Yolo_mark
yolov7
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| Yolo_mark | yolov7 | |
|---|---|---|
| 6 | 33 | |
| 1,783 | 12,681 | |
| - | - | |
| 10.0 | 4.0 | |
| over 3 years ago | 7 days ago | |
| C++ | Jupyter Notebook | |
| The Unlicense | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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
yolov7
- FLaNK Stack Weekly 16 October 2023
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Train a ML model able to identify animal species
If you want something off-the-shelf, try YoloV7.
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A video based Latin dictionary: get what you see in Latin (beta) - What do you think?
The current dictionary is still in a beta state and has only been trained on 80 words (e.g. 'man', 'dog', 'car', 'keyboard', 'book', etc.; see list of words, see dataset). I used the object detection model Yolov7 (paper, all credits to them).
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[D] Extracting the class labels and bounding boxes for objects, from a YOLO7 model after converting to an ONNX model
(Please note, this is a re-post of my original question here, I think this subreddit might be more appropriate for asking this question)At work, we use Unity, we have a project that needs object detection and classification. We decided to use this YOLO7 model (for non-technical reasons, It had to be the exact same model as the company does have pre-trained weights for this exact model). However, Unity only supports ONNX so I exported the model as an ONNX model, using the code provided in the repo:
- Coding Question Help
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DL for the Web: Repository of Models
Github Projects offering pretrained weights and train / run scripts. Example
- [OC] Football Player 3D Pose Estimation using YOLOv7 and Matplotlib
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Finding a good Tiny Yolo to train in Python
The only project I found is this one that implements Yolov7
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Visualizing image augmentations from YOLOV7
I'm wondering if there's an efficient way to visualize the image augmentations from the Yolov7 hyperparameters list here
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Train YOLOv8 ObjectDetection on Custom Dataset Tutorial
yolov7: https://github.com/WongKinYiu/yolov7#performance
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.
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
py-motmetrics - :bar_chart: Benchmark multiple object trackers (MOT) in Python
edgetpu - Coral issue tracker (and legacy Edge TPU API source)
VoTT - Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.
edgetpu-yolo - Minimal-dependency Yolov5 export and inference demonstration for the Google Coral EdgeTPU
TensorRT-For-YOLO-Series - tensorrt for yolo series (YOLOv8, YOLOv7, YOLOv6, YOLOv5), nms plugin support
YOLOv4 - Port of YOLOv4 to C# + TensorFlow
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
darknet - Convolutional Neural Networks
deprecated-core - 🔮 Instill Core contains components for supporting Instill VDP and Instill Model
XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model