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import subprocess | |
import sys | |
from pathlib import Path | |
import torch | |
from .. import logger | |
from ..utils.base_model import BaseModel | |
mickey_path = Path(__file__).parent / "../../third_party" | |
sys.path.append(str(mickey_path)) | |
from mickey.config.default import cfg | |
from mickey.lib.models.builder import build_model | |
device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
class Mickey(BaseModel): | |
default_conf = { | |
"config_path": "config.yaml", | |
"model_name": "mickey.ckpt", | |
"max_keypoints": 3000, | |
} | |
required_inputs = [ | |
"image0", | |
"image1", | |
] | |
weight_urls = "https://storage.googleapis.com/niantic-lon-static/research/mickey/assets/mickey_weights.zip" | |
# Initialize the line matcher | |
def _init(self, conf): | |
model_path = mickey_path / "mickey/mickey_weights" / conf["model_name"] | |
zip_path = mickey_path / "mickey/mickey_weights.zip" | |
config_path = model_path.parent / self.conf["config_path"] | |
# Download the model. | |
if not model_path.exists(): | |
model_path.parent.mkdir(exist_ok=True, parents=True) | |
link = self.weight_urls | |
if not zip_path.exists(): | |
cmd = ["wget", "--quiet", link, "-O", str(zip_path)] | |
logger.info(f"Downloading the Mickey model with {cmd}.") | |
subprocess.run(cmd, check=True) | |
cmd = ["unzip", "-d", str(model_path.parent.parent), str(zip_path)] | |
logger.info(f"Running {cmd}.") | |
subprocess.run(cmd, check=True) | |
logger.info("Loading mickey model...") | |
cfg.merge_from_file(config_path) | |
self.net = build_model(cfg, checkpoint=model_path) | |
logger.info("Load Mickey model done.") | |
def _forward(self, data): | |
# data['K_color0'] = torch.from_numpy(K['im0.jpg']).unsqueeze(0).to(device) | |
# data['K_color1'] = torch.from_numpy(K['im1.jpg']).unsqueeze(0).to(device) | |
pred = self.net(data) | |
pred = { | |
**pred, | |
**data, | |
} | |
inliers = data["inliers_list"] | |
pred = { | |
"keypoints0": inliers[:, :2], | |
"keypoints1": inliers[:, 2:4], | |
} | |
return pred | |