remove root dir logic from hydra (#587)

nerfactory/datamanagers/dataparsers/blender_parser.py

@@ -27,7 +27,7 @@ from nerfactory.cameras.cameras import Cameras, CameraType
 from nerfactory.datamanagers.dataparsers.base import DataParser, DataParserConfig
 from nerfactory.datamanagers.structs import DatasetInputs, SceneBounds
 from nerfactory.utils.colors import get_color
-from nerfactory.utils.io import get_absolute_path, load_from_json
+from nerfactory.utils.io import load_from_json
 
 
 @dataclass
@@ -64,12 +64,11 @@ class Blender(DataParser):
         else:
             alpha_color_tensor = None
 
-        abs_dir = get_absolute_path(self.data_directory)
-        meta = load_from_json(abs_dir / f"transforms_{split}.json")
+        meta = load_from_json(self.data_directory / f"transforms_{split}.json")
         image_filenames = []
         poses = []
         for frame in meta["frames"]:
-            fname = abs_dir / Path(frame["file_path"].replace("./", "") + ".png")
+            fname = self.data_directory / Path(frame["file_path"].replace("./", "") + ".png")
             image_filenames.append(fname)
             poses.append(np.array(frame["transform_matrix"]))
         poses = np.array(poses).astype(np.float32)

nerfactory/datamanagers/dataparsers/friends_parser.py

@@ -27,7 +27,7 @@ from rich.console import Console
 from nerfactory.cameras.cameras import Cameras, CameraType
 from nerfactory.datamanagers.dataparsers.base import DataParser, DataParserConfig
 from nerfactory.datamanagers.structs import DatasetInputs, SceneBounds, Semantics
-from nerfactory.utils.io import get_absolute_path, load_from_json
+from nerfactory.utils.io import load_from_json
 
 CONSOLE = Console()
 
@@ -78,9 +78,7 @@ class Friends(DataParser):
 
     def _generate_dataset_inputs(self, split="train"):  # pylint: disable=unused-argument,too-many-statements
 
-        abs_dir = get_absolute_path(self.config.data_directory)
-
-        cameras_json = load_from_json(abs_dir / "cameras.json")
+        cameras_json = load_from_json(self.config.data_directory / "cameras.json")
         frames = cameras_json["frames"]
         bbox = torch.tensor(cameras_json["bbox"])
 
@@ -96,7 +94,7 @@ class Friends(DataParser):
         camera_to_worlds = []
         for frame in frames:
             # unpack data
-            image_filename = abs_dir / images_folder / frame["image_name"]
+            image_filename = self.config.data_directory / images_folder / frame["image_name"]
             intrinsics = torch.tensor(frame["intrinsics"])
             camtoworld = torch.tensor(frame["camtoworld"])[:3]
             # append data
@@ -152,7 +150,7 @@ class Friends(DataParser):
                 )
                 for image_filename in image_filenames
             ]
-            panoptic_classes = load_from_json(abs_dir / "panoptic_classes.json")
+            panoptic_classes = load_from_json(self.config.data_directory / "panoptic_classes.json")
             stuff_classes = panoptic_classes["stuff"]
             stuff_colors = torch.tensor(panoptic_classes["stuff_colors"], dtype=torch.float32) / 255.0
             thing_classes = panoptic_classes["thing"]

nerfactory/datamanagers/dataparsers/instant_ngp_parser.py

@@ -28,7 +28,7 @@ from nerfactory.cameras import utils as camera_utils
 from nerfactory.cameras.cameras import Cameras, CameraType
 from nerfactory.datamanagers.dataparsers.base import DataParser, DataParserConfig
 from nerfactory.datamanagers.structs import DatasetInputs, SceneBounds
-from nerfactory.utils.io import get_absolute_path, load_from_json
+from nerfactory.utils.io import load_from_json
 
 
 @dataclass
@@ -53,14 +53,12 @@ class InstantNGP(DataParser):
 
     def _generate_dataset_inputs(self, split="train"):
 
-        abs_dir = get_absolute_path(self.config.data_directory)
-
-        meta = load_from_json(abs_dir / "transforms.json")
+        meta = load_from_json(self.config.data_directory / "transforms.json")
         image_filenames = []
         poses = []
         num_skipped_image_filenames = 0
         for frame in meta["frames"]:
-            fname = abs_dir / Path(frame["file_path"])
+            fname = self.config.data_directory / Path(frame["file_path"])
             if not fname:
                 num_skipped_image_filenames += 1
             else:

nerfactory/datamanagers/dataparsers/mipnerf_parser.py

@@ -26,7 +26,6 @@ import torch
 from nerfactory.cameras.cameras import Cameras, CameraType
 from nerfactory.datamanagers.dataparsers.base import DataParser, DataParserConfig
 from nerfactory.datamanagers.structs import DatasetInputs, SceneBounds
-from nerfactory.utils.io import get_absolute_path
 
 
 @dataclass
@@ -76,11 +75,10 @@ class Mipnerf360(DataParser):
         return poses_orig
 
     def _generate_dataset_inputs(self, split="train"):
-        abs_dir = get_absolute_path(self.config.data_directory)
         image_dir = "images"
         if self.config.downscale_factor > 1:
             image_dir += f"_{self.config.downscale_factor}"
-        image_dir = abs_dir / image_dir
+        image_dir = self.config.data_directory / image_dir
         if not image_dir.exists():
             raise ValueError(f"Image directory {image_dir} doesn't exist")
 
@@ -94,7 +92,7 @@ class Mipnerf360(DataParser):
         image_filenames = sorted(image_filenames)
         num_images = len(image_filenames)
 
