update img2img

README.md

@@ -138,6 +138,54 @@ prompt="a photo of a cat"
 image=pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0, timesteps=[399]).images[0]
 ```
 
+#### 4-step T2I Adapter 
+
+```python 
+from diffusers import StableDiffusionXLAdapterPipeline, T2IAdapter, AutoencoderKL, UNet2DConditionModel, LCMScheduler
+from diffusers.utils import load_image, make_image_grid
+from controlnet_aux.canny import CannyDetector
+from huggingface_hub import hf_hub_download
+import torch
+
+# load adapter
+adapter = T2IAdapter.from_pretrained("TencentARC/t2i-adapter-canny-sdxl-1.0", torch_dtype=torch.float16, varient="fp16").to("cuda")
+
+vae=AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
+
+base_model_id = "stabilityai/stable-diffusion-xl-base-1.0"
+repo_name = "tianweiy/DMD2"
+ckpt_name = "dmd2_sdxl_4step_unet_fp16.bin"
+# Load model.
+unet = UNet2DConditionModel.from_config(base_model_id, subfolder="unet").to("cuda", torch.float16)
+unet.load_state_dict(torch.load(hf_hub_download(repo_name, ckpt_name), map_location="cuda"))
+
+pipe = StableDiffusionXLAdapterPipeline.from_pretrained(
+    base_model_id, unet=unet, vae=vae, adapter=adapter, torch_dtype=torch.float16, variant="fp16", 
+).to("cuda")
+pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
+pipe.enable_xformers_memory_efficient_attention()
+
+canny_detector = CannyDetector()
+
+url = "https://huggingface.co/Adapter/t2iadapter/resolve/main/figs_SDXLV1.0/org_canny.jpg"
+image = load_image(url)
+
+# Detect the canny map in low resolution to avoid high-frequency details
+image = canny_detector(image, detect_resolution=384, image_resolution=1024)#.resize((1024, 1024))
+
+prompt = "Mystical fairy in real, magic, 4k picture, high quality"
+
+gen_images = pipe(
+  prompt=prompt,
+  image=image,
+  num_inference_steps=4,
+  guidance_scale=0, 
+  adapter_conditioning_scale=0.8, 
+  adapter_conditioning_factor=0.5
+).images[0]
+gen_images.save('out_canny.png')
+```
+
 Pretrained models can be found in [ImageNet](experiments/imagenet/README.md) and [SDXL](experiments/sdxl/README.md). 
 
 ## Training and Evaluation