Merge branch '210-rename_dichotomy' into 'release'

refact: rename dichotomy in dichotomy_python See merge request 3d/PandoraBox/pandora2d!167
CNES · Oct 26, 2024 · 347e73b · 347e73b
2 parents 20237a3 + 9934b99
commit 347e73b
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diff --git a/data_samples/json_conf_files/a_dichotomy_pipeline.json b/data_samples/json_conf_files/a_dichotomy_pipeline.json
@@ -22,7 +22,7 @@
         "invalid_disparity": "NaN"
       },
       "refinement": {
-        "refinement_method": "dichotomy",
+        "refinement_method": "dichotomy_python",
         "iterations": 2,
         "filter": { "method": "bicubic"}
       }

diff --git a/docs/source/exploring_the_field/refining_disparity.rst b/docs/source/exploring_the_field/refining_disparity.rst
@@ -6,11 +6,11 @@ The purpose of this step is to refine the disparity identified in the previous s
 So, the refinement step involves transforming a pixel disparity map into a sub-pixel disparity map.
 
 
-Two methods are available in pandora2d:
+Three methods are available in pandora2d:
 
 - Interpolation
 - Optical flow
-- Dichotomy
+- Dichotomy (python version)
 
 .. warning::
     The optical flow method is still in an experimental phase.

diff --git a/docs/source/userguide/step_by_step/refinement.rst b/docs/source/userguide/step_by_step/refinement.rst
@@ -214,7 +214,7 @@ Configuration and parameters
                       - Refinement method
                       - string
                       -
-                      - "dichotomy"
+                      - "dichotomy_python"
                       - Yes
                     * - *iterations*
                       - Number of iterations

diff --git a/notebooks/usage_dichotomy.ipynb b/notebooks/usage_dichotomy.ipynb
@@ -292,7 +292,7 @@
    "source": [
     "user_cfg_with_refinement = deepcopy(user_cfg)\n",
     "user_cfg_with_refinement[\"pipeline\"][\"refinement\"] = {\n",
-    "    \"refinement_method\": \"dichotomy\",\n",
+    "    \"refinement_method\": \"dichotomy_python\",\n",
     "    \"iterations\": 1,\n",
     "    \"filter\": {\"method\": \"bicubic\"},\n",
     "}"
@@ -307,7 +307,7 @@
    "source": [
     "user_cfg_with_two_refinements = deepcopy(user_cfg)\n",
     "user_cfg_with_two_refinements[\"pipeline\"][\"refinement\"] = {\n",
-    "    \"refinement_method\": \"dichotomy\",\n",
+    "    \"refinement_method\": \"dichotomy_python\",\n",
     "    \"iterations\": 2,\n",
     "    \"filter\": {\"method\": \"bicubic\"},\n",
     "}"
@@ -570,7 +570,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

diff --git a/pandora2d/refinement/dichotomy.py b/pandora2d/refinement/dichotomy.py
@@ -17,7 +17,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """
-Module for Dichotomy refinement method.
+Module for Dichotomy refinement method (python version).
 """
 
 import logging
@@ -34,13 +34,13 @@
 COST_SELECTION_METHOD_MAPPING = {"min": np.nanargmin, "max": np.nanargmax}
 
 
-@refinement.AbstractRefinement.register_subclass("dichotomy")
-class Dichotomy(refinement.AbstractRefinement):
-    """Subpixel refinement method by dichotomy."""
+@refinement.AbstractRefinement.register_subclass("dichotomy_python")
+class DichotomyPython(refinement.AbstractRefinement):
+    """Subpixel refinement method by dichotomy (python version)."""
 
     NB_MAX_ITER = 9
     schema = {
-        "refinement_method": And(str, lambda x: x in ["dichotomy"]),
+        "refinement_method": And(str, lambda x: x in ["dichotomy_python"]),
         "iterations": And(int, lambda it: it > 0),
         "filter": And(dict, lambda x: x["method"] in AbstractFilter.interpolation_filter_methods_avail),
     }

diff --git a/tests/functional_tests/README.md b/tests/functional_tests/README.md
@@ -77,19 +77,19 @@ Selecting the best similarity score, for the moment there is only the WTA method
 ## Refinement
 Accurate the disparity to smooth outliers. The algorithms tested here are:
 
