Spaces:
Running
Running
File size: 1,807 Bytes
1b369eb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 |
import sys
import yaml
from pathlib import Path
from ..utils.base_model import BaseModel
from .. import logger, MODEL_REPO_ID, DEVICE
rdd_path = Path(__file__).parent / "../../third_party/rdd"
sys.path.append(str(rdd_path))
from RDD.RDD import build as build_rdd
class Rdd(BaseModel):
default_conf = {
"keypoint_threshold": 0.1,
"max_keypoints": 4096,
"model_name": "RDD-v2.pth",
}
required_inputs = ["image"]
def _init(self, conf):
logger.info("Loading RDD model...")
model_path = self._download_model(
repo_id=MODEL_REPO_ID,
filename="{}/{}".format(
Path(__file__).stem, self.conf["model_name"]
),
)
config_path = rdd_path / "configs/default.yaml"
with open(config_path, "r") as file:
config = yaml.safe_load(file)
config["top_k"] = conf["max_keypoints"]
config["detection_threshold"] = conf["keypoint_threshold"]
config["device"] = DEVICE
self.net = build_rdd(config=config, weights=model_path)
self.net.eval()
logger.info("Loading RDD model done!")
def _forward(self, data):
image = data["image"]
pred = self.net.extract(image)[0]
keypoints = pred["keypoints"]
descriptors = pred["descriptors"]
scores = pred["scores"]
if self.conf["max_keypoints"] < len(keypoints):
idxs = scores.argsort()[-self.conf["max_keypoints"] or None :]
keypoints = keypoints[idxs, :2]
descriptors = descriptors[idxs]
scores = scores[idxs]
pred = {
"keypoints": keypoints[None],
"descriptors": descriptors[None].permute(0, 2, 1),
"scores": scores[None],
}
return pred
|