Notebook Utils

This repository contains utility functions for use within Jupyter notebooks. These utilities interact with various FaaS services, such as inpainting and segmentation.

Features

• Inpainting Utility: Utilize FaaS services to perform image inpainting, filling in missing parts of an image based on a mask.
• Segmentation Utility: Leverage FaaS services to segment images, identifying and isolating different parts of an image.
• Environment Variable Configuration: Easy setup with environment variables for API keys and endpoint IDs.
• Modular Design: Organized into specific modules for inpainting and segmentation, allowing for easy extension and maintenance.
• Jupyter Notebook Integration: Designed to be used within Jupyter notebooks, making it ideal for data scientists and researchers.
• Example Usage: Provides example code snippets to help users get started quickly.

Structure

• cloud_service_utils/: Contains specific implementations for inpainting and segmentation.

Usage

To use the utilities, import the necessary functions from the respective modules:

from cloud_service_utils.inpainting import inpaint_image_via_faas
from cloud_service_utils.segmentation import segment_image_via_faas

Setup

Ensure you have the required environment variables set up:

• RUNPOD_API_KEY: Your API key for accessing the FaaS services.
• RUNPOD_ENDPOINT_ID: The endpoint ID for the specific service.

Example

Here's an example of how to use the inpainting utility:

import cv2
from cloud_service_utils.inpainting import inpaint_image_via_faas

image = cv2.imread("input.png")
mask = cv2.imread("mask.png", cv2.IMREAD_GRAYSCALE)

result = inpaint_image_via_faas(image=image, mask=mask, debug=True)
cv2.imwrite("output.png", result)