shitty_gaze_mouse_controller
adversarial-robustness-toolbox
| shitty_gaze_mouse_controller | adversarial-robustness-toolbox | |
|---|---|---|
| 3 | 8 | |
| 22 | 4,523 | |
| - | 2.6% | |
| 5.0 | 9.6 | |
| 6 months ago | 9 days ago | |
| Python | Python | |
| MIT License | MIT License |
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shitty_gaze_mouse_controller
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RAM hacking to port my eye tracker to bloatscript
original project: https://github.com/SubhranshuSharma/shitty_gaze_mouse_controller
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Show HN: RAM hacking to port my eye tracker to bloatscript
So decided to use cheat engine to find a pointer chain that consistently resolves to ram address of coordinates of an html text element that js moves based on inference results.
original project: https://github.com/SubhranshuSharma/shitty_gaze_mouse_contro...
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I'm a genius https://github.com/SubhranshuSharma/shitty_gaze_mouse_cotroller
Notice the cursor goes left when eye goes left, right for right, at the camera for up, down for down, left eyebrow up for enable/disable, left eye blink for double click QUICK START- And before anything the main.py file takes photos of you, run main.py and raise your left eyebrow,then make your left eye look up then down then left then right then close our eye everytime u have to press s to save image anything else to retake photo https://github.com/SubhranshuSharma/shitty_gaze_mouse_cotroller
adversarial-robustness-toolbox
- [D] Couldn't devs of major GPTs have added an invisible but detectable watermark in the models?
- [D] ML Researchers/Engineers in Industry: Why don't companies use open source models more often?
- [D]: How safe is it to just use a strangers Model?
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[D] Does anyone care about adversarial attacks anymore?
Check out this project https://github.com/Trusted-AI/adversarial-robustness-toolbox
- adversarial-robustness-toolbox: Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
- Library for Machine Learning Security Evasion, Poisoning, Extraction, Inference
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Introduction to Adversarial Machine Learning
Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference.
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[D] Testing a model's robustness to adversarial attacks
Depending on what attacks you want I've found both https://github.com/cleverhans-lab/cleverhans and https://github.com/Trusted-AI/adversarial-robustness-toolbox to be useful.
What are some alternatives?
shitty_gaze_mouse_contro
DeepRobust - A pytorch adversarial library for attack and defense methods on images and graphs
autoscraper - A Smart, Automatic, Fast and Lightweight Web Scraper for Python
auto-attack - Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"
pytorch-lightning - Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
TextAttack - TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
alpha-zero-boosted - A "build to learn" Alpha Zero implementation using Gradient Boosted Decision Trees (LightGBM)
m2cgen - Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
waf-bypass - Check your WAF before an attacker does
Differential-Privacy-Guide - Differential Privacy Guide
gretel-synthetics - Synthetic data generators for structured and unstructured text, featuring differentially private learning.
unrpa - A program to extract files from the RPA archive format.