yolov3
AI-basketball-analysis
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yolov3 | AI-basketball-analysis | |
---|---|---|
4 | 12 | |
9,981 | 922 | |
0.9% | - | |
8.5 | 0.0 | |
5 days ago | 12 months ago | |
Python | Python | |
GNU Affero General Public License v3.0 | GNU General Public License v3.0 or later |
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.
yolov3
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[Tutorial] "Fine Tuning" Stable Diffusion using only 5 Images Using Textual Inversion.
Hey. I only have experience using the official repository, and only use Linux. Could you try the solutions here and see if it helps? https://github.com/ultralytics/yolov3/issues/1643
- How to train a model for object detection in Golang?
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Engineering Student AI model turns sign language to English in real time.
YOLOv3: https://github.com/ultralytics/yolov3
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I don't know how to train a YOLO v3 model with some custom data that is labeled in an unusual form (XML files)
Each image has an XML file associated with it. The XML files have the corresponding labels and bounding boxes, so I can write a script to convert them into this form, and follow this tutorial on training custom data.
AI-basketball-analysis
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[P] Basketball Shots Detection and Shooting Pose Analysis (Open Source)
Source code: https://github.com/chonyy/AI-basketball-analysis
- Show HN: Visualizing Basketball Trajectory and Analyzing Shooting Pose
- Automatically Overlaying Baseball Pitch Motion and Trajectory in Realtime (Open Source)
- Show HN: AI Basketball Analysis Web App and API
- Show HN: Visualize and Analyze Basketball Shots and Shooting Pose with ML
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Ask HN: Show me your Half Baked project
I built an app to visualize and analyze basketball shots and shooting pose with machine learning.
https://github.com/chonyy/AI-basketball-analysis
The result is pretty nice. However, the only problem is the slow inference speed. I'm now refactoring the project structure and changing the model to a much faster YOLO model.
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Show HN: Automatic Baseball Pitching Motion and Trajectory Overlay in Realtime
Thanks for asking! This is not a noob question.
I would say that the similar workflow could be applied to any ball-related sports. The object detection and the tracking algorithm is basically the same. Then, you could add any sport-specific feature!
For example, I have used a similar method to build AI Basketball Analysis.
- Show HN: AI Basketball Analysis in Realtime
- Show HN: AI Basketball Visualization
What are some alternatives?
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
yolov7 - Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
openpifpaf - Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.
yolov7_d2 - 🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
go-live - 🗂️ go-live is an ultra-light server utility that serves files, HTML or anything else, over HTTP.
HASS-Deepstack-object - Home Assistant custom component for using Deepstack object detection
veems - An open-source platform for online video.
yolov5-crowdhuman - Head and Person detection using yolov5. Detection from crowd.
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
tensorflow-yolo-v3 - Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)
SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data