Ultimate Image Processing APP : Batch Cropping, Zooming In, Resizing, Duplicate Image Removing, Face Extraction, SAM 2 and Yolo Segmentation, Masking for Windows, RunPod, Massed Compute and Free Kaggle Account

Batch Image Cropping, Zooming Subject, Resizing, Segmenting, Masking, Duplicate Removing APP that utilizes YOLO V11, SAM 2 and Gradio

Patreon exclusive posts index to find our scripts easily, Patreon scripts updates history to see which updates arrived to which scripts and amazing Patreon special generative scripts list that you can use in any of your task.

Join discord to get help, chat, discuss and also tell me your discord username to get your special rank : SECourses Discord

Please also Star, Watch and Fork our Stable Diffusion & Generative AI  GitHub repository and join our Reddit subreddit and follow me on LinkedIn (my real profile)

=======

Latest zip file : Ulti_Img_Process_V24.zip

Screenshots zip file : how_to_use_screenshots.zip

We have 1-Click installer for Windows, Massed Compute and a Free Kaggle Notebook. Read this post extremely carefully to learn how to use all

Video Tutorial : Hopefully coming soon

25 October 2025 Update V24

• Libraries updated to Torch 2.8, CUDA 12.9

  • With pre compiled xFormers, Flash Attention, Sage Attention and groundingdino

  • For all of the GPUs starting from RTX 1000 series to 5000 series or Cloud GPUs like A100, B200, etc

Windows Requirements

• Python 3.10, FFmpeg, CUDA 12.9, cuDNN 9.12 or above, 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

  • Follow tutorial along with this post : https://www.patreon.com/posts/click-to-open-post-used-in-tutorial-111553210

1 September 2025 Update V23

• Image batch resize cancel fixed

• Some errors regarding batch processing on Linux fixed

• Just extract latest zip file and overwrite older files for update

25 August 2025 Update V22

• SAM2 based auto cropping logic significantly improved

  • Now it will zoom into the maximum degree and leave no empty space

• Moreover, auto crop section now have pixel or percent based padding, so if it too agressively zoom in, you can set some padding

• If you are processing trasnparency having images, uncheck Save as PNG

  • Now when Save as PNG is unchecked, it will first convert to JPG and then process thus the processing will have 0 errors

  • Previously when you auto crop transparent pixels having png files, it wanst working properly

22 August 2025 Update V21

• New feature implemented upon request : Skip images with no SAM2 detection

• yolov11l-face.pt selection in Select Detection Class (YOLO) was not working and fixed

• Default selection of Select Detection Class (YOLO) is now set to person

• Just overwrite previous files to upgrade from V20

11 July 2025 Update V19

• Face Extraction tab improved and now it uses super fast yolov11l-face.pt

• Moreover now it supports all Yolo classes and SAM2 segment as well

  • So you can extract other than faces as well

• All with multi-threading support

• Run Windows install again, if you get any error delete venv folder and run install again

2 June 2025 Update V15

• A bug in SAM based automatic cropping fixed now should work perfect hopefully

• Now app supports RTX 5000 series on RunPod and Massed Compute as well

  • I have compiled groundingdino for Linux to make this happen

• Just overwrite older files with newest zip content to update

24 April 2025 Update V14

• Negative prompt feature implemented to SAM 2 Batch Segmentation APP by SECourses

  • Run Start_Segmenter.bat to start this app

• The logic of negative prompt fairly simple

  • For example positive prompt face.

    • Negative prompt eye.

    • So you get face masked with eyes being unmasked

  • It mask the face, mask the eyes, and subtract eyes from face mask

• Negative prompt masks auto saved inside generated_negative_masks folder

• Extract newest zip file into previous folder for update

24 April 2025 Update

• Windows Installer updated to support RTX 5000 series fully

• I have compiled xFormers and groundingdino with latest official Torch 2.7 for making this work

• Also a new amazing feature Generate Tiled Images implemented

  • This tiled image generation can be used to improve small details of training subject, especially useful for items, objects, products

Ultimate Batch Image Processing Gradio APP by SECourses

• Use Windows_Start_App.bat to start this APP

• This APP has the following features. Please look at the full screenshots to understand how it works exactly

• Image Cropper

  • This TAB is extremely useful to zoom in and crop the subjects

  • It supports YOLO Segmentation and also state of the art Grounded SAM 2

  • With Grounded SAM 2 you can use any keyword to mask / segment and zoom in subjects like person, ear, lips, tanks, cars, t-shirt, etc.

