The transpiler can translate ComfyUI's workflows to `@stable-canvas/comfyui-client` format.
npm install @stable-canvas/comfyui-client-transpilerThe transpiler can translate ComfyUI's workflows to @stable-canvas/comfyui-client format.
``
npm install @stable-canvas/comfyui-client-transpiler
references:
Since the order of widgets may change at any time, the function from .png to code may be unstable. It is recommended to use .json(API Format) to code
`ts
import { JsonReader } from "@stable-canvas/cw-reader";
import { Transpiler } from "./src/main";
import fs from "fs";
const file1 = await fs.promises.readFile("./tests/workflow-min.json");
const reader = new JsonReader(JSON.parse(file1.toString("utf-8")));
const workflow = await reader.getWorkflow();
const transpiler = new Transpiler(workflow);
const code = transpiler.toCode();
await fs.promises.writeFile("./demo_output.ts", code, {
encoding: "utf-8",
});
`
`ts`
const [LATENT_1] = cls.EmptyLatentImage({
width: 512,
height: 512,
batch_size: 1,
});
const [MODEL_1, CLIP_1, VAE_1] = cls.CheckpointLoaderSimple({
ckpt_name: "lofi_v5.baked.fp16.safetensors",
});
const [CONDITIONING_2] = cls.CLIPTextEncode({
text: "worst quality, bad anatomy, embedding:NG_DeepNegative_V1_75T",
clip: CLIP_1,
});
const [CONDITIONING_1] = cls.CLIPTextEncode({
text: "best quality, 1girl",
clip: CLIP_1,
});
const [LATENT_2] = cls.KSampler({
seed: 2765233096,
steps: 35,
cfg: 4,
sampler_name: "dpmpp_2m_sde_gpu",
scheduler: "karras",
denoise: 1,
model: MODEL_1,
positive: CONDITIONING_1,
negative: CONDITIONING_2,
latent_image: LATENT_1,
});
const [IMAGE_1] = cls.VAEDecode({
samples: LATENT_2,
vae: VAE_1,
});
const [] = cls.SaveImage({
filename_prefix: "from-sc-comfy-ui-client",
images: IMAGE_1,
});
`ts
import { ImageReader } from "@stable-canvas/cw-reader";
import { Transpiler } from "./src/main";
import fs from "fs";
const file1 = await fs.promises.readFile("./tests/img2img_workflow.png");
const reader = new ImageReader(file1.buffer);
const workflow = await reader.getWorkflow();
const transpiler = new Transpiler(workflow);
const code = transpiler.toCode();
await fs.promises.writeFile("./img2img_workflow.ts", code, {
encoding: "utf-8",
});
`
`ts``
const [MODEL_1, CLIP_1, VAE_1] = cls.CheckpointLoaderSimple({
ckpt_name: "v1-5-pruned-emaonly.ckpt",
});
const [CONDITIONING_2] = cls.CLIPTextEncode({
text: "photograph of victorian woman with wings, sky clouds, meadow grass\n",
clip: CLIP_1,
});
const [CONDITIONING_1] = cls.CLIPTextEncode({
text: "watermark, text\n",
clip: CLIP_1,
});
const [IMAGE_2, MASK_1] = cls.LoadImage({
image: "example.png",
upload: "image",
});
const [LATENT_1] = cls.VAEEncode({
pixels: IMAGE_2,
vae: VAE_1,
});
const [LATENT_2] = cls.KSampler({
seed: 280823642470253,
control_after_generate: "randomize",
steps: 20,
cfg: 8,
sampler_name: "dpmpp_2m",
scheduler: "normal",
denoise: 0.8700000000000001,
model: MODEL_1,
positive: CONDITIONING_2,
negative: CONDITIONING_1,
latent_image: LATENT_1,
});
const [IMAGE_1] = cls.VAEDecode({
samples: LATENT_2,
vae: VAE_1,
});
const [] = cls.SaveImage({
filename_prefix: "ComfyUI",
images: IMAGE_1,
});