semvec/pypi-packages huggingface dataset:
eyelogic-sdk 1.2.0
Python wrapper for the EyeLogic eye tracking API
Requires Python: >=3.6

# Python Binding for EyeLogic Eye Tracking Devices

This is the python wrapper for the EyeLogic eye tracking API. It offers the possibility to connect you with your device from any custom application.

## Download and install

The EyeLogic python SDK is available via the Python Package Index (PyPI), and can be installed through pip.
`pip install eyelogic-sdk`

You can also download the EyeLogic SDK directly from the [eyelogic homepage](https://www.eyelogicsolutions.com/). The SDK contains also bindings to other languages as well as a user manual and API description.

## Usage

In your python script, import the eyelogic SDK:

```
from eyelogic.ELApi import *
```

In the `__main__` section, the application implements its control flow. It consists of the following code lines:
```
api = ELApi("Demo Client")
```

This constructs a new instance of the ELApi class. The instanciation will automatically "initialize" the library. Hence, it will also be automatically be "deinitialized" whenever the api object gets out of scope, e.g. at the end of the program.

```
resultConnect = api.connect()
```
Connects to the EyeLogic server. Check for the return value in order to find out whether the connection was established successfully.

```
resultTracking = api.requestTracking(0)
```
Starts the tracking of the device. The parameter 0 specifies the frame-rate mode. If your device is capable of multiple frame-rate modes (60Hz, 120Hz, 250Hz), you can also enter a different number. The list of available frame-rates is given to the callback onDeviceConnected( ). Usually, the frame-rate mode 0 is the default (the highest available speed mode of your system).

```
resultCalibrate = api.calibrate(0)
```
Performs a calibration. This method blocks until the calibration was performed (or aborted). The parameter 0 denotes the type of calibration.

At the end of your recording, close the connection:
```
api.disconnect()
```
ai-kissing 1767774.217.43
High-quality integration for https://supermaker.ai/video/ai-kissing/
Requires Python: >=3.6

# ai-kissing

A Python library providing automated tools to explore and integrate with ai-kissing capabilities, designed to interact with the services offered by https://supermaker.ai/video/ai-kissing/. This package simplifies accessing and utilizing ai-driven kissing simulation and analysis.

## Installation

To install the `ai-kissing` package, use pip:
bash
pip install ai-kissing

## Basic Usage

Here are a few examples demonstrating how to use the `ai-kissing` library:

**1. Generating a Kissing Probability Score:**

This example demonstrates how to calculate a probability score based on provided facial images.
python
from ai_kissing import AIKissing

ai_kiss = AIKissing()

image1_path = "path/to/image1.jpg"
image2_path = "path/to/image2.jpg"

try:
    probability = ai_kiss.get_kissing_probability(image1_path, image2_path)
    print(f"Kissing Probability: {probability}")
except Exception as e:
    print(f"Error: {e}")

**2. Simulating a Kissing Scenario (Text-Based):**

This example shows how to generate a text-based simulation of a kissing scenario.
python
from ai_kissing import AIKissing

ai_kiss = AIKissing()

try:
    scenario = ai_kiss.generate_kissing_scenario(description="A romantic sunset kiss on the beach.")
    print(f"Generated Scenario: {scenario}")
except Exception as e:
    print(f"Error: {e}")

**3. Analyzing an Existing Video for Kissing Moments:**

This example outlines how to identify potential kissing moments within a video file.
python
from ai_kissing import AIKissing

ai_kiss = AIKissing()

video_path = "path/to/video.mp4"

try:
    kissing_moments = ai_kiss.analyze_video(video_path)
    print(f"Kissing Moments: {kissing_moments}") # Returns timestamps or frame numbers
except Exception as e:
    print(f"Error: {e}")

**4.  Generating a Kissing Themed Poem:**

This example uses the AI to generate a poem related to kissing.
python
from ai_kissing import AIKissing

ai_kiss = AIKissing()

try:
    poem = ai_kiss.generate_kissing_poem(theme="first love")
    print(f"Kissing Poem: {poem}")
except Exception as e:
    print(f"Error: {e}")

## Features

*   **Kissing Probability Assessment:**  Calculate the likelihood of a kissing scenario based on facial image analysis.
*   **Kissing Scenario Generation:** Create text-based kissing scenarios based on descriptive prompts.
*   **Video Analysis for Kissing Moments:** Identify and timestamp potential kissing moments within video footage.
*   **Kissing Themed Content Generation:** Generate poems and other content related to kissing.
*   **Easy Integration:** Simple API for seamless integration with other applications.
*   **Error Handling:** Robust error handling to provide informative messages in case of issues.

## License

MIT License

This project is a gateway to the ai-kissing ecosystem. For advanced features and full capabilities, please visit: https://supermaker.ai/video/ai-kissing/