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 Model

# Initialize load model
model = Model("mimicvision/face_recognition")

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

Sample: Iris Recognition

from mimicx import Model

# Initialize load model
model = Model("mimicvision/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-0.1.26.tar.gz (4.5 kB view details)

Uploaded Source

Built Distribution

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

mimicx-0.1.26-py2.py3-none-any.whl (4.7 kB view details)

Uploaded Python 2Python 3

File details

Details for the file mimicx-0.1.26.tar.gz.

File metadata

  • Download URL: mimicx-0.1.26.tar.gz
  • Upload date:
  • Size: 4.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.6

File hashes

Hashes for mimicx-0.1.26.tar.gz
Algorithm Hash digest
SHA256 20064174a0d7568804839a9cdaf232a91f7c715fc6780c0ce013a5a26ca0af69
MD5 3a0e8221df0ef3fef978a1457b720f5b
BLAKE2b-256 45dc6a7fd7e1b47fec0e40242a6372088b6481bc65c89f69e9b8c4d1b041c88b

See more details on using hashes here.

File details

Details for the file mimicx-0.1.26-py2.py3-none-any.whl.

File metadata

  • Download URL: mimicx-0.1.26-py2.py3-none-any.whl
  • Upload date:
  • Size: 4.7 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-0.1.26-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 236c648bf3cfbe27162ddd5042e6ddbda6e92f5425e0b7b54f632af68eba77bb
MD5 413761ab1e8e1da3c0df6caf6d81ed3f
BLAKE2b-256 8653a6cadd34028b446a1de6fd25793659a978578a0645a6f05d16985368aee4

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