BlenderProc
com.unity.perception
| BlenderProc | com.unity.perception | |
|---|---|---|
| 15 | 8 | |
| 2,554 | 872 | |
| 2.3% | 1.1% | |
| 8.3 | 0.0 | |
| 18 days ago | 11 months ago | |
| Python | C# | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
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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.
com.unity.perception
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Synthetic image Generation
Unity
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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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Help with Yolov4 Training and Synthetic Data
I see that you are already selected Unity for your AR app development, so you can go ahead and generate your data in Unity as well. They have an open source package to do that. Repo has tutorials to get you started and perception team is responsive to issues and questions.
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Unity provides People Generator & Home Interior Generator for Computer Vision tasks!
Check the Unity Perception Package here.
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How to generate images and labels using unity (or other game engine) to train YOLO5 object detection model? (Synthetic Data generation using unity for neural network learning). Are there any existing solutions? Or something similar
Hey, you can use Unity’s official Perception package. They have tutorials in the repo, but if you need more there are couple of tutorials on YT. If you don’t mind, what kind of images are you going to generate? I am developing a synthetic data generation tool for Unity, may I ask you couple of questions?
- Are there any tools to generate images and labels from 3d models/games?
- [D] Use of (machine learning + Game engines) for automatic 2D/3D content creation
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How to get started with synthetic data generation?
Using Unity: https://github.com/Unity-Technologies/com.unity.perception
What are some alternatives?
zpy - Synthetic data for computer vision. An open source toolkit using Blender and Python.
Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment - This project is part of the CS course 'Systems Engineering Meets Life Sciences I' at Goethe University Frankfurt. In this Computer Vision project, we present our first attempt at tackling the problem of traffic sign recognition using a systems engineering approach.
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
PeopleSansPeople - Unity's privacy-preserving human-centric synthetic data generator
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
kubric - A data generation pipeline for creating semi-realistic synthetic multi-object videos with rich annotations such as instance segmentation masks, depth maps, and optical flow.
agi2nerf - Simple tool for converting Agisoft XML files to NERF JSON files for https://github.com/NVlabs/instant-ngp
EasySynth - Unreal Engine plugin for easy creation of synthetic image datasets
segmentation_models - Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data
SingleViewReconstruction - Official Code: 3D Scene Reconstruction from a Single Viewport
unrealcv - UnrealCV: Connecting Computer Vision to Unreal Engine