Generate Images with Semantic Kernel
Semantic Kernel skill providing image generation and vision capabilities through Python examples demonstrating prompt-based and direct image generation
Why it matters
Leverage Semantic Kernel's image generation capabilities to create visual content programmatically. This asset enables the integration of AI-powered image synthesis into your applications.
Outcomes
What it gets done
Integrate image generation into applications using Semantic Kernel.
Programmatically control image creation parameters.
Explore examples of image generation prompts.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/sk-concept-images | bash Overview
Semantic Kernel - Images
This skill provides image generation and vision capabilities for Semantic Kernel-based AI assistants. It includes two Python example files: `image_gen_prompt.py` and `image_generation.py`, demonstrating how to implement visual AI features within the Semantic Kernel framework. Use this skill when you need to extend an AI assistant with the ability to generate images from prompts or process visual inputs. It's appropriate for developers building conversational AI systems that require visual content creation or image understanding as part of their workflow.
What it does
When you need to add visual content creation and image understanding to your AI assistant, this skill delivers image generation and vision capabilities using Semantic Kernel's Python SDK. It provides two working examples: image_gen_prompt.py for prompt-based image generation and image_generation.py for direct image generation workflows, enabling you to integrate visual AI features into conversational and automated systems.
Source README
Image generation and vision capabilities with Semantic Kernel
Examples (2 files):
image_gen_prompt.pyimage_generation.py
Discussion
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