semi-supervised-segmentation-on-graphs
auto_annotate
| semi-supervised-segmentation-on-graphs | auto_annotate | |
|---|---|---|
| 3 | 2 | |
| 5 | 159 | |
| - | 0.0% | |
| 0.0 | 4.2 | |
| over 3 years ago | about 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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semi-supervised-segmentation-on-graphs
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[P] Semi Supervised Segmentation on Graphs using Eikonal Equation with PyOpenCl backend.
I would like to share this project with you. https://github.com/aGIToz/semi-supervised-segmentation-on-graphs . It does segmentation on graphs. Its application on images and pointclouds.
- semi supervised segmentation on images using eikonal equation with pyopencl backend.
- Show HN: Semi-Supervised-Segmentation-on-Graphs
auto_annotate
- Labeling is boring. Use this tool to speed up your next object detection project!
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Auto Annotation Tool for TensorFlow Object Detection
Are you tired to label your images by hand to work with object detection? Have hundreds or thousands of images to label? Then this project will make your life easier, just create some annotations and let the machine do the rest for you!
https://github.com/AlvaroCavalcante/auto_annotate
What are some alternatives?
Pseudo-Labelling - Pseudo Labelling on MNIST dataset in Tensorflow 2.x
synthetic-dataset-object-detection - How to Create Synthetic Dataset for Computer Vision (Object Detection) (Article on Medium)
Graph_Signal_Processing - Signal processing on graphs using torch_geometric.
diffgram - The AI Datastore for Schemas, BLOBs, and Predictions. Use with your apps or integrate built-in Human Supervision, Data Workflow, and UI Catalog to get the most value out of your AI Data.
ETCI-2021-Competition-on-Flood-Detection - Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
inscriptor - Blip 2 Captioning, Mass Captioning, Question Answering, and other tools.