Cinemagraph Pro vs LivePortrait

Cinemagraph Pro turns video into cinemagraphs for photographers, marketers, and designers working on Mac, iPhone, or iPad. Users capture or import a clip, trim it, choose a still image, and paint over that image to reveal motion. On supported devices, the iOS app can capture, edit, and share 4K cinemagraphs; export quality depends on the source video. It can export H.264, HEVC, Live Photo, and GIF, share to social networks, save a Facebook Profile video, or export an Apple Live Photo. An Apple Watch can act as a remote shutter release or set a capture countdown. The app supports iCloud Drive and can upload work to Flixel for sharing and embedding; its App Store listing also mentions one-tap upload to Facebook Ad Manager. Flixel Cloud supports embedding motion imagery on websites, blogs, email campaigns, and digital displays, and advertises unlimited uploads. The product has a free plan and free trial. Listed paid options include $9.99 a month for Flixel Cloud Web and Cinemagraph Pro for iOS, and $299.99, paid once for License.

LivePortrait creates portrait video from a single image, using motion from video, audio, text, or generation. It also supports editing portrait video using a source video and a driving video. Stitching and eye and lip retargeting controls provide ways to adjust animation. The project supplies inference code, pretrained models, and a Gradio interface for local use, as well as a demo hosted on Hugging Face Spaces. Its PyTorch implementation is released under the MIT License, and the project reports generation speed of 12.8 ms on an RTX 4090 GPU with PyTorch. Human-mode instructions cover Linux, Windows, and Apple Silicon macOS; Intel macOS is untested. Animal models can animate cats, dogs, and pandas using human-driven motion, but animal mode is tested only on Linux and Windows with an NVIDIA GPU and is unsupported on macOS. Local setup requires git, conda, FFmpeg, Python 3.10, and downloaded pretrained weights. Commercial users must replace the included InsightFace detection models. Maintainers warn of possible deepfake misuse and visual artifacts.