| | import os |
| | import torch |
| | import numpy as np |
| | from einops import rearrange |
| | from annotator.pidinet.model import pidinet |
| | from annotator.util import safe_step |
| | from annotator.annotator_path import models_path, DEVICE |
| | import safetensors.torch |
| | |
| |
|
| | def get_state_dict(d): |
| | return d.get("state_dict", d) |
| |
|
| | def load_state_dict(ckpt_path, location="cpu"): |
| | _, extension = os.path.splitext(ckpt_path) |
| | if extension.lower() == ".safetensors": |
| | state_dict = safetensors.torch.load_file(ckpt_path, device=location) |
| | else: |
| | state_dict = torch.load(ckpt_path, map_location=torch.device(location)) |
| | state_dict = get_state_dict(state_dict) |
| | return state_dict |
| |
|
| | netNetwork = None |
| | remote_model_path = "https://huggingface.co/lllyasviel/Annotators/resolve/main/table5_pidinet.pth" |
| | modeldir = os.path.join(models_path, "pidinet") |
| | old_modeldir = os.path.dirname(os.path.realpath(__file__)) |
| |
|
| | def apply_pidinet(input_image, is_safe=False, apply_fliter=False): |
| | global netNetwork |
| | if netNetwork is None: |
| | modelpath = os.path.join(modeldir, "table5_pidinet.pth") |
| | old_modelpath = os.path.join(old_modeldir, "table5_pidinet.pth") |
| | if os.path.exists(old_modelpath): |
| | modelpath = old_modelpath |
| | elif not os.path.exists(modelpath): |
| | from basicsr.utils.download_util import load_file_from_url |
| | load_file_from_url(remote_model_path, model_dir=modeldir) |
| | netNetwork = pidinet() |
| | ckp = load_state_dict(modelpath) |
| | netNetwork.load_state_dict({k.replace('module.',''):v for k, v in ckp.items()}) |
| | |
| | netNetwork = netNetwork.to(DEVICE) |
| | netNetwork.eval() |
| | assert input_image.ndim == 3 |
| | input_image = input_image[:, :, ::-1].copy() |
| | with torch.no_grad(): |
| | image_pidi = torch.from_numpy(input_image).float().to(DEVICE) |
| | image_pidi = image_pidi / 255.0 |
| | image_pidi = rearrange(image_pidi, 'h w c -> 1 c h w') |
| | edge = netNetwork(image_pidi)[-1] |
| | edge = edge.cpu().numpy() |
| | if apply_fliter: |
| | edge = edge > 0.5 |
| | if is_safe: |
| | edge = safe_step(edge) |
| | edge = (edge * 255.0).clip(0, 255).astype(np.uint8) |
| | |
| | return edge[0][0] |
| |
|
| | def unload_pid_model(): |
| | global netNetwork |
| | if netNetwork is not None: |
| | netNetwork.cpu() |
