Deep-Learning-Push-Up-Counter
labml
| Deep-Learning-Push-Up-Counter | labml | |
|---|---|---|
| 1 | 23 | |
| 26 | 1,867 | |
| - | 2.1% | |
| 1.8 | 9.7 | |
| almost 4 years ago | 6 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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.
Deep-Learning-Push-Up-Counter
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Counting repetitions in a video
Hi ! I am currently working on a project which involves the recognition of tennis strokes in videos. I have already implemented the detection part using a pre-trained OpenPose model to find the body keypoints and an LSTM for the classification task. Now I am having some trouble counting those movements. I have seen various approaches, but I would like something lightweight, somehow related to this specific task. Here is a project which uses optical flows to detect patterns in the movements, but a tennis stroke is a more complex action and I don't know how to label the frames (swing, not swing maybe). Another solution would be to use the already computed keypoints to compute some angles, but I didn't find something related to tennis. Thank you!
labml
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Creating stickers using SD with img2img
Used the PromptArt app by labml.ai to generate a sticker of an image I took from my iPhone. The results are amazing.
- [D] Why doesn’t your team use an experiment tracking tool?
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Probe PyTorch models
💻 Github
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[P] Probe PyTorch models
🧑🏫 Demo that extracts attention maps of BERT
- Show HN: Probe PyTorch Models
- [D] How do you guys tune hyperparameters, when a single training run takes a long time (days to weeks)?
- Machine Learning Best Practices
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[D] Machine Learning Best Practices
from github
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[P] Annotated deep learning paper implementations
labmlai/labml is a set of tools (tracking experiments, configurations, a bunch of helpers) we coded to ease our ML work (which later improved and open sourced). So we use it in all our projects because it makes things easier for us.
- React's UI State Model vs. Vanilla JavaScript
What are some alternatives?
SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data
nn - 🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
DenseDepth - High Quality Monocular Depth Estimation via Transfer Learning
guildai - Experiment tracking, ML developer tools
Machine_Learning_and_Deep_Learning_models - Repository containing models based on ideas of Machine learning and Deep learning
Practical_RL - A course in reinforcement learning in the wild
Face-Mask-Detection - Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras
tensorflow-onnx - Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
YPDL-Build-a-movie-recommendation-engine-with-TensorFlow - In this tutorial, we are going to build a Restricted Boltzmann Machine using TensorFlow that will give us recommendations based on movies that have been watched already. The datasets we are going to use are acquired from GroupLens and contains movies, users, and movie ratings by these users.
MIRNet-TFJS - TensorFlow JS models for MIRNet for low-light💡 image enhancement
Lottery_Ticket_Hypothesis-TensorFlow_2 - Implementing "The Lottery Ticket Hypothesis" paper by "Jonathan Frankle, Michael Carbin"
spock - spock is a framework that helps manage complex parameter configurations during research and development of Python applications