[core] ConsisID by SHYuanBest · Pull Request #10140 · huggingface/diffusers (original) (raw)

@a-r-r-o-w @HuggingFaceDocBuilderDev hi, I have add consisid to this branch, can you help us to reveiew the code? Is there anything else I missed?

import torch
from diffusers import ConsisIDPipeline
from diffusers.pipelines.consisid.consisid_utils import prepare_face_models, process_face_embeddings_infer
from diffusers.utils import export_to_video
from huggingface_hub import snapshot_download

snapshot_download(repo_id="BestWishYsh/ConsisID-preview", local_dir="BestWishYsh/ConsisID-preview")

face_helper_1, face_helper_2, face_clip_model, face_main_model, eva_transform_mean, eva_transform_std = prepare_face_models("BestWishYsh/ConsisID-preview", device="cuda", dtype=torch.bfloat16)

pipe = ConsisIDPipeline.from_pretrained("BestWishYsh/ConsisID-preview", torch_dtype=torch.bfloat16)
pipe.to("cuda")

prompt = "The video captures a boy walking along a city street, filmed in black and white on a classic 35mm camera. His expression is thoughtful, his brow slightly furrowed as if he's lost in contemplation. The film grain adds a textured, timeless quality to the image, evoking a sense of nostalgia. Around him, the cityscape is filled with vintage buildings, cobblestone sidewalks, and softly blurred figures passing by, their outlines faint and indistinct. Streetlights cast a gentle glow, while shadows play across the boy's path, adding depth to the scene. The lighting highlights the boy's subtle smile, hinting at a fleeting moment of curiosity. The overall cinematic atmosphere, complete with classic film still aesthetics and dramatic contrasts, gives the scene an evocative and introspective feel."
image = "https://github.com/PKU-YuanGroup/ConsisID/blob/main/asserts/example_images/2.png?raw=true"

id_cond, id_vit_hidden, image, face_kps = process_face_embeddings_infer(face_helper_1, face_clip_model, face_helper_2, eva_transform_mean, eva_transform_std, face_main_model, "cuda", torch.bfloat16, image, is_align_face=True)

video = pipe(image=image, prompt=prompt, use_dynamic_cfg=False, id_vit_hidden=id_vit_hidden, id_cond=id_cond, kps_cond=face_kps, generator=torch.Generator("cuda").manual_seed(42))
export_to_video(video.frames[0], "output.mp4", fps=8)