Fix import errors, add solution for TLS issue on older systems

README.md

@@ -19,6 +19,23 @@ conda install -c conda-forge --strict-channel-priority xdem
 ```
 The `--strict-channel-priority` flag seems essential for Windows installs to function correctly, and is recommended for UNIX-based systems as well.
 
+Solving dependencies can take a long time with `conda`. To speed up this, consider installing `mamba`:
+
+```bash
+conda install mamba -n base -c conda-forge
+```
+
+Once installed, the same commands can be run by simply replacing `conda` by `mamba`. More details available through the [mamba project](https://github.com/mamba-org/mamba).
+
+If running into the `sklearn` error `ImportError: dlopen: cannot load any more object with static TLS`, your system 
+needs to update its `glibc` (see details [here](https://github.com/scikit-learn/scikit-learn/issues/14485#issuecomment-822678559)).
+If you have no administrator right on the system, you might be able to circumvent this issue by installing a working 
+environment with specific downgraded versions of `scikit-learn` and `numpy`:
+```bash
+conda create -n xdem-env -c conda-forge xdem scikit-learn==0.20.3 numpy==1.19.*
+```
+On very old systems, if the above install results in segmentation faults, try setting more specifically 
+`numpy==1.19.2=py37h54aff64_0` (worked with Debian 8.11, GLIBC 2.19).
 
 ### Installing with pip
 **NOTE**: Setting up GDAL and PROJ may need some extra steps, depending on your operating system and configuration.

xdem/coreg.py

@@ -11,6 +11,11 @@
 from enum import Enum
 from typing import Any, Callable, Optional, overload, Union, Sequence, TypeVar
 
+try:
+    import cv2
+    _has_cv2 = True
+except ImportError:
+    _has_cv2 = False
 import fiona
 import geoutils as gu
 from geoutils.georaster import RasterType
@@ -35,12 +40,6 @@
 except ImportError:
     _has_rd = False
 
-try:
-    import cv2
-    _has_cv2 = True
-except ImportError:
-    _has_cv2 = False
-
 try:
     from pytransform3d.transform_manager import TransformManager
     import pytransform3d.transformations
@@ -917,9 +916,11 @@ def __init__(self, max_iterations=100, tolerance=0.05, rejection_scale=2.5, num_
     def _fit_func(self, ref_dem: np.ndarray, tba_dem: np.ndarray, transform: Optional[rio.transform.Affine],
                   weights: Optional[np.ndarray], verbose: bool = False):
         """Estimate the rigid transform from tba_dem to ref_dem."""
+
         if weights is not None:
             warnings.warn("ICP was given weights, but does not support it.")
 
+
         bounds, resolution = _transform_to_bounds_and_res(ref_dem.shape, transform)
         points: dict[str, np.ndarray] = {}
         # Generate the x and y coordinates for the reference_dem
@@ -1392,6 +1393,10 @@ def apply_matrix(dem: np.ndarray, transform: rio.transform.Affine, matrix: np.nd
     if np.mean(np.abs(empty_matrix - matrix)) == 0.0:
         return demc + matrix[2, 3]
 
+    # Opencv is required down from here
+    if not _has_cv2:
+        raise ValueError("Optional dependency needed. Install 'opencv'")
+
     nan_mask = xdem.spatial_tools.get_mask(dem)
     assert np.count_nonzero(~nan_mask) > 0, "Given DEM had all nans."
     # Create a filled version of the DEM. (skimage doesn't like nans)

xdem/misc.py

@@ -5,7 +5,12 @@
 import warnings
 from typing import Any, Callable
 
-import cv2
+try:
+    import cv2
+    _has_cv2 = True
+except ImportError:
+    _has_cv2 = False
+
 import numpy as np
 
 import xdem.version
@@ -28,6 +33,10 @@ def generate_random_field(shape: tuple[int, int], corr_size: int) -> np.ndarray:
 
     :returns: A numpy array of semi-random values from 0 to 1
     """
+
+    if not _has_cv2:
+        raise ValueError("Optional dependency needed. Install 'opencv'")
+
     field = cv2.resize(
         cv2.GaussianBlur(
             np.repeat(