| import torch | |
| from transformers import CLIPProcessor, CLIPVisionModel | |
| from modules import devices | |
| import os | |
| from annotator.annotator_path import clip_vision_path | |
| remote_model_path = "https://huggingface.co./openai/clip-vit-large-patch14/resolve/main/pytorch_model.bin" | |
| clip_path = clip_vision_path | |
| print(f'ControlNet ClipVision location: {clip_path}') | |
| clip_proc = None | |
| clip_vision_model = None | |
| def apply_clip(img): | |
| global clip_proc, clip_vision_model | |
| if clip_vision_model is None: | |
| modelpath = os.path.join(clip_path, 'pytorch_model.bin') | |
| if not os.path.exists(modelpath): | |
| from basicsr.utils.download_util import load_file_from_url | |
| load_file_from_url(remote_model_path, model_dir=clip_path) | |
| clip_proc = CLIPProcessor.from_pretrained(clip_path) | |
| clip_vision_model = CLIPVisionModel.from_pretrained(clip_path) | |
| with torch.no_grad(): | |
| clip_vision_model = clip_vision_model.to(devices.get_device_for("controlnet")) | |
| style_for_clip = clip_proc(images=img, return_tensors="pt")['pixel_values'] | |
| style_feat = clip_vision_model(style_for_clip.to(devices.get_device_for("controlnet")))['last_hidden_state'] | |
| return style_feat | |
| def unload_clip_model(): | |
| global clip_proc, clip_vision_model | |
| if clip_vision_model is not None: | |
| clip_vision_model.cpu() |