--- title: Codeformer API Usage Guide createdAt: Thu Jul 18 2024 06:12:37 GMT+0000 (Coordinated Universal Time) updatedAt: Thu Jul 18 2024 13:40:04 GMT+0000 (Coordinated Universal Time) --- # Codeformer API Usage Guide ## Introduction This document will guide developers on how to use the aonweb library to call the Codeformer API, is a deep learning model designed primarily for image restoration tasks, particularly for enhancing the quality of low-resolution, degraded, or old images. It is known for its ability to perform face restoration, making it especially useful for tasks such as upscaling low-resolution faces in images or videos ## Prerequisites - Node.js environment - `aonweb` library installed - Valid Aonet APPID ## Basic Usage ### 1. Import Required Modules ```js import { AI, AIOptions } from 'aonweb'; ``` ### 2. Initialize AI Instance ```js const ai_options = new AIOptions({ appId: 'your_app_id_here', dev_mode: true }); const aonweb = new AI(ai_options); ``` ### 3. Prepare Input Data Example ```js const data = { input:{ "image": "https://replicate.delivery/mgxm/7534e8f1-ee01-4d66-ae40-36343e5eb44a/003.png", "upscale": 2, "face_upsample": true, "background_enhance": true, "codeformer_fidelity": 0.1 } }; ``` ### 4. Call the AI Model ```js const price = 8; // Cost of the AI call try { const response = await aonweb.prediction("/predictions/ai/codeformer@lucataco", data, price); // Handle response console.log("Codeformer result:", response); } catch (error) { // Error handling console.error("Error generating :", error); } ``` ### Parameter Description - `image`: String, Please provide the image file that needs to be processed. - `upscale`: String, The final upsampling scale of the image. - `face_upsample`: String, Upsample restored faces for high-resolution AI-created images. - `background_enhance`: Boolean, Enhance background image with Real-ESRGAN. - `codeformer_fidelity`: Boolean, Balance the quality (lower number) and fidelity (higher number). ### Notes - Ensure that the provided image URL is publicly accessible and of good quality to achieve the best recognition results. - The API may take some time to process the input and generate the result, consider implementing appropriate wait or loading states. - Handle possible errors, such as network issues, invalid input, or API limitations. - Adhere to the terms of use and privacy regulations, especially when handling image samples of others. ### Example Response The API response will contain the results of the image recognition or other relevant information. Parse and use the response data according to the actual API documentation.