort AI generated images according to the original training images to get the best ones comparatively

• The images in target folder will be renamed as the followings

• Image_Similarity_Rank - Image_Similarity_Score - Older File Name

  • e.g. image_rock.png will become 33 - 0.55 - image_rock.png

    • 33 is similarity rank, 0.55 is its distance (lesser is more similar)

• Following DeepFace models supported but I didn't test them except Facenet512 which is best

  

Windows Requirements

• Python 3.10, FFmpeg, CUDA 12.4, cuDNN 8.9 and 9.4+ (I am using 9.7 atm), C++ tools and Git

• If it doesn't work make sure to below tutorial and install everything exactly as shown in this below tutorial

• https://youtu.be/DrhUHnYfwC0

  • It should work with above version of CUDA 12.4 and cuDNN 8.9 but haven't tested

How To Install and Use:

Windows:

• First watch above requirements tutorial and follow every step

  • Extract zip archive into a drive like c:/face_sort

  • Longer directory path causes issues

  • Double click and install with Windows_Install.bat and that is it

  • Then run with Windows_Start_App.bat to start Similarity Sorter SECourses APP

  • And follow above and below attached screenshot

Massed Compute (Recommend Cloud) :

• Please register via this link : https://vm.massedcompute.com/signup?linkId=lp_034338&sourceId=secourses&tenantId=massed-compute

  • We have a special coupon for all GPUs : SECourses

    If you want to learn more about GPUs and prices read this link : https://www.patreon.com/posts/126671823

    Select RTX A6000 or Better GPU - like L40S or A6000 ADA or A100 or H100

  • Then select our image SECourses from Creator dropdown

  • Then follow Massed_Compute_Instructions_READ.txt

  • Same as my any other Massed Compute installer script

  • Example tutorial for learn how to install and use Massed Compute

    • (Starts at 12:58) : https://youtu.be/KW-MHmoNcqo?si=G1WbG-Qw4ujWvOtG&t=778

RunPod (Cloud):

• Please register via this link : https://get.runpod.io/955rkuppqv4h

  • Then follow Runpod_Instructions_READ.txt

  • Same as my any other RunPod installer script

  • Use the template written in Runpod_Instructions_READ.txt file

  • Example tutorial for learn how to install and use RunPod

    • (starts at 22:03) : https://youtu.be/KW-MHmoNcqo?si=QN8X8Sjn13ZYu-EU&t=1323