bpycv
zpy
| bpycv | zpy | |
|---|---|---|
| 3 | 9 | |
| 455 | 288 | |
| - | 0.0% | |
| 4.6 | 0.0 | |
| about 2 months ago | over 2 years ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 only |
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bpycv
- Bpycv: Computer Vision and Deep Learning Utils for Blender
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Python code that takes pictures from different view points of a 3d model
Blender is capable of running in a headless mode. I ‘ve had the exact same use case nearly a thousand times. This library worked out well for my purposes https://github.com/DIYer22/bpycv
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[P] Synthetic Data for CV with Python and Blender
Can someone who knows a bit about this compare to, e.g., bpycv? Seems like they are doing very similar stuff
zpy
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Help finding a model that can identify small cubes
This is actually a great problem for synthetic data. You can make a synthetic dataset of colored cubes on different backgrounds using something like Unity or zpy (shameless plug). The synthetic data will be much larger and more varied than one you create & label by hand.
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Why isn't this technology used more for AI projects?
I'm sort of in the same boat. I just discovered this very interesting package called zpy that's meant to help automate turning synthetic conditions into training data. I have some experience with Python and am fairly new to Blender, but I could probably get as far as making a good segmented dataset.
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Why Blender Is the Best Software for the 3D Workflow
Thanks for getting this far! If you’re interested in 3D and what it can do for synthetic data, check out our open-source data development toolkit zpy. Everything you need to generate and iterate synthetic data for computer vision is available for free. Your feedback, commits, and feature requests are invaluable as we continue to build a more robust set of tools for generating synthetic data. In the meantime, if you need our support with a particularly tricky problem, please reach out.
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Discussion on Medium
I work at Zumo Labs, where we create synthetic data for computer vision using zpy (github.com/ZumoLabs/zpy).
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How to 3D Scan an Object for Synthetic Data
The easiest way to get started with zpy (available on GitHub) is to follow the steps outlined in this short video tutorial series.
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Use Python and Blender to Make More Dynamic Training Data
Tools that make synthetic data generation easy are fundamentally changing the way machine learning work is done. Iterating and improving the dataset over the course of a project is more important to project success than iterating the model architecture. That's why we are releasing zpy, an open source synthetic data toolkit. All developers should have the option of working with dynamic data rather than static data.
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[P] Synthetic Data for CV with Python and Blender
https://github.com/ZumoLabs/zpy We just released our open source synthetic data toolkit built on top of Blender. Our package makes it easy to design and generate synthetic data for computer vision projects. Let us know what you think and what features you want us to focus on next!
https://github.com/ZumoLabs/zpy We just released our open source synthetic data toolkit built on top of Blender. Our package makes it easy to design and generate synthetic data for computer vision projects. Let us know what you think and what features you want us to focus on next!
- Using Blender for Computer Vision
What are some alternatives?
labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.
BlenderProc - A procedural Blender pipeline for photorealistic training image generation
labelme - Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
retopoflow - A suite of retopology tools for Blender
sahi - Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
Meshroom - 3D Reconstruction Software
learning-topology-synthetic-data - Tensorflow implementation of Learning Topology from Synthetic Data for Unsupervised Depth Completion (RAL 2021 & ICRA 2021)
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
pyrender - Easy-to-use glTF 2.0-compliant OpenGL renderer for visualization of 3D scenes.
TextRecognitionDataGenerator - A synthetic data generator for text recognition
unsupervised-depth-completion-visual-inertial-odometry - Tensorflow and PyTorch implementation of Unsupervised Depth Completion from Visual Inertial Odometry (in RA-L January 2020 & ICRA 2020)
BlenderNeRF - Easy NeRF synthetic dataset creation within Blender