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

Installers and APP is shared here with instructions : https://www.patreon.com/posts/120352012

APP : https://www.patreon.com/posts/120352012

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

Screenshots and How To Use : how_to_use_screenshots.zip

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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