Cutout.Pro vs DDColor

Cutout.Pro removes image backgrounds and can replace them with other backgrounds. It accepts JPG, PNG, WEBP and BMP files up to 15 MB, with output up to 4096 × 4096 pixels in PNG or JPG. An Erase & Restore brush lets users refine missed background areas or clipped foreground details. Batch processing is available; the Windows and Mac desktop app can process folders. Other access includes Android, iOS, Linux, web and API. Each upload receives a low-resolution preview without a watermark, account or credits, while an HD image download uses one credit. New accounts receive five credits without a credit card. The free plan is available, and the listed subscription with 80 credits per month costs $5 a month. Other subscription and pay-as-you-go credit packages are listed. Main-platform credit purchases have a 14-day refund guarantee, but Shopify App credit purchases are non-refundable. Cutout.Pro was founded in 2018 and is based in Kowloon, Hong Kong.

DDColor is a free model for adding color to historical black-and-white photos and recoloring anime-game landscapes. It uses multi-scale visual features to optimize learnable color tokens for automatic colorization. The repository offers paper, ModelScope, artistic and tiny pretrained variants; the maker recommends ModelScope for images outside ImageNet and identifies tiny as the lightest option. Local inference scripts and a runnable Gradio demo are documented, alongside inference guidance for Hugging Face Hub and ModelScope. The repository also links to Replicate demos and an API. Users can train with ImageNet or a custom dataset, and the documentation covers ONNX export with an example using the tiny model. Requirements are Python 3.7 or later and PyTorch 1.7 or later. The repository includes an Apache License, Version 2.0, and lists no paid plans or product usage limits. One stated limitation is that colorfulness loss can result in unattractive color blocks, including red artifacts.