-+-----------+-----------------------+
-| Algorithm | Description           |
-+-----------+-----------------------+
-| fo        | Optical flow          |
-+-----------+-----------------------+
-| dichotomy | Reseach by dichotomy  |
-+-----------+-----------------------+
-| bicubic   | Bicubic interpolation |
-+-----------+-----------------------+
-| sinc      | Sinux cardinal        |
-+-----------+-----------------------+
-| spline    | Spline                |
-+-----------+-----------------------+
++-----------+-----------------------------------------+
+| Algorithm | Description                             |
++-----------+-----------------------------------------+
+| fo        | Optical flow                            |
++-----------+-----------------------------------------+
+| dichotomy_python | Reseach by dichotomy with python |
++-----------+-----------------------------------------+
+| bicubic   | Bicubic interpolation                   |
++-----------+-----------------------------------------+
+| sinc      | Sinux cardinal                          |
++-----------+-----------------------------------------+
+| spline    | Spline                                  |
++-----------+-----------------------------------------+
 
 ## Validation
 A criterion that gives the user additional confidence in the result. The algorithms tested here are:

diff --git a/tests/functional_tests/conftest.py b/tests/functional_tests/conftest.py
@@ -38,6 +38,6 @@ def correct_pipeline_with_dichotomy():
         "pipeline": {
             "matching_cost": {"matching_cost_method": "zncc", "window_size": 5},
             "disparity": {"disparity_method": "wta", "invalid_disparity": -99},
-            "refinement": {"refinement_method": "dichotomy", "iterations": 2, "filter": {"method": "bicubic"}},
+            "refinement": {"refinement_method": "dichotomy_python", "iterations": 2, "filter": {"method": "bicubic"}},
         }
     }
diff --git a/tests/functional_tests/matching_cost/test_disparity_margins.py b/tests/functional_tests/matching_cost/test_disparity_margins.py
@@ -96,11 +96,11 @@ def config(self, subpix, refinement_config, matching_cost_method):
         [
             pytest.param(
                 1,
-                {"refinement_method": "dichotomy", "iterations": 1, "filter": {"method": "bicubic"}},
+                {"refinement_method": "dichotomy_python", "iterations": 1, "filter": {"method": "bicubic"}},
                 (10, 10, 8, 6),
                 [0, 1, 2, 3, 4, 5],
                 [-3, -2, -1, 0, 1, 2, 3, 4],
-                id="Subpix=1 and refinement_method=dichotomy",
+                id="Subpix=1 and refinement_method=dichotomy_python",
             ),
             pytest.param(
                 1,
@@ -124,11 +124,11 @@ def config(self, subpix, refinement_config, matching_cost_method):
             ),
             pytest.param(
                 2,
-                {"refinement_method": "dichotomy", "iterations": 1, "filter": {"method": "bicubic"}},
+                {"refinement_method": "dichotomy_python", "iterations": 1, "filter": {"method": "bicubic"}},
                 (10, 10, 15, 11),
                 [0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5],
                 [-3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4],
-                id="Subpix=2 and refinement_method=dichotomy",
+                id="Subpix=2 and refinement_method=dichotomy_python",
             ),
             pytest.param(
                 2,
@@ -152,11 +152,11 @@ def config(self, subpix, refinement_config, matching_cost_method):
             ),
             pytest.param(
                 4,
-                {"refinement_method": "dichotomy", "iterations": 1, "filter": {"method": "bicubic"}},
+                {"refinement_method": "dichotomy_python", "iterations": 1, "filter": {"method": "bicubic"}},
                 (10, 10, 29, 21),
                 np.arange(0, 5.25, 0.25),
                 np.arange(-3, 4.25, 0.25),
-                id="Subpix=4 and refinement_method=dichotomy",
+                id="Subpix=4 and refinement_method=dichotomy_python",
             ),
             pytest.param(
                 4,

diff --git a/tests/functional_tests/refinement/dichotomy/test_dichotomy_pipeline.py b/tests/functional_tests/refinement/dichotomy/test_dichotomy_pipeline.py
@@ -34,7 +34,7 @@
 
