pointnet2
BlenderProc
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| pointnet2 | BlenderProc | |
|---|---|---|
| 2 | 15 | |
| 2,875 | 2,544 | |
| - | 3.5% | |
| 0.0 | 8.3 | |
| over 1 year ago | 14 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 only |
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pointnet2
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Why does trained model fail on new data?
Is this how you trained the segmentation? https://github.com/charlesq34/pointnet2
- Are the New M1 Macbooks Any Good for Deep Learning? Let’s Find Out
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?
Pointnet_Pointnet2_pytorch - PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
zpy - Synthetic data for computer vision. An open source toolkit using Blender and Python.
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
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
dgcnn.pytorch - A PyTorch implementation of Dynamic Graph CNN for Learning on Point Clouds (DGCNN)
com.unity.perception - Perception toolkit for sim2real training and validation in Unity
ttach - Image Test Time Augmentation with PyTorch!
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
agi2nerf - Simple tool for converting Agisoft XML files to NERF JSON files for https://github.com/NVlabs/instant-ngp
RAFT
segmentation_models - Segmentation models with pretrained backbones. Keras and TensorFlow Keras.