From a5cd77214f710a2ec4fcf46d5de1bc3a05c95c33 Mon Sep 17 00:00:00 2001 From: bddppq Date: Fri, 1 Sep 2023 14:17:24 -0700 Subject: [PATCH] Add client docs for using fully managed sdxl endpoint (#27) * Add client docs for using fully managed sdxl endpoint * Add images and missing imports * add more images * add images * format * update images --- advanced/sdxl/README.md | 87 ++++++++++++++++++++++++++++++- advanced/sdxl/assets/image.png | Bin 0 -> 404753 bytes advanced/sdxl/assets/inpaint.png | Bin 0 -> 1201245 bytes advanced/sdxl/assets/mask.png | Bin 0 -> 12106 bytes advanced/sdxl/assets/txt2img.png | Bin 0 -> 1252697 bytes 5 files changed, 85 insertions(+), 2 deletions(-) create mode 100644 advanced/sdxl/assets/image.png create mode 100644 advanced/sdxl/assets/inpaint.png create mode 100644 advanced/sdxl/assets/mask.png create mode 100644 advanced/sdxl/assets/txt2img.png diff --git a/advanced/sdxl/README.md b/advanced/sdxl/README.md index 6db6e2c..e08247f 100644 --- a/advanced/sdxl/README.md +++ b/advanced/sdxl/README.md @@ -8,6 +8,90 @@ There are two ways to access SDXL model: Lepton provides the SDXL model as a fully managed api endpoints at https://sdxl.lepton.run. Users can easily use the lepton Python client or existing https request tool to generate high resolution realistic images right away. +Creating the client: +```python +from leptonai.client import Client + +API_URL = "https://sdxl.lepton.run" +TOKEN = "YOUR_TOKEN_HERE" + +c = Client(API_URL, token=TOKEN) +``` + +Text to Image: +```python +prompt = "A cat launching rocket" +seed = 1234 +image_bytes = c.txt2img(prompt=prompt, seed=seed) +with open("txt2img_prompt.png", "wb") as f: + f.write(image_bytes) +``` + +Text to Image (with refiner): +```python +prompt = "A cat launching rocket" +seed = 1234 +image_bytes = c.txt2img(prompt=prompt, seed=seed, use_refiner=True) +with open("txt2img_prompt_refiner.png", "wb") as f: + f.write(image_bytes) +``` + + +Inpaint +```python +import base64 +import requests + +from leptonai.photon import FileParam + + +img_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png" +mask_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png" +prompt = "Mickey mouse sitting on a bench" +seed = 2236 + + +# Directly using urls to pass images +image_bytes = c.inpaint(image=img_url, mask_image=mask_url, prompt=prompt, seed=seed) +with open("inpaint_url.png", "wb") as f: + f.write(image_bytes) + +# Or use FileParam to send image files: +img_content = requests.get(img_url).content +mask_content = requests.get(mask_url).content +image_bytes = c.inpaint( + image=FileParam(img_content), + mask_image=FileParam(mask_content), + prompt=prompt, + seed=seed, +) +with open("inpaint_file_param.png", "wb") as f: + f.write(image_bytes) + +# Or use base64 to encode image files: +img_content = requests.get(img_url).content +mask_content = requests.get(mask_url).content +image_bytes = c.inpaint( + image=base64.b64encode(img_content).decode("ascii"), + mask_image=base64.b64encode(mask_content).decode("ascii"), + prompt=prompt, + seed=seed, +) +with open("inpaint_base64.png", "wb") as f: + f.write(image_bytes) +``` +Image: + + + +Mask: + + + +Result: + + + ## Dedicated SDXL inference service If fully managed api does not fit your use case, you can also easily launch a dedicated SDXL model inference service on Lepton platform. @@ -47,8 +131,7 @@ Once the inference service is up (either locally or in the cloud), you can use t ```python from leptonai.client import Client -SERVICE_URL = "https://sdxl.lepton.run" # if use fully managed api -# SERVICE_URL = "http://localhost:8080" # if run locally +SERVICE_URL = "http://localhost:8080" # if run locally # SERVICE_URL = "DEPLOYMENT URL shown on Lepton Cloud Platform" # if run on the Lepton Cloud Platform c = Client(SERVICE_URL) diff --git a/advanced/sdxl/assets/image.png b/advanced/sdxl/assets/image.png new file mode 100644 index 0000000000000000000000000000000000000000..e84dfc8554d344a69afb1fe8c7b8b2997d4e5e11 GIT binary patch literal 404753 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