tfjs-models | Pretrained models for TensorFlow.js | Machine Learning library

I'm trying to use tfjs-models/universal-sentence-encoder within a React Native app by following these instructions. However, I get the following error when I try to load the model:

I am trying to change the shape and position of eyes and lips and for this purpose I use tenserflow.js face-landmark-detection model. I get the all 468 facial landmarks but the problem is i don't know and i never find any solution on internet how to get the position of only required landmark like lips and eyes. I get all the points but want to apply changes on lips and eyes how i apply changes only on these landmarks.

I try to run deep lab model javascript on video here but I get the error Unhandled Rejection (Error): The dtype of dict['ImageTensor'] provided in model.execute(dict) must be int32, but was float32 , here is my code

As in the following js code, I am loading the model as a promise: tf.loadLayersModel('../tfjs-models/hadwritten-digits/model.json')

Now, I am using model.predict that will return an tensor of shape (1, 128, 128, 1) i.e. one grayscale image. I am having a lot of issue now on with promises and awaits. I have a canvas with known id in index.html, I want to put the image into. Needed some help now.

I am building an Expo app using redux-saga and tensorflow js. The model has to be loaded async when initializing the app. In all the examples, the model is loaded in a component and stored in the component's state.

I would like however to perform inference in a saga and not directly in the component.

I don't know how to write the initialization process so as to be able to access the loaded model from within the saga.

In App.js I have the following:

I have downloaded a pre-trained PoseNet model for Tensorflow.js (tfjs) from Google, so its a json file.

However, I want to use it on Android, so I need the .tflite model. Although someone has 'ported' a similar model from tfjs to tflite here, I have no idea what model (there are many variants of PoseNet) they converted. I want to do the steps myself. Also, I don't want to run some arbitrary code someone uploaded into a file in stackOverflow:

Caution: Be careful with untrusted code—TensorFlow models are code. See Using TensorFlow Securely for details. Tensorflow docs

Does anyone know any convenient ways to do this?

I'm attempting to use TensorFlow face mesh(JS) for a simple face tracker. I've used the standard code on the site but I'm getting an error for height: Uncaught (in promise) TypeError: Cannot read property 'height' of null at facemesh:17 at L.estimateFaces (facemesh:17) at main ((index):76)

I'm new to JS but I can't work out where I am going wrong. Any help would be much appreciated.

TensorFlow code: https://github.com/tensorflow/tfjs-models/tree/master/facemesh

MyCode:

I'm trying to load a model.json file with it's weights.bin from the root directory in my react app.

When I call an example I found online from storage.googleapis.com it works but loading from my root doesn't.

The contents of App.js in my react app...