gl_cadscene_rendertechniques
onnx-tensorrt
| gl_cadscene_rendertechniques | onnx-tensorrt | |
|---|---|---|
| 1 | 4 | |
| 147 | 2,766 | |
| 0.0% | 1.4% | |
| 3.1 | 5.3 | |
| 4 months ago | 4 days ago | |
| C++ | C++ | |
| Apache License 2.0 | Apache License 2.0 |
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gl_cadscene_rendertechniques
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Has anyone used Intel's Masked Occlusion Culling library?
And this, for some profiling results: https://github.com/nvpro-samples/gl_cadscene_rendertechniques
onnx-tensorrt
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Introducing Cellulose - an ONNX model visualizer with hardware runtime support annotations
[1] - We use onnx-tensorrt for this TensorRT compatibility checks.
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[P] [D]How to get TensorFlow model to run on Jetson Nano?
Conversion was done from Keras Tensorflow using to ONNX https://github.com/onnx/keras-onnx followed by ONNX to TensorRT using https://github.com/onnx/onnx-tensorrt The Python code used for inference using TensorRT can be found at https://github.com/jonnor/modeld/blob/tensorrt/tensorrtutils.py
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New to this: could I use Nvidia Nano + lobe?
Hi! You can run the models trained in Lobe on the Jetson Nano, either through TensorFlow (https://docs.nvidia.com/deeplearning/frameworks/install-tf-jetson-platform/index.html), ONNX runtime (https://elinux.org/Jetson_Zoo#ONNX_Runtime), or running ONNX on TensorRT (https://github.com/onnx/onnx-tensorrt).
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How to install ONNX-TensorRT Python Backend on Jetpack 4.5
Hello, I would like to install https://github.com/onnx/onnx-tensorrt from a package because compiling is a lot of complicated. Is there any source for this package?
What are some alternatives?
gl_occlusion_culling - OpenGL sample for shader-based occlusion culling
onnxruntime - ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
obs-StreamFX - StreamFX is a plugin for OBS® Studio which adds many new effects, filters, sources, transitions and encoders! Be it 3D Transform, Blur, complex Masking, or even custom shaders, you'll find it all here.
TensorRT - NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
jetson-inference - Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
server - The Triton Inference Server provides an optimized cloud and edge inferencing solution.
deepC - vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers
keras-onnx - Convert tf.keras/Keras models to ONNX
modeld - Self driving car lane and path detection