Yolo_mark
VoTT
| Yolo_mark | VoTT | |
|---|---|---|
| 6 | 8 | |
| 1,783 | 3,670 | |
| - | - | |
| 10.0 | 0.8 | |
| over 3 years ago | over 2 years ago | |
| C++ | TypeScript | |
| The Unlicense | MIT License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Yolo_mark
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Way to label yolov7 images fast
I've used Yolo_mark (https://github.com/AlexeyAB/Yolo_mark) with success when needing to label a few hundred thousand images. Its still a manual solution, but there are keyboard shortcuts for navigating between images and classes, and with some practice you can get through a ton of images quite quickly.
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Implementation of YOLO in python or C++?
What are you talking about? Darknet -- where YOLO started! -- is written in C and C++. Check the active repo: https://github.com/AlexeyAB/darknet
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I was excited about YOLOv7, so I built a sharable object detection application with VDP and Streamlit.
When YOLOv7 was out, I built a web app to test it against the classic YOLOv4 and shared it with my team, then deployed it online to share with the community.
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HOW to find MOTA and MOTP for MOT evaluation metrics?
Because I need to calculate MOTA and MOTP for the tracking metrics. please anyone with this concept help me as I am beginner to the computer vision. Incase if it helps I am working based on the github https://github.com/AlexeyAB/darknet
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How to improve a YoloV5 model after the first training?
My work heavily involves the use of the yolo algorithm such as optimising it for performance on mobile devices. Yolov5 is made by a private company that has been pushing sub bar models for a while. I've benchmarked their smallest models comparing them to Yolov4 tiny and the results were staggering, v4 being around 3-4 times faster. Yolov4 has way more resources for development, I highly suggest checking out this repo https://github.com/AlexeyAB/darknet
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[D] What are people using to organize large groups of people for data labelling?
YOLO Mark
VoTT
- Need help identifying a good open source data annotation tool
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Best Image Annotation Tools
VoTT is an image annotation tool from Microsoft that has several interesting features that differ from the other tools. The installation of this tool is very easy because you could just simply download the installer according to your OS from their Github page.
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Heads Up: apparently Firefox does NOT add quarantine flag to downloaded Apps anymore (all downloaded apps launch instantly, even if they are not notarized or signed)
Last app tested was this and it is safe to try, when downloaded with Safari, it shows the warnings and prevents the launch, when downloaded with Firefox it opens instantly, no warning. (I downloaded on Firefox first which launched instantly, then removed the app and tried with Safari and the warning appeared)
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[D] What are people using to organize large groups of people for data labelling?
VoTT
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(WIP) I trained Yolov5 on Diablo
I annotated 100 images which 70% was used for the training. I used 7 classes and annotated with VoTT then converted to Pytorch yolov5 from roboflow. I don't remember the mAp, sorry.
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Face Recognition
Labeling images: depending on the tool, you must label the images in PASCAL VOC format for TF or YOLO for Darknet. You can use programs like labelImg, VIA, VoTT (no longer maintain), among others.
- [D] Can anyone recommend a tool for sorting images into folders for image classification?
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I'm currently working on an image labeling tool for machine learning: looking for advice!
Are you doing this as an exercise or is it that you need an image annotation tool? There are some really good open source ones, such as VoTT. Maybe you can start from there.
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.
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]
py-motmetrics - :bar_chart: Benchmark multiple object trackers (MOT) in Python
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
TensorRT-For-YOLO-Series - tensorrt for yolo series (YOLOv8, YOLOv7, YOLOv6, YOLOv5), nms plugin support
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.
deprecated-core - 🔮 Instill Core contains components for supporting Instill VDP and Instill Model
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
yolov7 - Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
make-sense - Free to use online tool for labelling photos. https://makesense.ai