VisionAPI 0.1.4

VisionAPI - a Python library for GPT-Based Vision Models inference

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.