gretel-synthetics
AI-basketball-analysis
gretel-synthetics | AI-basketball-analysis | |
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4 | 12 | |
535 | 923 | |
3.2% | - | |
7.2 | 0.0 | |
5 days ago | about 1 year ago | |
Python | Python | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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gretel-synthetics
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Ask HN: If we train an LLM with “data” instead of “language” tokens
Hey there! Co-founder of Gretel.ai here, and I think I can provide some insights on this topic.
Firstly, the concept you're hinting at is not purely traditional ML. In traditional machine learning, we often prioritize feature extraction and engineering specific to a given problem space before training.
What you're describing and what we've been working on at Gretel.ai, is leveraging the power of models like Large Language Models (LLMs) to understand and extrapolate from vast amounts of diverse data without the need for time-consuming feature engineering. Here's a link to our open-source library https://github.com/gretelai/gretel-synthetics for synthetic data generation (currently supporting GAN and RNN-based language models), and also our recent announcement around a Tabular LLM we're training to help people build with data https://gretel.ai/tabular-llm
A few areas where we've found tabular or Large Data Models to be really useful are:
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Libraries for synthetic data?
you can try QuantGAN: https://github.com/PakAndrey/QuantGANforRisk also try DoppelGANger https://github.com/gretelai/gretel-synthetics/tree/master/src/gretel_synthetics/timeseries_dgan
- Which open source tool for generating synthetic data sets?
- Gretel-synthetics: open-source library to create synthetic datasets
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.
https://github.com/chonyy/AI-basketball-analysis
- Show HN: AI Basketball Analysis in Realtime
- Show HN: AI Basketball Visualization
What are some alternatives?
Copulas - A library to model multivariate data using copulas.
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
gretel-python-client - The Gretel Python Client allows you to interact with the Gretel REST API.
openpifpaf - Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.
rex-gym - OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
go-live - 🗂️ go-live is an ultra-light server utility that serves files, HTML or anything else, over HTTP.
adversarial-robustness-toolbox - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
veems - An open-source platform for online video.
CTGAN - Conditional GAN for generating synthetic tabular data.
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
RobustVideoMatting - Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data