 
 @pytest.fixture()
-def make_cfg_for_dichotomy(  # pylint: disable=too-many-arguments
+def make_cfg_for_dichotomy_python(  # pylint: disable=too-many-arguments
     left_img_path,
     right_img_path,
     method,
@@ -75,7 +75,7 @@ def make_cfg_for_dichotomy(  # pylint: disable=too-many-arguments
                 "invalid_disparity": -9999,
             },
             "refinement": {
-                "refinement_method": "dichotomy",
+                "refinement_method": "dichotomy_python",
                 "iterations": iterations,
                 "filter": {"method": method},
             },
@@ -92,7 +92,7 @@ def make_cfg_for_dichotomy(  # pylint: disable=too-many-arguments
 @pytest.mark.parametrize("roi", [{"col": {"first": 100, "last": 120}, "row": {"first": 100, "last": 120}}])
 @pytest.mark.parametrize("col_disparity", [{"init": 0, "range": 1}])
 @pytest.mark.parametrize("row_disparity", [{"init": 0, "range": 3}])
-def test_dichotomy_execution(make_cfg_for_dichotomy):
+def test_dichotomy_execution(make_cfg_for_dichotomy_python):
     """
     Description : Test that execution of Pandora2d with a dichotomy refinement does not fail.
     Data :
@@ -104,7 +104,7 @@ def test_dichotomy_execution(make_cfg_for_dichotomy):
     """
     pandora2d_machine = Pandora2DMachine()
 
-    cfg = check_conf(make_cfg_for_dichotomy, pandora2d_machine)
+    cfg = check_conf(make_cfg_for_dichotomy_python, pandora2d_machine)
 
     cfg["ROI"]["margins"] = pandora2d_machine.margins_img.global_margins.astuple()
     roi = get_roi_processing(cfg["ROI"], cfg["input"]["col_disparity"], cfg["input"]["row_disparity"])
@@ -131,7 +131,7 @@ def test_dichotomy_execution(make_cfg_for_dichotomy):
 # this type of disparity will also need to be tested here.
 @pytest.mark.parametrize("col_disparity", [{"init": -1, "range": 1}])
 @pytest.mark.parametrize("row_disparity", [{"init": 0, "range": 1}])
-def test_extrema_disparities_not_processed(make_cfg_for_dichotomy):
+def test_extrema_disparities_not_processed(make_cfg_for_dichotomy_python):
     """
     Description : Test that execution of Pandora2d with a dichotomy refinement does not
     take into account points for which best cost value is found at the edge of the disparity range.
@@ -141,7 +141,7 @@ def test_extrema_disparities_not_processed(make_cfg_for_dichotomy):
     """
     pandora2d_machine = pandora2d.state_machine.Pandora2DMachine()
 
-    cfg = check_conf(make_cfg_for_dichotomy, pandora2d_machine)
+    cfg = check_conf(make_cfg_for_dichotomy_python, pandora2d_machine)
 
     cfg["ROI"]["margins"] = pandora2d_machine.margins_img.global_margins.astuple()
     roi = get_roi_processing(cfg["ROI"], cfg["input"]["col_disparity"], cfg["input"]["row_disparity"])

diff --git a/tests/performance_tests/refinement/dichotomy/test_dichotomy_performance.py b/tests/performance_tests/refinement/dichotomy/test_dichotomy_performance.py
@@ -103,7 +103,11 @@ def cfg_dichotomy(self, shift_path, subpix, filter_method):
                     "spline_order": 3,
                 },  # we use spline_order=3 to get better results when subpix is different from 1
                 "disparity": {"disparity_method": "wta", "invalid_disparity": np.nan},
-                "refinement": {"refinement_method": "dichotomy", "iterations": 9, "filter": {"method": filter_method}},
+                "refinement": {
+                    "refinement_method": "dichotomy_python",
+                    "iterations": 9,
+                    "filter": {"method": filter_method},
+                },
             },
         }
 

diff --git a/tests/resource_tests/test_pandora2d.py b/tests/resource_tests/test_pandora2d.py
@@ -117,7 +117,7 @@ def dichotomy_pipeline(self, matching_cost_method, subpix, iterations, filter_me
             "matching_cost": {"matching_cost_method": matching_cost_method, "subpix": subpix},
             "disparity": {"disparity_method": "wta", "invalid_disparity": -99},
             "refinement": {
-                "refinement_method": "dichotomy",
+                "refinement_method": "dichotomy_python",
                 "iterations": iterations,
                 "filter": {"method": filter_method},
             },

diff --git a/tests/unit_tests/test_pandora2d.py b/tests/unit_tests/test_pandora2d.py
@@ -85,7 +85,7 @@ def test_run_prepare(left_img_path, right_img_path) -> None:
         [
             pytest.param({"refinement_method": "interpolation"}, Margins(3, 3, 3, 3), id="interpolation"),
             pytest.param(
-                {"refinement_method": "dichotomy", "iterations": 3, "filter": {"method": "bicubic"}},
+                {"refinement_method": "dichotomy_python", "iterations": 3, "filter": {"method": "bicubic"}},
                 Margins(1, 1, 2, 2),
                 id="dichotomy with bicubic filter",
             ),