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Human-like mouse automation using statistical models and minimum-jerk interpolation

Project description

HumanMoveMouse 🖱️

Python License

🎯 Human-like mouse automation using statistical models and minimum-jerk interpolation.


Overview

HumanMoveMouse is a human-like mouse automation tool built on over 300 real human mouse movement samples.
By extracting key statistical features from these trajectories and combining them with minimum-jerk interpolation,
the tool enables the generation of natural, smooth, and realistic cursor paths.

These paths closely mimic real human behavior and are ideal for automation tasks requiring authenticity,
such as UI testing, game botting, or user behavior simulation.


Installation

Install the required packages using pip:

pip install numpy pandas scipy scikit-learn pyautogui pygame

Core Functions & Examples

Basic Movement

Move the cursor smoothly between two points.

from human_mouse.human_mouse_controller import HumanMouseController 
controller = HumanMouseController(model_pkl="mouse_model.pkl") 
controller.move((100, 100), (800, 600)) # Move to coordinates 
controller.move_and_click((800, 600), (400, 400)) # Move and click

Parameter Tuning

Adjust trajectory smoothness and speed.

controller = HumanMouseController( 
    model_pkl="mouse_model.pkl", 
    num_points=200, 
    jitter_amplitude=0.2, 
    speed_factor=0.5, ) 

controller.move((300, 300), (900, 500))

Drag and Drop

controller.drag((500, 500), (700, 700))`

Training a Model

You can train your own model using real mouse data.
First, collect trajectory CSVs using:

csv_data_collecter/Mouse Trajectory Collecter.py

Then train a model with:

from human_mouse.human_mouse_stat_mj import train_mouse_model 
train_mouse_model("./csv_data", "mouse_model.pkl")`

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