ai-pose-generator-2 1766998.955.554
High-quality integration for https://supermaker.ai/image/ai-pose-generator/
Requires Python: >=3.6

# ai-pose-generator-2

An automated library designed to demonstrate the capabilities of the ai-pose-generator-2 model and facilitate integration with the SuperMaker AI pose generation platform. This package provides a streamlined interface for generating and manipulating AI-powered poses directly within your Python environment.

## Installation

You can install the `ai-pose-generator-2` package using pip:
bash
pip install ai-pose-generator-2

## Basic Usage

Here are a few examples showcasing how to use the `ai-pose-generator-2` library:

**1. Generating a Basic Pose:**
python
from ai_pose_generator_2 import PoseGenerator

generator = PoseGenerator()
pose = generator.generate_pose()  # Generates a default pose
print(pose) # Returns a dictionary representing the pose

This example demonstrates the simplest way to generate a pose using the default settings. The `generate_pose()` method returns a dictionary containing the coordinates of key body joints.

**2. Customizing the Pose with Parameters:**
python
from ai_pose_generator_2 import PoseGenerator

generator = PoseGenerator()
pose = generator.generate_pose(style="athletic", gender="female")
print(pose) # Returns a pose based on the specified style and gender

This example shows how to influence the generated pose using parameters like `style` and `gender`. Different styles and gender options will affect the generated pose's characteristics.

**3. Integrating with an Image Processing Pipeline:**
python
from ai_pose_generator_2 import PoseGenerator
from PIL import Image, ImageDraw

generator = PoseGenerator()
pose = generator.generate_pose()

# Example: Create a simple image and draw the pose keypoints
image = Image.new("RGB", (512, 512), "white")
draw = ImageDraw.Draw(image)

for keypoint, coordinates in pose.items():
    x, y = coordinates
    draw.ellipse((x - 5, y - 5, x + 5, y + 5), fill="red")

image.save("pose_image.png") # Saves the image with the pose

This example demonstrates how to integrate the generated pose data into an image processing workflow. It creates a basic image and draws red circles at the keypoint coordinates returned by the generator.

**4. Generating Multiple Poses:**
python
from ai_pose_generator_2 import PoseGenerator

generator = PoseGenerator()
poses = generator.generate_multiple_poses(num_poses=3)

for i, pose in enumerate(poses):
    print(f"Pose {i+1}: {pose}")

This example showcases the ability to generate multiple poses in a single call, which can be useful for creating animation sequences or analyzing variations in pose generation.

**5. Specifying Body Type Parameters**
python
from ai_pose_generator_2 import PoseGenerator

generator = PoseGenerator()
pose = generator.generate_pose(body_type="muscular", age_range="adult")
print(pose)

This example shows how to generate poses with specific body types and age ranges.

## Features

*   **Effortless Pose Generation:** Generate realistic human poses with a single function call.
*   **Customizable Parameters:** Control pose style, gender, body type, and age range for tailored results.
*   **Integration Ready:** Easily integrate generated pose data into image processing, animation, and other creative applications.
*   **Multiple Pose Generation:** Generate batches of poses efficiently.
*   **Simple API:** Easy-to-use API for both beginners and experienced developers.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

This project is a gateway to the ai-pose-generator-2 ecosystem. For advanced features and full capabilities, please visit: https://supermaker.ai/image/ai-pose-generator/