Open Source JavaScript 3D Modeling Software

TensorSpace is a neural network 3D visualization framework built using TensorFlow.js, Three.js and Tween.js. TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser. From TensorSpace, it is intuitive to learn what the model structure is, how the model is trained and how the model predicts the results based on the intermediate information. After preprocessing the model, TensorSpace supports the visualization of pre-trained models from TensorFlow, Keras and TensorFlow.js. TensorSpace is a neural network 3D visualization framework designed for not only showing the basic model structure but also presenting the processes of internal feature abstractions, intermediate data manipulations and final inference generations. By applying TensorSpace API, it is more intuitive to visualize and understand any pre-trained models built by TensorFlow, Keras, TensorFlow.js, etc.

face3D chung is a small mesh editor with which you can create 3D obj model character avatar head objects with texture from a single photo of any man or woman for your games. Works by 3D & texture morphing .Uses freebasic apps gui_chung , loadobj3ds_chung and ancient openGL . Can run on a small netbook. .Added speaking avatars with moving lips using TTS_chung_dll and aiml_chung_dll aiml chatbot .Added online speaking avatar using HTML5 , javascript , jsc3d and custom elizabot like chatbot with eval() javascript function . Added talk3D_chung a small example using obj models created with face3D_chung . Added speak3D_chung_dll a dll to load and display face3D_chung talking avatars in openGL Added face3D libertybasic demo example of calldll in liberty basic . Can be used as mesh editor (adjust texture,scale parts) by load/save as model .

Run Keras models in the browser, with GPU support provided by WebGL 2. Models can be run in Node.js as well, but only in CPU mode. Because Keras abstracts away a number of frameworks as backends, the models can be trained in any backend, including TensorFlow, CNTK, etc. Check out the demos/ directory for real examples running Keras.js in VueJS. Library version compatibility, Keras 2.1.2.

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