VisionAPI - a Python library for GPT-Based Vision Models inference
Project description
VisionAPI 👓✨ - AI Vision & Language Processing
Welcome to the Future of AI Vision 🌟
Hello and welcome to VisionAPI, where cutting-edge GPT-based models meet simplicity in a sleek API interface. Our mission is to harness the power of AI to work with images, videos, and audio to create Apps fasther than ever.
🚀 Getting Started
Prerequisites
Make sure you have Python installed on your system and you're ready to dive into the world of AI.
📦 Installation
To install VisionAPI, simply run the following command in your terminal:
pip install visionapi
🔑 Authentication
Before you begin, authenticate your OpenAI API key with the following command:
export OPENAI_API_KEY='your-api-key-here'
🔩 Usage
🖼️ Image Inference
Empower your applications to understand and describe images with precision.
import visionapi
# Initialize the Inference Engine
inference = visionapi.Inference()
# Provide an image URL or a local path
image = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
# Set your descriptive prompt
prompt = "What is this image about?"
# Get the AI's perspective
response = inference.image(image, prompt)
# Revel in the AI-generated description
print(response.message.content)
🎥 Video Inference
Narrate the stories unfolding in your videos with our AI-driven descriptions.
import visionapi
# Gear up the Inference Engine
inference = visionapi.Inference()
# Craft a captivating prompt
prompt = "Summarize the key moments in this video."
# Point to your video file
video = "path/to/video.mp4"
# Let the AI weave the narrative
response = inference.video(video, prompt)
# Display the narrative
print(response.message.content)
🎨 Image Generation
Watch your words paint pictures with our intuitive image generation capabilities.
import visionapi
# Activate the Inference Engine
inference = visionapi.Inference()
# Describe your vision
prompt = "A tranquil lake at sunset with mountains in the background."
# Bring your vision to life
image_urls = inference.generate_image(prompt, save=True) # Set `save=True` to store locally
# Behold the AI-crafted imagery
print(image_urls)
🗣️ TTS (Text to Speech)
Transform your text into natural-sounding speech with just a few lines of code.
import visionapi
# Power up the Inference Engine
inference = visionapi.Inference()
# Specify where to save the audio
save_path = "output/speech.mp3"
# Type out what you need to vocalize
text = "Hey, ready to explore AI-powered speech synthesis?"
# Make the AI speak
inference.TTS(text, save_path)
🎧 STT (Speech to Text)
Convert audio into text with unparalleled clarity, opening up a world of possibilities.
import visionapi
# Initialize the Inference Engine
inference = visionapi.Inference()
# Convert spoken words to written text
text = inference.STT('path/to/audio.mp3')
# Marvel at the transcription
print(text)
🌐 Contribute
Add cool stuff:
- Fork the repository.
- Extend the capabilities by integrating more models.
- Enhance existing features or add new ones.
- Submit a pull request with your improvements.
Your contributions are what make VisionAPI not just a tool, but a community.
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