ayolo
image-sorter2
| ayolo | image-sorter2 | |
|---|---|---|
| 1 | 1 | |
| 5 | 84 | |
| - | - | |
| 5.2 | 0.0 | |
| almost 3 years ago | 7 months ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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ayolo
image-sorter2
-
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.
What are some alternatives?
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
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.
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
labelCloud - A lightweight tool for labeling 3D bounding boxes in point clouds.
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]
awesome-data-labeling - A curated list of awesome data labeling tools