Project import generated by Copybara.

GitOrigin-RevId: d38dc934bcd08e03061c37d26d36da216456d10d

docs/solutions/face_mesh.md

@@ -44,7 +44,7 @@ prediction accuracy. In addition, in our pipeline the crops can also be
 generated based on the face landmarks identified in the previous frame, and only
 when the landmark model could no longer identify face presence is the face
 detector invoked to relocalize the face. This strategy is similar to that
-employed in our [MediaPipe Hand](./hand.md) solution, which uses a palm detector
+employed in our [MediaPipe Hands](./hands.md) solution, which uses a palm detector
 together with a hand landmark model.
 
 The pipeline is implemented as a MediaPipe

docs/solutions/hands.md

@@ -5,7 +5,7 @@ parent: Solutions
 nav_order: 3
 ---
 
-# MediaPipe Hand
+# MediaPipe Hands
 {: .no_toc }
 
 1. TOC
@@ -23,7 +23,7 @@ naturally to people, robust real-time hand perception is a decidedly challenging
 computer vision task, as hands often occlude themselves or each other (e.g.
 finger/palm occlusions and hand shakes) and lack high contrast patterns.
 
-MediaPipe Hand is a high-fidelity hand and finger tracking solution. It employs
+MediaPipe Hands is a high-fidelity hand and finger tracking solution. It employs
 machine learning (ML) to infer 21 3D landmarks of a hand from just a single
 frame. Whereas current state-of-the-art approaches rely primarily on powerful
 desktop environments for inference, our method achieves real-time performance on
@@ -38,7 +38,7 @@ and new research avenues.
 
 ## ML Pipeline
 
-MediaPipe Hand utilizes an ML pipeline consisting of multiple models working
+MediaPipe Hands utilizes an ML pipeline consisting of multiple models working
 together: A palm detection model that operates on the full image and returns an
 oriented hand bounding box. A hand landmark model that operates on the cropped
 image region defined by the palm detector and returns high-fidelity 3D hand

docs/solutions/solutions.md

@@ -20,7 +20,7 @@ has_toc: false
 :---------------------------------------------------------------------------- | :-----: | :-: | :-----: | :-: | :---:
 [Face Detection](https://google.github.io/mediapipe/solutions/face_detection)       | ✅       | ✅   | ✅       | ✅   | ✅
 [Face Mesh](https://google.github.io/mediapipe/solutions/face_mesh)                 | ✅       | ✅   | ✅       |     |
-[Hand](https://google.github.io/mediapipe/solutions/hand)                           | ✅       | ✅   | ✅       | ✅   |
+[Hands](https://google.github.io/mediapipe/solutions/hands)                         | ✅       | ✅   | ✅       | ✅   |
 [Hair Segmentation](https://google.github.io/mediapipe/solutions/hair_segmentation) | ✅       |     | ✅       | ✅   |
 [Object Detection](https://google.github.io/mediapipe/solutions/object_detection)   | ✅       | ✅   | ✅       |     | ✅
 [Box Tracking](https://google.github.io/mediapipe/solutions/box_tracking)           | ✅       | ✅   | ✅       |     |