MimicX 0.1.9

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

MIMICX AI Library 📚

Build Modular, Asynchronous, and Composable AI Pipelines for Generative AI.

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.

Face Recognition Sample

import os
from mimicx import MimicVision

# Get the current directory of this script (or notebook)
folder_path = os.path.dirname(__file__)

if __name__ == "__main__":
    # Initialize the MimicVision client
    client = MimicVision()

    # Load the face recognition model
    client.load('face_recognition')

    # Define image paths
    img_path_1 = os.path.join(folder_path, "image1.png")
    img_path_2 = os.path.join(folder_path, "image2.png")

    # Extract face features from both images
    features1 = client.extract_face_feature(img_path_1)
    features2 = client.extract_face_feature(img_path_2)

    # Compare the two sets of face features
    result = client.compare_features_faces(features1, features2)

    # Print the similarity score or the error message
    if isinstance(result, (float, int)):
        print(f"Face similarity: {result:.2f}")
    else:
        print(result)

Iris Recognition Sample

import os
from mimicx import MimicVision

# Get the current directory of this script
folder_path = os.path.dirname(__file__)

if __name__ == "__main__":
    # Initialize the MimicVision client
    client = MimicVision()

    # Load the iris recognition model
    client.load('iris_recognition')

    # Define image paths
    img_path_1 = os.path.join(folder_path, "image1.png")
    img_path_2 = os.path.join(folder_path, "image2.png")

    # Extract iris features
    features1 = client.extract_iris_feature(img_path_1)
    features2 = client.extract_iris_feature(img_path_2)

    # Compare iris features
    result = client.compare_features_iris(features1, features2)

    if isinstance(result, (float, int)):
        print(f"Iris similarity: {result:.2f}")
    else:
        print(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.