  • How this tab works is that you enter your desired aspect ratios - enter your desired resolutions here so that it will generate accurate folder names for batch image resize

  • After finding the subject in processed image like person, it gets it. And then it starts to expand it in the least possible amount to reach your desired aspect ratio like cropping 1920x1080 image into 1024x1024 aspect ratio with subject focus being person

  • Then it saves these images with full resolution with crop / zoom in into given folder

  • The folder structure is extremely important so look very carefully and read the screenshot images - it shows all

  • This processing will never cut / remove any part of the subject so it won't reach desired aspect ration in every case, the Image Resizer tab will cut the image and obtain desired aspect ratio and resolution exactly

  • This tab is fully multi-threaded and supports running on multiple GPU as well

• Image Resizer

  • This is the second stage of processing images but of course can be used standalone as well

  • Give the Output Folder of the image cropping processing

  • It will then look for subfolders with the exact same names of your desired target resolutions

  • E.g. you want your images to be 1024x1024 pixel then it will look sub folder named as 1024x1024

  • Again look at the screenshots very carefully to understand how it works

  • This tab will crop / cut subject as well to reach the desired target aspect ratio and then it will downscale the image into the desired resolution

  • When cutting body parts of human, it will focus on face and will not part the direction of the image that contains the face

  • You can also use Resize without cropping (center image and add white background) option as well

  • This tab is fully multi-threaded and it runs on CPU

• Move Low-Res Files 

  • WIP not tested yet but should be working

• Rename Files 

  • WIP not tested yet but should be working

• Extract Faces

  • With this tab you can extract faces from given folder

  • It will automatically find the face in given image and save it into desired folder

  • You can also set positive or negative padding depending on your requirement

  • This tab is fully multi-threaded

• Find Duplicates

  • This tab is extremely useful to find duplicate images in given folder and move them to the target folder

  • It supports following algorithms and default parameters working decent:

    • aHash (Average Hash) : How it works: Calculates the average color of the image, then creates a hash based on whether each pixel is brighter or darker than the average.

    • dHash (Difference Hash): How it works: Similar to aHash but compares the difference in brightness between adjacent pixels.

    • pHash (Perceptual Hash): How it works: Uses the Discrete Cosine Transform (DCT) to focus on low-frequency components, making it robust to minor changes.

    • wHash (Wavelet Hash): How it works: Uses Wavelet transform to capture image details at different scales.

    • ColorHash: How it works: Creates a hash based on the color histogram of the image.

    • KAZE: How it works: Detects and describes local features in images using non-linear scale spaces, making it robust to scale, rotation, and some level of viewpoint change.

    • Multi-Hash: How it works: Combines multiple hashing algorithms (aHash, dHash, pHash, wHash, ColorHash, KAZE) to improve overall accuracy.

  • This tab is fully multi-threaded and it was super hard to code this one as multi-threaded

SAM 2 Batch Segmentation Gradio APP by SECourses

• Use Start_Segmenter.bat to start this APP

• It is built upon Grounded-SAM-2

  • https://github.com/IDEA-Research/Grounded-SAM-2

• This APP is super important to decide your subject finding / masking prompt and Box Threshold and Text Threshold

• After finding parameters, you can use them in your Batch Processing APP with SAM 2 prompting box instead of YOLO

• It will automatically save every Mask and Segmented Image into outputs folder

• It supports fully folder Batch Processing as well

• It is fully multi-threaded and supports multi-GPU as well, it was really hard to code in Python

• Look and read the screenshots very carefully to learn how to use it

• You can use generated Masks in training like in Kohya training as well

How To Install and Use:

Windows:

• First watch above requirements tutorial and follow every step

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

  • 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 Ultimate Batch Processing APP

  • To run Segmentation APP run with Start_Segmenter.bat

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

Kaggle (Free Cloud - Not Recommend):

• Register Kaggle for free and verify your phone number : https://www.kaggle.com/

• Upload the Kaggle notebook file from downloaded attachments

• Follow the instructions on the Kaggle notebook

• How to Use Kaggle Notebooks General Tutorial

  • (Starts at 27:34) https://youtu.be/KW-MHmoNcqo?si=vkKTvWHbZVrn4x7h&t=1654