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import torch |
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import spaces |
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from diffusers import StableDiffusionPipeline, DDIMScheduler, AutoencoderKL |
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from ip_adapter.ip_adapter_faceid import IPAdapterFaceID |
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from huggingface_hub import hf_hub_download |
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from insightface.app import FaceAnalysis |
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import gradio as gr |
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import cv2 |
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base_model_path = "SG161222/Realistic_Vision_V4.0_noVAE" |
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vae_model_path = "stabilityai/sd-vae-ft-mse" |
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ip_ckpt = hf_hub_download(repo_id='h94/IP-Adapter-FaceID', filename="ip-adapter-faceid_sd15.bin", repo_type="model") |
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device = "cuda" |
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noise_scheduler = DDIMScheduler( |
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num_train_timesteps=1000, |
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beta_start=0.00085, |
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beta_end=0.012, |
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beta_schedule="scaled_linear", |
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clip_sample=False, |
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set_alpha_to_one=False, |
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steps_offset=1, |
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) |
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vae = AutoencoderKL.from_pretrained(vae_model_path).to(dtype=torch.float16) |
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pipe = StableDiffusionPipeline.from_pretrained( |
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base_model_path, |
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torch_dtype=torch.float16, |
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scheduler=noise_scheduler, |
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vae=vae, |
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) |
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ip_model = IPAdapterFaceID(pipe, ip_ckpt, device) |
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@spaces.GPU |
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def generate_image(images, prompt, negative_prompt): |
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pipe.to(device) |
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app = FaceAnalysis(name="buffalo_l", providers=['CUDAExecutionProvider', 'CPUExecutionProvider']) |
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app.prepare(ctx_id=0, det_size=(640, 640)) |
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faceid_all_embeds = [] |
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for image in images: |
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face = cv2.imread(image) |
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faces = app.get(face) |
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faceid_embed = torch.from_numpy(faces[0].normed_embedding).unsqueeze(0) |
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faceid_all_embeds.append(faceid_embed) |
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average_embedding = torch.mean(torch.stack(faceid_all_embeds, dim=0), dim=0) |
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image = ip_model.generate( |
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prompt=prompt, negative_prompt=negative_prompt, faceid_embeds=average_embedding, width=512, height=512, num_inference_steps=30 |
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) |
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print(image) |
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return image |
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demo = gr.Interface( |
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fn=generate_image, |
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inputs=[ |
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gr.Files( |
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label="Drag 1 or more photos of your face", |
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file_types=["image"] |
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), |
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gr.Textbox(label="Prompt", |
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info="Try something like 'a photo of a man/woman/person'", |
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placeholder="A photo of a [man/woman/person]..."), |
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gr.Textbox(label="Negative Prompt") |
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], |
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outputs=[gr.Gallery(label="Generated Image")], |
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title="IP-Adapter-FaceID demo", |
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description="Demo for the [h94/IP-Adapter-FaceID model](https://huggingface.co/h94/IP-Adapter-FaceID)", |
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allow_flagging=False, |
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) |
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demo.launch() |