-        poses_data = np.load(abs_dir / "poses_bounds.npy")
+        poses_data = np.load(self.config.data_directory / "poses_bounds.npy")
         poses = poses_data[:, :-2].reshape([-1, 3, 5]).astype(np.float32)
         bounds = poses_data[:, -2:].transpose([1, 0])
 

nerfactory/datamanagers/dataparsers/nerfactory_parser.py

@@ -28,7 +28,7 @@ from nerfactory.cameras import utils as camera_utils
 from nerfactory.cameras.cameras import CAMERA_MODEL_TO_TYPE, Cameras, CameraType
 from nerfactory.datamanagers.dataparsers.base import DataParser, DataParserConfig
 from nerfactory.datamanagers.structs import DatasetInputs, SceneBounds
-from nerfactory.utils.io import get_absolute_path, load_from_json
+from nerfactory.utils.io import load_from_json
 
 
 @dataclass
@@ -60,9 +60,8 @@ class Nerfactory(DataParser):
 
     def _generate_dataset_inputs(self, split="train"):
         # pylint: disable=too-many-statements
-        abs_dir = get_absolute_path(self.config.data_directory)
 
-        meta = load_from_json(abs_dir / "transforms.json")
+        meta = load_from_json(self.config.data_directory / "transforms.json")
         image_filenames = []
         poses = []
         num_skipped_image_filenames = 0
@@ -72,9 +71,9 @@ class Nerfactory(DataParser):
             else:
                 filepath = Path(frame["file_path"])
             if self.config.downscale_factor > 1:
-                fname = abs_dir / f"images_{self.config.downscale_factor}" / filepath.name
+                fname = self.config.data_directory / f"images_{self.config.downscale_factor}" / filepath.name
             else:
-                fname = abs_dir / filepath
+                fname = self.config.data_directory / filepath
             if not fname:
                 num_skipped_image_filenames += 1
             else:

nerfactory/datamanagers/dataparsers/record3d_parser.py

@@ -28,7 +28,7 @@ from nerfactory.cameras.cameras import Cameras, CameraType
 from nerfactory.datamanagers.dataparsers.base import DataParser, DataParserConfig
 from nerfactory.datamanagers.structs import DatasetInputs, SceneBounds
 from nerfactory.utils import poses as pose_utils
-from nerfactory.utils.io import get_absolute_path, load_from_json
+from nerfactory.utils.io import load_from_json
 
 
 @dataclass
@@ -57,9 +57,7 @@ class Record3D(DataParser):
     config: Record3DDataParserConfig
 
     def _generate_dataset_inputs(self, split: str = "train") -> DatasetInputs:
-        abs_dir = get_absolute_path(self.config.data_directory)
-
-        image_dir = abs_dir / "rgb"
+        image_dir = self.config.data_directory / "rgb"
 
         if not image_dir.exists():
             raise ValueError(f"Image directory {image_dir} doesn't exist")
@@ -73,7 +71,7 @@ class Record3D(DataParser):
         image_filenames = np.array(image_filenames)
         num_images = len(image_filenames)
 
-        metadata_path = abs_dir / "metadata.json"
+        metadata_path = self.config.data_directory / "metadata.json"
         metadata_dict = load_from_json(metadata_path)
 
         poses_data = np.array(metadata_dict["poses"])

nerfactory/utils/io.py

@@ -16,11 +16,9 @@
 Input/output utils.
 """
 import json
-import logging
-import os
 import pickle
 from pathlib import Path
-from typing import Any, Tuple
+from typing import Any
 
 
 def load_from_json(filename: Path):
@@ -67,56 +65,3 @@ def write_to_pkl(filename: Path, content: Any):
     assert filename.suffix == ".pkl"
     with open(filename, "wb") as f:
         pickle.dump(content, f)
-
-
-def get_git_root(path: str, dirs: Tuple[str] = (".git",), default: str = "") -> str:
-    """Find the root of the git repository.
-    'https://stackoverflow.com/questions/22081209/find-the-root-of-the-git-repository-where-the-file-lives'
-
-    Args:
-        path: The path to start from.
-        dirs: The directories to look for.
-        default: The default value to return if no git root is found.
-
-    Returns:
-        The root of the git repository. Returns None if not found.
-    """
-    prev, test = None, os.path.abspath(path)
-    while prev != test:
-        if any(os.path.isdir(os.path.join(test, directory)) for directory in dirs):
-            return test
-        prev, test = test, os.path.abspath(os.path.join(test, os.pardir))
-    logging.info("Couldn't find git root")
-    return default
-
-
-def get_project_root(path: str) -> Path:
-    """Return the project root directory from an environment variable.
-    # TODO: handle this better and report user error
-
-    Args:
-        path: The path to start from.
-
-    Returns:
-        The project root directory.
-    """
-    project_root = os.getenv("PROJECT_ROOT")
-    if project_root is None:
-        logging.info(
-            "Please set PROJECT_ROOT to the root directory of this repo. "
-            "Going to try calling get_git_root(path) instead."
-        )
-        project_root = get_git_root(path)
-    return Path(project_root)
-
-
-def get_absolute_path(path, proj_root_func=get_project_root) -> Path:
-    """
-    Returns the full, absolute path.
-    Relative paths are assumed to start at the repo directory.
-    """
-    str_absolute_path = str(path)
-    if str_absolute_path == "" or str_absolute_path[0] == "/":
-        return path
-    absolute_path = proj_root_func(str_absolute_path) / path
-    return absolute_path