Consistent crops
Apply one crop and composition workflow across a full batch of training images.
SDXL Dataset Builder
Turn mixed images into a consistent SDXL dataset.
Apply one crop, size, format and filename pattern to many images, then export matching captions and images together.
Free · No account · Local processing · Images + Caption TXT in ZIP
Matching Caption TXT
Create one text file per image using your own reusable caption template.
Private by design
Your images stay on your device while SwiftCrop processes and packages the dataset.
A faster SDXL dataset workflow
Go from an unorganized image folder to a consistent export in three steps.
1. Add images
Drop JPEG, PNG or WebP files into SwiftCrop and review the batch.
2. Set dataset options
Choose size, format, filename pattern, Dataset Name and Caption Template.
3. Export the ZIP
Download processed images with optional matching Caption TXT files.
Built for SDXL, DreamBooth and fine-tuning datasets
- Batch image resizing and cropping
- Portrait-aware composition adjustment
- Sequential, consistent filenames
- Image and Caption TXT pairs in one ZIP
Flexible output sizes
Quickly prepare 1024×1024 datasets or select another resolution for your setup.
SwiftCrop prepares files only; you remain in control of the training configuration and caption content.
Explore the AI Creator Hub
Prepare datasets for other popular image-generation workflows.
SDXL dataset FAQ
Is 1024×1024 required?
Not always. SwiftCrop offers 1024×1024 as a practical preset and also supports other or custom sizes.
Can I review crops before export?
Yes. You can inspect and manually adjust images before batch export.
Are images processed privately?
Yes. Processing stays in your browser and images are not uploaded to SwiftCrop servers.