rd-blender-docker
BlenderProc
rd-blender-docker | BlenderProc | |
---|---|---|
2 | 15 | |
409 | 2,560 | |
0.0% | 2.5% | |
0.0 | 8.3 | |
over 1 year ago | 29 days ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 only |
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rd-blender-docker
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Does anyone know where the project setting is to disable blend file import? I'm compiling in a Docker instance online, so I won't be connecting Blender for the time being. Searching "blender" in the project settings doesn't bring up anything, but the warning implies that there is a setting for this.
I see you solved the issue but you can add blender to docker.
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Watchtower – Blender Studio
I'm so curious, what does the NYT use Blender for?
The repo doesn't have much context: https://github.com/nytimes/rd-blender-docker
BlenderProc
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Synthetic image Generation
Blender with add-ons (Kubric, BlenderProc)
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dataset collection for transfer learning
If you are interested, there are open source solutions on top of Unity, Blender, Unreal. You can generate yourself the data you described easier than it looks (the amount of options and settings can be intimidating with these tools).
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Are there any tools to generate images and labels from 3d models/games?
Blender addons like https://github.com/google-research/kubric and https://github.com/DLR-RM/BlenderProc
- How to get started with synthetic data generation?
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Course/Learning Material recommendations for getting started with Synthetic Data Generation for Computer Vision Models
I have been going through some papers and reviewing existing methods and I've come across stuff like UnrealCV (https://unrealcv.org/) and blenderproc (https://github.com/DLR-RM/BlenderProc).
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Searching for MIT CSAIL's IKEA dataset
I'm trying to use BlenderProc to automatically generate training data for object recognition.
- [P] BlenderProc2: Photorealistic Rendering of Procedurally Generated Scenes
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[D] What's the best method to generate synthetic data for an image with text? Small dataset
Check this out https://github.com/DLR-RM/BlenderProc. I haven't used it extensively, but it seems to decent for generating synthetic image data.
- Apple’s Machine Learning Team Introduces ‘Hypersim’: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding
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Using Blender for Computer Vision
That looks really interesting, have you seen BlenderProc: https://github.com/DLR-RM/BlenderProc it looks really similar just that BlenderProc already supports a vast variety of datasets and is fully documented.
What are some alternatives?
zoomrec - Record Zoom meetings automatically in headless docker container with Python and FFmpeg
zpy - Synthetic data for computer vision. An open source toolkit using Blender and Python.
armory - 3D Engine with Blender Integration
albumentations - Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
BlenderUSDHydraAddon - This add-on allows you to assemble and compose USD data with Blender data and render it all using various renderers via Hydra.
com.unity.perception - Perception toolkit for sim2real training and validation in Unity
Bforartists - Bforartists is a fork of the popular 3D software Blender, with the goal to improve the UI.
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
RadeonProRenderBlenderAddon - This hardware-agnostic rendering plug-in for Blender uses accurate ray-tracing technology to produce images and animations of your scenes, and provides real-time interactive rendering and continuous adjustment of effects.
agi2nerf - Simple tool for converting Agisoft XML files to NERF JSON files for https://github.com/NVlabs/instant-ngp
segmentation_models - Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
SingleViewReconstruction - Official Code: 3D Scene Reconstruction from a Single Viewport