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import kornia | |
from ..utils.base_model import BaseModel | |
class DISK(BaseModel): | |
default_conf = { | |
"weights": "depth", | |
"max_keypoints": None, | |
"nms_window_size": 5, | |
"detection_threshold": 0.0, | |
"pad_if_not_divisible": True, | |
} | |
required_inputs = ["image"] | |
def _init(self, conf): | |
self.model = kornia.feature.DISK.from_pretrained(conf["weights"]) | |
def _forward(self, data): | |
image = data["image"] | |
features = self.model( | |
image, | |
n=self.conf["max_keypoints"], | |
window_size=self.conf["nms_window_size"], | |
score_threshold=self.conf["detection_threshold"], | |
pad_if_not_divisible=self.conf["pad_if_not_divisible"], | |
) | |
return { | |
"keypoints": [f.keypoints for f in features][0][None], | |
"scores": [f.detection_scores for f in features][0][None], | |
"descriptors": [f.descriptors.t() for f in features][0][None], | |
} | |