anylabeling
MobileSAM
| anylabeling | MobileSAM | |
|---|---|---|
| 6 | 4 | |
| 1,895 | 4,345 | |
| - | - | |
| 6.0 | 8.9 | |
| 18 days ago | 4 months ago | |
| Python | Jupyter Notebook | |
| GNU General Public License v3.0 only | Apache License 2.0 |
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anylabeling
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AnyLabeling Auto-labeling with MobileSAM - the newest and fastest variant of Segment Anything
Check out AnyLabeling v0.3.2 today: https://github.com/vietanhdev/anylabeling/releases/tag/v0.3.2.
- AnyLabeling - Image Labeling tool with Auto Labeling from Segment Anything + YOLOs
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labelme VS anylabeling - a user suggested alternative
2 projects | 15 Apr 2023
AnyLabeling is a desktop app for image data labeling. It is a fork of LabelMe with upgraded UI and AI-assisted labeling with Segment Anything and YOLO models.
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labelImg VS anylabeling - a user suggested alternative
2 projects | 15 Apr 2023
AnyLabeling is a desktop app for image data labeling. It is a fork of LabelMe with upgraded UI and AI-assisted labeling with Segment Anything and YOLO models.
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AnyLabeling v0.2.2 now supported all Segment Anything models (ViT-B, ViT-L, ViT-H) + YOLOv5 + YOLOv8 for auto labeling
We also fixed some bugs from the last release and improved model performance. Check out at: https://github.com/vietanhdev/anylabeling We will love to hear your feedback to improve this program. Discussion at: https://github.com/vietanhdev/anylabeling/discussions/30
- Segment Anything Demo by Meta AI
MobileSAM
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EfficientSAM
https://github.com/ChaoningZhang/MobileSAM was the previous attempt at distilling the large image encoder used by SAM.
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AnyLabeling Auto-labeling with MobileSAM - the newest and fastest variant of Segment Anything
MobileSAM repo: https://github.com/ChaoningZhang/MobileSAM.
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Faster Segment Anything: Towards Lightweight SAM for Mobile Applications
Highlight: The training of MobileSAM can be completed on a single GPU within less than one day. MobileSAM is 60+ times smaller yet performs on par with the original SAM. For inference speed, Compared with the concurrent FastSAM, our MobileSAM with a superior performance is 7 times smaller and 4 times faster, making it more suitable for mobile applications. The code for MobileSAM project is provided at https://github.com/ChaoningZhang/MobileSAM.
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Fast Segment Anything (40ms/image)
lmao you called it FasterSAM
What are some alternatives?
autodistill - Images to inference with no labeling (use foundation models to train supervised models).
FastSAM - Fast Segment Anything
labelme - Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
sd-webui-inpaint-anything - Inpaint Anything extension performs stable diffusion inpainting on a browser UI using masks from Segment Anything.
segment-anything - The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
EfficientSAM - EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
labelImg - LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.
DIS - This is the repo for our new project Highly Accurate Dichotomous Image Segmentation
segment-anything-video - MetaSeg: Packaged version of the Segment Anything repository
SAMtext
ClashRoyaleBuildABot - A platform for creating bots to play Clash Royale
yolov8-face - yolov8 face detection with landmark