fix: lanet and r2d2

hloc/matchers/imp.py

@@ -4,7 +4,7 @@ from pathlib import Path
 
 import torch
 
-from .. import device, logger
+from .. import DEVICE, logger
 from ..utils.base_model import BaseModel
 
 pram_path = Path(__file__).parent / "../../third_party/pram"
@@ -34,7 +34,7 @@ class IMP(BaseModel):
     def _init(self, conf):
         self.conf = {**self.default_conf, **conf}
         weight_path = pram_path / "weights" / self.conf["model_name"]
-        self.net = GML(self.conf).eval().to(device)
+        self.net = GML(self.conf).eval().to(DEVICE)
         self.net.load_state_dict(
             torch.load(weight_path, map_location="cpu")["model"], strict=True
         )

third_party/lanet/augmentations.py

@@ -12,7 +12,7 @@ import torchvision
 import torchvision.transforms as transforms
 from PIL import Image
 
-from lanet_utils import image_grid
+from ..lanet_utils import image_grid
 
 
 def filter_dict(dict, keywords):

third_party/lanet/evaluation/descriptor_evaluation.py

@@ -8,7 +8,7 @@ from os import path as osp
 import cv2
 import numpy as np
 
-from lanet_utils import warp_keypoints
+from ..lanet_utils import warp_keypoints
 
 
 def select_k_best(points, descriptors, k):

third_party/lanet/evaluation/detector_evaluation.py

@@ -8,7 +8,7 @@ from os import path as osp
 import cv2
 import numpy as np
 
-from lanet_utils import warp_keypoints
+from ..lanet_utils import warp_keypoints
 
 
 def compute_repeatability(data, keep_k_points=300, distance_thresh=3):

third_party/lanet/network_v0/modules.py

@@ -2,7 +2,7 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
-from lanet_utils import image_grid
+from ..lanet_utils import image_grid
 
 
 class ConvBlock(nn.Module):

third_party/lanet/network_v1/modules.py

@@ -4,7 +4,7 @@ import torch.nn as nn
 import torch.nn.functional as F
 
 from torchvision import models
-from lanet_utils import image_grid
+from ..lanet_utils import image_grid
 
 
 class ConvBlock(nn.Module):

third_party/r2d2/extract.py

@@ -8,9 +8,9 @@ from PIL import Image
 import numpy as np
 import torch
 
-from .tools import common
-from .tools.dataloader import norm_RGB
-from .nets.patchnet import *
+from tools import common
+from tools.dataloader import norm_RGB
+from nets.patchnet import *
 
 
 def load_network(model_fn):