Skip to main content

Human-like AI for everyone — vision, text, voice, and more in one simple package.

Project description

MIMICX AI Library 📚

License PyPI version

Create Human-Like AI: Perception, Reasoning, and Interaction in One Library

Mimicx AI is a lightweight Python library for giving machines human-level perception and decision-making capabilities by enabling advanced perception, contextual reasoning, autonomous decision-making, and intuitive human-machine interaction.

At its core, Mimicx structures its capabilities into specialized domains — Vision, Text, Voice, Feel, Twin, Phy, Sense, and Mind — each targeting a unique dimension of machine perception, reasoning, and interaction.

Sample: Face Recognition

from mimicx import MimicVision

# Initialize client and load model
client = MimicVision()
client.load('face_recognition')

# Compare faces
result = client.compare_faces(image1_path, image2_path)
print(f"Face similarity: {result:.2f}")
       

Sample: Iris Recognition

from mimicx import MimicVision

# Initialize client and load model
client = MimicVision()
client.load('iris_recognition')

# Compare faces
result = client.compare_iris(image1_path, image2_path)
print(f"Iris similarity: {result}")

Notes

  • Ensure that the images exist in the same directory as this script.

  • The MimicX package must be installed and properly configured.

  • The load('face_recognition') call initializes the face recognition model.

✨ Key Features

  • MimicVision: processes and interprets visual data, enabling advanced image and video understanding.

  • MimicText: handles natural language processing and contextual text reasoning.

  • MimicVoice: works with audio signals for speech recognition, synthesis, and voice interaction.

  • MimicFeel: captures and interprets tactile and sensory data to simulate touch and emotion.

  • MimicTwin: creates and manages digital twins, bridging physical and virtual environments.

  • MimicPhy: interfaces with physical systems for autonomous control and robotics.

  • MimicSense: integrates multisensory data streams for comprehensive environmental awareness.

  • MimicMind: enables high-level cognitive functions including planning, decision-making, and adaptive learning.

📦 Installation

The GenAI Processors library requires Python 3.10+.

Install it with:

pip install mimicx

🤝 Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines on how to contribute to this project.

📜 License

This project is licensed under the MIT License, See the LICENSE file for details.

Mimicx Terms of Services

If you make use of Mimicx via the MimicX library, please ensure you review the Terms of Service.

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

mimicx-0.1.15.tar.gz (5.1 kB view details)

Uploaded Source

Built Distribution

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

mimicx-0.1.15-py2.py3-none-any.whl (5.4 kB view details)

Uploaded Python 2Python 3

File details

Details for the file mimicx-0.1.15.tar.gz.

File metadata

  • Download URL: mimicx-0.1.15.tar.gz
  • Upload date:
  • Size: 5.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.6

File hashes

Hashes for mimicx-0.1.15.tar.gz
Algorithm Hash digest
SHA256 3a1bd8047b288a790a08588cec4f3524c5857320b9bdc5fd9c47d709d941313c
MD5 9189b9b830a226f929e056f394b4b4f6
BLAKE2b-256 ef3b3a68778a9a07b47402f3463726c7548236fd2467a602145f65d87c49182a

See more details on using hashes here.

File details

Details for the file mimicx-0.1.15-py2.py3-none-any.whl.

File metadata

  • Download URL: mimicx-0.1.15-py2.py3-none-any.whl
  • Upload date:
  • Size: 5.4 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.6

File hashes

Hashes for mimicx-0.1.15-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 5752404253fa6d7145d2db37e6f5d6244a0b55cf063594e83811d55ad33b8723
MD5 8393dfa7556b85dd7a4c22aac15ed441
BLAKE2b-256 b1ac6b8972cd6f74bc2d919abe4908b9ac39714ec0267517588f45a07709210f

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