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Found 6 Skills
Three.js and React Three Fiber sub-skill - 3D scenes, shaders, postprocessing.
Addon screen-space post-processing for three.js using EffectComposer, Pass base class, RenderPass, and stock passes such as UnrealBloomPass, SSAOPass, SSRPass, BokehPass, OutlinePass, FXAAPass/SMAAPass, TAARenderPass, and ShaderPass; references the Shaders addon group for underlying shader modules; contrasts with core PostProcessing class used in node/WebGPU stacks (see threejs-node-tsl and threejs-renderers). Use when building composer chains—not for basic renderer tone mapping alone (threejs-renderers).
three.js node-based shading: Nodes API surface, NodeMaterial and MeshStandardNodeMaterial-style families, TSL (Three.js Shading Language) entry at TSL.html, WebGPURenderer pairing, and core PostProcessing (class) versus addon EffectComposer at a high level. Use when authoring shaders as graphs, using TSL builtins, compute-oriented nodes, or modern WebGPU pipelines; for classic MeshStandardMaterial, MeshPhysicalMaterial, and string-based ShaderMaterial GLSL use threejs-materials; for stock EffectComposer + Pass passes use threejs-postprocessing; for WebGLRenderer-only tuning without nodes use threejs-renderers.
Three.js 3D graphics library - scene setup, geometry, materials, lighting, textures, animation, loaders, shaders, postprocessing, interaction. Use when building 3D web experiences, creating WebGL visualizations, working with GLTF models, implementing custom shaders, or adding interactive 3D elements to web applications.
Complete toolkit for Huawei Ascend NPU model conversion and end-to-end inference adaptation. Workflow 1 auto-discovers input shapes and parameters from user source code. Workflow 2 exports PyTorch models to ONNX. Workflow 3 converts ONNX to .om via ATC with multi-CANN version support. Workflow 4 adapts the user's full inference pipeline (preprocessing + model + postprocessing) to run end-to-end on NPU. Workflow 5 verifies precision between ONNX and OM outputs. Workflow 6 generates a reproducible README. Supports any standard PyTorch/ONNX model. Use when converting, testing, or deploying models on Ascend AI processors.
Add or debug Three.js bloom, antialiasing, ambient occlusion, depth effects, and render-target composition.