fix: extractors

hloc/extractors/d2net.py

@@ -9,6 +9,7 @@ d2net_path = Path(__file__).parent / "../../third_party"
 sys.path.append(str(d2net_path))
 from d2net.lib.model_test import D2Net as _D2Net
 from d2net.lib.pyramid import process_multiscale
+d2net_path = Path(__file__).parent / "../../third_party/d2net"
 
 class D2Net(BaseModel):
     default_conf = {

hloc/extractors/lanet.py

@@ -5,9 +5,9 @@ import torch
 
 from ..utils.base_model import BaseModel
 
-lanet_path = Path(__file__).parent / "../../third_party"
+lanet_path = Path(__file__).parent / "../../third_party/lanet"
 sys.path.append(str(lanet_path))
-from lanet.network_v0.model import PointModel
+from network_v0.model import PointModel
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 

hloc/extractors/rord.py

@@ -6,15 +6,15 @@ import torch
 from ..utils.base_model import BaseModel
 from .. import logger
 
-rord_path = Path(__file__).parent / "../../third_party/RoRD"
+rord_path = Path(__file__).parent / "../../third_party"
 sys.path.append(str(rord_path))
-from lib.model_test import D2Net as _RoRD
-from lib.pyramid import process_multiscale
+from RoRD.lib.model_test import D2Net as _RoRD
+from RoRD.lib.pyramid import process_multiscale
 
 class RoRD(BaseModel):
     default_conf = {
         "model_name": "rord.pth",
-        "checkpoint_dir": rord_path / "models",
+        "checkpoint_dir": rord_path / "RoRD" / "models",
         "use_relu": True,
         "multiscale": False,
         "max_keypoints": 1024,

third_party/RoRD/lib/pyramid.py

@@ -2,8 +2,8 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
-from lib.exceptions import EmptyTensorError
-from lib.utils import interpolate_dense_features, upscale_positions
+from .exceptions import EmptyTensorError
+from .utils import interpolate_dense_features, upscale_positions
 
 
 def process_multiscale(image, model, scales=[.5, 1, 2]):

third_party/RoRD/lib/utils.py

@@ -4,7 +4,7 @@ import numpy as np
 
 import torch
 
-from lib.exceptions import EmptyTensorError
+from .exceptions import EmptyTensorError
 
 
 def preprocess_image(image, preprocessing=None):

third_party/d2net/lib/pyramid.py

@@ -2,8 +2,8 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
-from lib.exceptions import EmptyTensorError
-from lib.utils import interpolate_dense_features, upscale_positions
+from .exceptions import EmptyTensorError
+from .utils import interpolate_dense_features, upscale_positions
 
 
 def process_multiscale(image, model, scales=[.5, 1, 2]):

third_party/d2net/lib/utils.py

@@ -4,7 +4,7 @@ import numpy as np
 
 import torch
 
-from lib.exceptions import EmptyTensorError
+from .exceptions import EmptyTensorError
 
 
 def preprocess_image(image, preprocessing=None):