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()