mediapipe/docs/solutions/models.md
2023-04-03 17:44:07 -07:00

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MediaPipe Models and Model Cards

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Attention: Thank you for your interest in MediaPipe Solutions. We have ended support for these MediaPipe Legacy Solutions as of March 1, 2023. All other MediaPipe Legacy Solutions will be upgraded to a new MediaPipe Solution. The code repository and prebuilt binaries for all MediaPipe Legacy Solutions will continue to be provided on an as-is basis. We encourage you to check out the new MediaPipe Solutions at: https://developers.google.com/mediapipe/solutions


Face Detection

Full-range dense and sparse models have the same quality in terms of F-score however differ in underlying metrics. The dense model is slightly better in Recall whereas the sparse model outperforms the dense one in Precision. Speed-wise sparse model is ~30% faster when executing on CPU via XNNPACK whereas on GPU the models demonstrate comparable latencies. Depending on your application, you may prefer one over the other.

Face Mesh

Iris

Hands

Pose

Holistic

Selfie Segmentation

Hair Segmentation

Object Detection

Objectron

KNIFT