awesome-data-labeling
diffgram
| awesome-data-labeling | diffgram | |
|---|---|---|
| 7 | 9 | |
| 3,480 | 1,800 | |
| 1.6% | 0.9% | |
| 0.0 | 8.8 | |
| 7 months ago | 3 days ago | |
| Python | ||
| - | GNU General Public License v3.0 or later |
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awesome-data-labeling
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CVAT alternatives for video frame annotation
GitHub - heartexlabs/awesome-data-labeling: A curated list of awesome data labeling tools
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[P] Can anyone suggest free Image annotation tool for multi labelling?
Checkout this curated list on heartexlabs github. I used the list to find server-like annotation tools.
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Segmentation Maps
A Google search throws plenty of results for labelling tools: - https://github.com/heartexlabs/awesome-data-labeling - https://www.folio3.ai/blog/labelling-images-annotation-tool/ - https://neptune.ai/blog/data-labeling-software/amp
- How would you structure a dataset for both image counting and classification? And what would be the best approach for this task?
- Awesome-Data-Labeling
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How to get image dataset annotated? Any idea?
If you're looking for a tool or something, there are plenty out there. Of course, even with these tools, labeling 50k images is likely not feasible for an individual.
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[D] Suggestions for sentiment analysis tools
You can have a look at aws ground truth for this, or have a look at this https://github.com/heartexlabs/awesome-data-labeling
diffgram
- Open source tool scrapes git commit email addresses to send spam to.
- Open Source Training Data – Diffgram
- Open Source Data Annotation - Diffgram
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[D] Labelbox threatens to sue small open-source startup Diffgram
As a few examples of how much depth we have considered, here's a detailed comparison with sagemaker. Part of an integration with scale. Part of code for labelbox integration, datasaur (scroll to trusted by for our logo) etc. To the best of my knowledge I am trying to track every firm that is in this direct space.
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[P] 😃🎉 Open source AI/ML data annotation platform for free [Product Hunt]
(Direct repo link https://github.com/diffgram/diffgram)
- Open Source AI Data Annotation 2.0 (Source Code)
- Open Source AI Data Annotation 2.0
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[P] Diffgram - Open Annotation Platform
We list some benefits here but if I had to pick one thing, it's that it's a complete system. You can be up and running in 2 minutes on docker. And scale to "big tech co" level on multiple k8s clusters.
- Show HN: Open Core Diffgram (GitHub)
What are some alternatives?
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
SSL4MIS - Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
VoTT - Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.
cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]
dataqa - Labelling platform for text using weak supervision.
cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/opencv/cvat]
hover - :speedboat: Label data at scale. Fun and precision included.
labelbee-client - Out-of-the-box Annotation Toolbox
auto_annotate - Labeling is boring. Use this tool to speed up your next object detection project!
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