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Module
Vladimir Mandic edited this page Nov 18, 2022
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3 revisions
Each module is fully self enclosed:
- Defined in a separate folder under
/src/
- Performs
load
andpredict
functions - Uses global configuration object
- Runs prediction on global input image
- Merges results into global results object
Define module that implements load
and predict
async methods:
export async function load(config: Config | any) { ... }
- loads specific model using
modelPath
configuration - returns
tf.GraphModel
export async function predict(image: Tensor, config: Config, idx: number, count: number) { ... }
- input image is already preprocessed and passed to predict method as tensor
- takes input tensor and resizes and normalizes it as needed
- optionally implements
skipFrames
for caching of results - optionally uses
idx
andcount
params to map cached objects to current objects - uses any other optional configuration params
- returns result object
in human.ts
:
- define model placeholder (
module.load()
stores model here) in the main constructor
in config.ts
:
- define configuration types
- set configuration defaul values
in result.ts
:
- define results type
in models.ts
:
- enable model loading sync and async by calling
module.load()
if model works on full image, execute from human.ts
if model works on face image, execute from face.ts
- add results placeholder
- implement calls to
module.predict()
for sync and async - merge results object
- For simple module that works on pre-detected face tensor,
follow existing module defintion isemotion/emotion.ts
- For simple module that works on a full image tensor,
follow existing module definition inobject/centernet.ts
Human Library Wiki Pages
3D Face Detection, Body Pose, Hand & Finger Tracking, Iris Tracking, Age & Gender Prediction, Emotion Prediction & Gesture Recognition