Comments (3)
Hi, @ZhongxuYang
Thank you for bringing this issue to our attention and as far I know, you can download model from kaggle here is link and please make sure select only Model Variations as TensorFlow.js option and download whichever model you want to use and once model got downloaded then please try to load the model with the help of below code snippet and it should work
const tf = require('@tensorflow/tfjs-node');
const modelPath = '/path/to/your/model.json';
const handler = tf.io.fileSystem(modelPath);
const model = await tf.loadLayersModel(handler);
You can also load a model composed of Layer objects, including its topology and optionally weights by below options also please refer to tf.loadLayersModel for examples :
- Load a model from an HTTP server.
- Save model's topology and weights to browser local storage; then load it back.
- Saving model's topology and weights to browser IndexedDB; then load it back.
- Load a model from user-selected files from HTML file input elements.
If issue still persists please let us know with error log for further investigation.
Thank you for your cooperation and patience.
from tfjs.
Hi, @ZhongxuYang
Thank you for bringing this issue to our attention and as far I know, you can download model from kaggle here is link and please make sure select only Model Variations as TensorFlow.js option and download whichever model you want to use and once model got downloaded then please try to load the model with the help of below code snippet and it should work
const tf = require('@tensorflow/tfjs-node'); const modelPath = '/path/to/your/model.json'; const handler = tf.io.fileSystem(modelPath); const model = await tf.loadLayersModel(handler);
You can also load a model composed of Layer objects, including its topology and optionally weights by below options also please refer to tf.loadLayersModel for examples :
- Load a model from an HTTP server.
- Save model's topology and weights to browser local storage; then load it back.
- Saving model's topology and weights to browser IndexedDB; then load it back.
- Load a model from user-selected files from HTML file input elements.
If issue still persists please let us know with error log for further investigation.
Thank you for your cooperation and patience.
Thank you for your patient reply!
I have followed your tips to fulfill my needs. Proceed as follows:
- download model from kaggle here is link
- Pass the
detectorConfig
argument to theposeDetection.createDetector
function call.
const loadHandpose = async () => {
const detectorConfig: MoveNetModelConfig = {
modelUrl: '/your/public/path',
}
detector = await poseDetection.createDetector(model, detectorConfig)
startDetect()
}
from tfjs.
Are you satisfied with the resolution of your issue?
Yes
No
from tfjs.
Related Issues (20)
- Tensor shape mismatch during execution in the browser HOT 5
- Unsupported for BFloat16 in CPU environment in the browser HOT 4
- Operator data type mismatch HOT 4
- Different Model Outputs on Android vs. iOS with tfjs HOT 6
- KHR_parallel_shader_compile to speed up WebGL Backend
- fresh react native install (18.2.0 / 0.74.3) and tfjs 4.20 issue HOT 2
- DataMove HOT 5
- Error: The implicit shape can't be a fractional number. HOT 6
- [Codelab]: Making Predictions from 2D Data HOT 4
- TypeError: undefined is not an object (evaluating 'env().platform.encode')
- Exception: Error dumping weights, duplicate weight name weight HOT 2
- [Codelab]: Making Predictions from 2D Data Typo HOT 3
- New Community Project: T-Rex Game with Hand Motion Control using TensorFlow.js
- Error Server HOT 7
- hi, I am using google collab to convert my .h5 model to temsorflowjs. This is the error that I get: HOT 7
- Tensorflowjs converter not work using google collab HOT 5
- Convergence of Actor critic algorthim HOT 4
- Converted Model Using TensorFlow.JS Converter Not Working HOT 7
- Clarification regarding the latest mediapipe facemesh model for tfjs HOT 3
- FP16 inference support in WebGPU
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from tfjs.