Portrait-aware crop
Detects faces and adjusts their position for a more consistent training dataset.
SwiftCrop AI Dataset
Prepare LoRA & FLUX training images in your browser
Batch crop images to 1024×1024, automatically position portraits, and export a consistent dataset without uploading your images to a server.
Free · No account · No installation · JPEG / PNG / WebP
Batch processing
Apply one size, format and quality setting to many images, then download them together.
No image uploads
Detection, cropping, resizing and ZIP creation run locally in your browser.
A consistent dataset in three steps
The dataset entry automatically selects 1024×1024, JPEG quality 95 and sequential filenames.
Add your images
Use drag and drop, file selection, or paste images directly from the clipboard.
Auto-adjust portraits
SwiftCrop automatically adjusts image composition. You can still fine-tune any image manually.
Export in batch
Create consistent JPEG files and download them together as a ZIP on desktop.
Useful for
- LoRA training image preprocessing
- FLUX, Stable Diffusion and SDXL datasets
- DreamBooth and portrait dataset composition
- Bulk square cropping and resizing
Default setup
- Output: 1024 × 1024 px
- JPEG at 95% quality
- Filename: dataset_###
- Auto crop after adding images
AI Creator Hub
Explore model-specific dataset preparation guides.
Frequently asked questions
Can I prepare LoRA training images?
Yes. SwiftCrop supports batch cropping, resizing, portrait positioning, and sequential filenames.
Does it work for FLUX and SDXL?
Yes. It can prepare image datasets for FLUX, Stable Diffusion, SDXL, DreamBooth, and similar workflows.
Are my images uploaded or stored?
No. Your images remain on your device and are processed inside the browser.
Do I have to use 1024×1024?
No. You can change the output to 512×512, 768×768, or any custom dimensions in the main tool.
Spend less time preparing training images.
Open SwiftCrop with the dataset settings already applied.
Start for free