Merge pull request #4118 from kuaashish:master
PiperOrigin-RevId: 513364683
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82ee00f25d
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@ -60,7 +60,7 @@ The second approach allows up to [`max_in_flight`] invocations of the
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packets from [`CalculatorBase::Process`] are automatically ordered by timestamp
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before they are passed along to downstream calculators.
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With either aproach, you must be aware that the calculator running in parallel
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With either approach, you must be aware that the calculator running in parallel
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cannot maintain internal state in the same way as a normal sequential
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calculator.
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@ -38,8 +38,8 @@ If you open a GitHub issue, here is our policy:
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- **OS Platform and Distribution (e.g., Linux Ubuntu 16.04)**:
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- **Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device**:
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- **Bazel version**:
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- **Android Studio, NDK, SDK versions (if issue is related to building in mobile dev enviroment)**:
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- **Xcode & Tulsi version (if issue is related to building in mobile dev enviroment)**:
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- **Android Studio, NDK, SDK versions (if issue is related to building in mobile dev environment)**:
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- **Xcode & Tulsi version (if issue is related to building in mobile dev environment)**:
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- **Exact steps to reproduce**:
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### Describe the problem
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@ -44,7 +44,7 @@ snippets.
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| Browser | Platform | Notes |
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| ------- | ----------------------- | -------------------------------------- |
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| Chrome | Android / Windows / Mac | Pixel 4 and older unsupported. Fuschia |
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| Chrome | Android / Windows / Mac | Pixel 4 and older unsupported. Fuchsia |
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| | | unsupported. |
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| Chrome | iOS | Camera unavailable in Chrome on iOS. |
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| Safari | iPad/iPhone/Mac | iOS and Safari on iPad / iPhone / |
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@ -66,7 +66,7 @@ WARNING: Download from https://storage.googleapis.com/mirror.tensorflow.org/gith
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```
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usually indicates that Bazel fails to download necessary dependency repositories
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that MediaPipe needs. MedaiPipe has several dependency repositories that are
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that MediaPipe needs. MediaPipe has several dependency repositories that are
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hosted by Google sites. In some regions, you may need to set up a network proxy
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or use a VPN to access those resources. You may also need to append
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`--host_jvm_args "-DsocksProxyHost=<ip address> -DsocksProxyPort=<port number>"`
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@ -143,7 +143,7 @@ about the model in this [paper](https://arxiv.org/abs/2006.10962).
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The [Face Landmark Model](#face-landmark-model) performs a single-camera face landmark
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detection in the screen coordinate space: the X- and Y- coordinates are
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normalized screen coordinates, while the Z coordinate is relative and is scaled
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as the X coodinate under the
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as the X coordinate under the
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[weak perspective projection camera model](https://en.wikipedia.org/wiki/3D_projection#Weak_perspective_projection).
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This format is well-suited for some applications, however it does not directly
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enable the full spectrum of augmented reality (AR) features like aligning a
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@ -48,7 +48,7 @@ camera, in real-time, without the need for specialized hardware. Through use of
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iris landmarks, the solution is also able to determine the metric distance
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between the subject and the camera with relative error less than 10%. Note that
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iris tracking does not infer the location at which people are looking, nor does
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it provide any form of identity recognition. With the cross-platfrom capability
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it provide any form of identity recognition. With the cross-platform capability
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of the MediaPipe framework, MediaPipe Iris can run on most modern
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[mobile phones](#mobile), [desktops/laptops](#desktop) and even on the
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[web](#web).
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@ -109,7 +109,7 @@ You can also find more details in this
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### Iris Landmark Model
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The iris model takes an image patch of the eye region and estimates both the eye
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landmarks (along the eyelid) and iris landmarks (along ths iris contour). You
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landmarks (along the eyelid) and iris landmarks (along this iris contour). You
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can find more details in this [paper](https://arxiv.org/abs/2006.11341).
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![iris_tracking_eye_and_iris_landmarks.png](https://mediapipe.dev/images/mobile/iris_tracking_eye_and_iris_landmarks.png) |
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@ -95,7 +95,7 @@ process new data sets, in the documentation of
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MediaSequence uses SequenceExamples as the format of both inputs and
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outputs. Annotations are encoded as inputs in a SequenceExample of metadata
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that defines the labels and the path to the cooresponding video file. This
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that defines the labels and the path to the corresponding video file. This
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metadata is passed as input to the C++ `media_sequence_demo` binary, and the
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output is a SequenceExample filled with images and annotations ready for
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model training.
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@ -180,7 +180,7 @@ and a
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The detection subgraph performs ML inference only once every few frames to
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reduce computation load, and decodes the output tensor to a FrameAnnotation that
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contains nine keypoints: the 3D bounding box's center and its eight vertices.
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The tracking subgraph runs every frame, using the box traker in
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The tracking subgraph runs every frame, using the box tracker in
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[MediaPipe Box Tracking](./box_tracking.md) to track the 2D box tightly
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enclosing the projection of the 3D bounding box, and lifts the tracked 2D
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keypoints to 3D with
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@ -623,7 +623,7 @@ z_ndc = 1 / Z
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### Pixel Space
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In this API we set upper-left coner of an image as the origin of pixel
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In this API we set upper-left corner of an image as the origin of pixel
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coordinate. One can convert from NDC to pixel space as follows:
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```
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