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MediaPipe Team 2020-11-04 19:46:41 -05:00 committed by chuoling
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3 changed files with 13 additions and 13 deletions

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@ -59,12 +59,12 @@ MediaPipe Python package is available on
[PyPI](https://pypi.org/project/mediapipe/), and can be installed simply by `pip
install mediapipe` on Linux and macOS, as described in:
* [MediaPipe Face Mesh](../solutions/pose.md#python) and
[colab](https://mediapipe.page.link/face_mesh_py_colab)
* [MediaPipe Hands](../solutions/pose.md#python) and
[colab](https://mediapipe.page.link/hands_py_colab)
* [MediaPipe Pose](../solutions/pose.md#python) and
[colab](https://mediapipe.page.link/pose_py_colab)
* [MediaPipe Face Mesh](https://google.github.io/mediapipe/solutions/face_mesh#python)
([colab](https://mediapipe.page.link/face_mesh_py_colab))
* [MediaPipe Hands](https://google.github.io/mediapipe/solutions/hands#python)
([colab](https://mediapipe.page.link/hands_py_colab))
* [MediaPipe Pose](https://google.github.io/mediapipe/solutions/pose#python)
([colab](https://mediapipe.page.link/pose_py_colab))
## MediaPipe on the Web

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@ -59,12 +59,12 @@ MediaPipe Python package is available on
[PyPI](https://pypi.org/project/mediapipe/), and can be installed simply by `pip
install mediapipe` on Linux and macOS, as described in:
* [MediaPipe Face Mesh](../solutions/pose.md#python) and
[colab](https://mediapipe.page.link/face_mesh_py_colab)
* [MediaPipe Hands](../solutions/pose.md#python) and
[colab](https://mediapipe.page.link/hands_py_colab)
* [MediaPipe Pose](../solutions/pose.md#python) and
[colab](https://mediapipe.page.link/pose_py_colab)
* [MediaPipe Face Mesh](https://google.github.io/mediapipe/solutions/face_mesh#python)
([colab](https://mediapipe.page.link/face_mesh_py_colab))
* [MediaPipe Hands](https://google.github.io/mediapipe/solutions/hands#python)
([colab](https://mediapipe.page.link/hands_py_colab))
* [MediaPipe Pose](https://google.github.io/mediapipe/solutions/pose#python)
([colab](https://mediapipe.page.link/pose_py_colab))
## MediaPipe on the Web

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@ -20,7 +20,7 @@ through a machine learning (ML) model, trained on a newly created 3D dataset.
![objectron_shoe_android_gpu.gif](../images/mobile/objectron_shoe_android_gpu.gif) | ![objectron_chair_android_gpu.gif](../images/mobile/objectron_chair_android_gpu.gif) | ![objectron_camera_android_gpu.gif](../images/mobile/objectron_camera_android_gpu.gif) | ![objectron_cup_android_gpu.gif](../images/mobile/objectron_cup_android_gpu.gif)
:--------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------:
*Fig 1(a). Objectron for Shoes.* | *Fig 1(b). Objectron for Chairs.* | *Fig 1(c). Objectron for Cameras.* | *Fig 1(d). Objectron for Cups.*
*Fig 1a. Shoe Objectron* | *Fig 1b. Camera Objectron* | *Fig 1c. Camera Objectron* | *Fig 1d. Cup Objectron*
Object detection is an extensively studied computer vision problem, but most of
the research has focused on