add IP-Adapter-FaceID-SDXL demo

README.md

@@ -124,6 +124,70 @@ images = ip_model.generate(
 
 ```
 
+### IP-Adapter-FaceID-SDXL
+
+Firstly, you should use [insightface](https://github.com/deepinsight/insightface) to extract face ID embedding:
+
+```python
+
+import cv2
+from insightface.app import FaceAnalysis
+import torch
+
+app = FaceAnalysis(name="buffalo_l", providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])
+app.prepare(ctx_id=0, det_size=(640, 640))
+
+image = cv2.imread("person.jpg")
+faces = app.get(image)
+
+faceid_embeds = torch.from_numpy(faces[0].normed_embedding).unsqueeze(0)
+```
+
+Then, you can generate images conditioned on the face embeddings:
+
+```python
+
+import torch
+from diffusers import StableDiffusionXLPipeline, DDIMScheduler
+from PIL import Image
+
+from ip_adapter.ip_adapter_faceid import IPAdapterFaceIDXL
+
+base_model_path = "/dockerdata/models/RealVisXL_V3.0/"
+ip_ckpt = "ip-adapter-faceid_sdxl.bin"
+device = "cuda"
+
+noise_scheduler = DDIMScheduler(
+    num_train_timesteps=1000,
+    beta_start=0.00085,
+    beta_end=0.012,
+    beta_schedule="scaled_linear",
+    clip_sample=False,
+    set_alpha_to_one=False,
+    steps_offset=1,
+)
+pipe = StableDiffusionXLPipeline.from_pretrained(
+    base_model_path,
+    torch_dtype=torch.float16,
+    scheduler=noise_scheduler,
+    add_watermarker=False,
+)
+
+# load ip-adapter
+ip_model = IPAdapterFaceIDXL(pipe, ip_ckpt, device)
+
+# generate image
+prompt = "A closeup shot of a beautiful Asian teenage girl in a white dress wearing small silver earrings in the garden, under the soft morning light"
+negative_prompt = "monochrome, lowres, bad anatomy, worst quality, low quality, blurry"
+
+images = ip_model.generate(
+    prompt=prompt, negative_prompt=negative_prompt, faceid_embeds=faceid_embeds, num_samples=2,
+    width=1024, height=1024,
+    num_inference_steps=30, guidance_scale=7.5, seed=2023
+)
+
+```
+
 ### IP-Adapter-FaceID-Plus
 
 Firstly, you should use [insightface](https://github.com/deepinsight/insightface) to extract face ID embedding and face image: