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import os
from .api import make_detectron2_model, semantic_run
from annotator.base_annotator import BaseProcessor
class OneformerDetector(BaseProcessor):
configs = {
"coco": {
"name": "150_16_swin_l_oneformer_coco_100ep.pth",
"config": 'configs/coco/oneformer_swin_large_IN21k_384_bs16_100ep.yaml'
},
"ade20k": {
"name": "250_16_swin_l_oneformer_ade20k_160k.pth",
"config": 'configs/ade20k/oneformer_swin_large_IN21k_384_bs16_160k.yaml'
}
}
def __init__(self, config=configs["coco"], **kwargs):
super().__init__(**kwargs)
self.model = None
self.metadata = None
self.config = config
self.model_dir = os.path.join(self.models_path, "oneformer")
def load_model(self):
remote_model_path = "https://huggingface.co/lllyasviel/Annotators/resolve/main/" + self.config["name"]
modelpath = os.path.join(self.model_dir, self.config["name"])
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=self.model_dir)
config = os.path.join(os.path.dirname(__file__), self.config["config"])
model, self.metadata = make_detectron2_model(config, modelpath)
self.model = model
def unload_model(self):
if self.model is not None:
self.model.model.cpu()
def __call__(self, img):
if self.model is None:
self.load_model()
self.model.model.to(self.device)
return semantic_run(img, self.model, self.metadata)
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