Blog Explanation: Medium
This repository contains the backend of a Stable Diffusion application, specifically designed for generating creative logos. The app utilizes Stable Diffusion version 1.5 integrated with a Control Net Canny model to transform standard logos into more creative versions.
- Stable Diffusion 1.5 with Control Net Canny: Leverages the latest in AI to generate unique logo designs.
- FastAPI Implementation: Built using FastAPI for efficient and scalable backend services.
- Base64 Image Encoding: Accepts and processes images encoded in Base64 format, streamlining the image handling process.
- Seamless Inference Process: Conducts inference on the decoded images and returns the creatively enhanced logos in Base64 format.
- The FastAPI backend accepts a 'BaseSDRequest' object containing all necessary parameters.
- Images should be sent as Base64 encoded strings. These are then decoded at the backend for processing.
- After inference, the final image is re-encoded in Base64 and returned to the user.
Included in the repository is a Google Colab notebook for the Logo Avatars POC. This interactive notebook allows you to run the entire process and see the results in real-time. Just copy link of any image & run it. Colab Notebook
GET /heartbeat| Parameter | Type | Description |
|---|---|---|
none |
none |
To check if the server is running |
POST /generate_image| Name | Type | Description |
|---|---|---|
prompt |
string |
Required. The prompt for generating the image. |
encoded_control_net_image |
string |
Required. The encoded control net image in base64 format. |
control_type |
string |
Required. The type of control used in image generation. |
height |
int |
Required. The height of the generated image. |
width |
int |
Required. The width of the generated image. |
controlnet_conditioning_scale |
float |
The scale of control net conditioning. Default is 1.0. |
negative_prompt |
string |
A string specifying negative prompts. Default is "deformed, nsfw, blurr". |
base_model |
string |
The base model used for generation. Default is "digiplay/Juggernaut_final". |
num_inference_steps |
int |
The number of inference steps. Default is 20. |
guidance_scale |
float |
The guidance scale. Default is 0.6. |
num_images_per_prompt |
int |
The number of images generated per prompt. Default is 1. |
{
"prompt": "Colorful, jungle surrounding, trees, natural, detailed, hd, 4k, best quality, extremely detailed",
"generated_image_encoded": "base64_encoded_generated_image_string"
}
