image-sorter2
awesome-data-labeling
| image-sorter2 | awesome-data-labeling | |
|---|---|---|
| 1 | 7 | |
| 84 | 3,465 | |
| - | 1.2% | |
| 0.0 | 0.0 | |
| 7 months ago | 7 months ago | |
| Python | ||
| Apache License 2.0 | - |
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image-sorter2
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How are custom (bounding box) object datasets collected in research/practice? Thinking about making an iOS app to help if this is tedious.
I first altered the image-sorter2 code to do multi-classes and save to CSV file instead of moving files to directories. I then implemented the YOLOv5 algorithm in the image viewing, so that it would predict where the people were in the image. I could then label where the people were by box number and label their activity. It ends up being pretty quick to label images this way.
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
What are some alternatives?
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.
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
labelCloud - A lightweight tool for labeling 3D bounding boxes in point clouds.
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.
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]
SSL4MIS - Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
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]
labelbee-client - Out-of-the-box Annotation Toolbox
VoTT - Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.
ScrivanoForLinux - Scrivano is a notetaking application for handwritten notes.
datalabel - datalabel is a UI-based data editing tool that makes it easy to create labeled text data in a dataframe. With datalabel, you can quickly and effortlessly edit your data without having to write any code. Its intuitive interface makes it ideal for both experienced data professionals and those new to data editing.