Skip to main content

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")`

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

humanmovemouse-0.1.1.tar.gz (12.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

humanmovemouse-0.1.1-py3-none-any.whl (13.0 kB view details)

Uploaded Python 3

File details

Details for the file humanmovemouse-0.1.1.tar.gz.

File metadata

  • Download URL: humanmovemouse-0.1.1.tar.gz
  • Upload date:
  • Size: 12.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.9

File hashes

Hashes for humanmovemouse-0.1.1.tar.gz
Algorithm Hash digest
SHA256 423021c1d2c36a0073a6d708ef07a12bc25c603d77fefa4806aa218e61603e64
MD5 3c0e25662a82d2e2a3d9c014d8ebb3ec
BLAKE2b-256 954a100af97efc02afa5f7a70e5c208ac1d6fdea3e03198dff18fa63fc9ebd74

See more details on using hashes here.

File details

Details for the file humanmovemouse-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: humanmovemouse-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 13.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.9

File hashes

Hashes for humanmovemouse-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 3f4a63662939c292ef95896455f0b3cc1dd7e5fa5c5404472c9a630a2a9a5691
MD5 67575698fda8acdfb9238923f534f14e
BLAKE2b-256 a6bf229228e873c2eb6e3cc6645d79b85e176def40312e304494a1375943425d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page