Merge branch '835-le-reechantillonnage-de-la-classification-est-gourm…

…and-en-temps-et-memoire-et-provoque-des' into 'master'

Resolve "Le rééchantillonnage de la classification est gourmand en temps et mémoire et provoque des freeze"

Closes #835

See merge request 3d/cars-park/cars!744

cars/applications/resampling/bicubic_resampling.py

@@ -213,7 +213,7 @@ def pre_run(
             largest_epipolar_region,
         )
 
-    def run(
+    def run(  # noqa: C901
         self,
         sensor_image_left,
         sensor_image_right,
@@ -226,8 +226,9 @@ def run(
         tile_width=None,
         tile_height=None,
         add_color=True,
+        add_classif=True,
         epipolar_roi=None,
-    ):  # noqa: C901
+    ):
         """
         Run resampling application.
 
@@ -276,6 +277,8 @@ def run(
         :type tile_height: int
         :param add_color: add color image to dataset
         :type add_color: bool
+        :param add_classif: add classif to dataset
+        :type add_classif: bool
         :param epipolar_roi: Epipolar roi to use if set.
             Set None tiles outsize roi
         :type epipolar_roi: list(int), [row_min, row_max,  col_min, col_max]
@@ -437,6 +440,15 @@ def margins_fun(  # pylint: disable=unused-argument
                 dtype=np.uint8,
             )
 
+            self.orchestrator.add_to_save_lists(
+                os.path.join(pair_folder, "epi_img_right_mask.tif"),
+                cst.EPI_MSK,
+                epipolar_images_right,
+                cars_ds_name="epi_img_right_mask",
+                dtype=np.uint8,
+            )
+
+        if self.save_intermediate_data and add_classif:
             self.orchestrator.add_to_save_lists(
                 os.path.join(pair_folder, "epi_img_left_classif.tif"),
                 cst.EPI_CLASSIFICATION,
@@ -446,14 +458,6 @@ def margins_fun(  # pylint: disable=unused-argument
                 optional_data=True,
             )
 
-            self.orchestrator.add_to_save_lists(
-                os.path.join(pair_folder, "epi_img_right_mask.tif"),
-                cst.EPI_MSK,
-                epipolar_images_right,
-                cars_ds_name="epi_img_right_mask",
-                dtype=np.uint8,
-            )
-
             self.orchestrator.add_to_save_lists(
                 os.path.join(pair_folder, "epi_img_right_classif.tif"),
                 cst.EPI_CLASSIFICATION,
@@ -610,6 +614,7 @@ def margins_fun(  # pylint: disable=unused-argument
                         used_disp_min=used_disp_min[row, col],
                         used_disp_max=used_disp_max[row, col],
                         add_color=add_color,
+                        add_classif=add_classif,
                         color1=color1,
                         mask1=mask1,
                         mask2=mask2,
@@ -647,6 +652,7 @@ def generate_epipolar_images_wrapper(
     used_disp_min=None,
     used_disp_max=None,
     add_color=True,
+    add_classif=True,
     color1=None,
     mask1=None,
     mask2=None,
@@ -719,6 +725,7 @@ def generate_epipolar_images_wrapper(
         nodata1=nodata1,
         nodata2=nodata2,
         add_color=add_color,
+        add_classif=add_classif,
     )
 
     if add_color:
@@ -753,22 +760,24 @@ def generate_epipolar_images_wrapper(
         left_dataset[cst.EPI_IMAGE].attrs["color_type"] = color_types
 
     # Add classification layers to dataset
-    if left_classif_dataset:
-        left_dataset.coords[cst.BAND_CLASSIF] = left_classif_dataset.attrs[
-            cst.BAND_NAMES
-        ]
-        left_dataset[cst.EPI_CLASSIFICATION] = xr.DataArray(
-            left_classif_dataset[cst.EPI_IMAGE].values,
-            dims=[cst.BAND_CLASSIF, cst.ROW, cst.COL],
-        ).astype(bool)
-    if right_classif_dataset:
-        right_dataset.coords[cst.BAND_CLASSIF] = right_classif_dataset.attrs[
-            cst.BAND_NAMES
-        ]
-        right_dataset[cst.EPI_CLASSIFICATION] = xr.DataArray(
-            right_classif_dataset[cst.EPI_IMAGE].values,
-            dims=[cst.BAND_CLASSIF, cst.ROW, cst.COL],
-        ).astype(bool)
+    if add_classif:
+        if left_classif_dataset:
+            left_dataset.coords[cst.BAND_CLASSIF] = left_classif_dataset.attrs[
+                cst.BAND_NAMES
+            ]
+            left_dataset[cst.EPI_CLASSIFICATION] = xr.DataArray(
+                left_classif_dataset[cst.EPI_IMAGE].values,
+                dims=[cst.BAND_CLASSIF, cst.ROW, cst.COL],
+            ).astype(bool)
+        if right_classif_dataset:
+            right_dataset.coords[cst.BAND_CLASSIF] = (
+                right_classif_dataset.attrs[cst.BAND_NAMES]
+            )
+            right_dataset[cst.EPI_CLASSIFICATION] = xr.DataArray(
+                right_classif_dataset[cst.EPI_IMAGE].values,
+                dims=[cst.BAND_CLASSIF, cst.ROW, cst.COL],
+            ).astype(bool)
+
     # Add attributes info
     attributes = {}
     # fill datasets with saving info, window, profile, overlaps for correct

cars/applications/resampling/resampling.py

@@ -109,6 +109,7 @@ def run(
         tile_height=None,
         step=None,
         add_color=True,
+        add_classif=True,
         epipolar_roi=None,
     ):  # noqa: C901
         """

cars/applications/resampling/resampling_tools.py

@@ -63,6 +63,7 @@ def epipolar_rectify_images(
     nodata1=0,
     nodata2=0,
     add_color=True,
+    add_classif=True,
 ):
     """
     Resample left and right images, with color on left
@@ -184,28 +185,29 @@ def epipolar_rectify_images(
 
     # resample the mask images
     left_classif_dataset = None
-    if classif1:
-        left_classif_dataset = resample_image(
-            classif1,
-            grid1,
-            [epipolar_size_x, epipolar_size_y],
-            region=left_region,
-            band_coords=cst.BAND_CLASSIF,
-            interpolator_img=interpolator_classif,
-            interpolator_mask=interpolator_mask,
-        )
-
     right_classif_dataset = None
-    if classif2:
-        right_classif_dataset = resample_image(
-            classif2,
-            grid2,
-            [epipolar_size_x, epipolar_size_y],
-            region=right_region,
-            band_coords=cst.BAND_CLASSIF,
-            interpolator_img=interpolator_classif,
-            interpolator_mask=interpolator_mask,
-        )
+    if add_classif:
+        if classif1:
+            left_classif_dataset = resample_image(
+                classif1,
+                grid1,
+                [epipolar_size_x, epipolar_size_y],
+                region=left_region,
+                band_coords=cst.BAND_CLASSIF,
+                interpolator_img=interpolator_classif,
+                interpolator_mask=interpolator_mask,
+            )
+
+        if classif2:
+            right_classif_dataset = resample_image(
+                classif2,
+                grid2,
+                [epipolar_size_x, epipolar_size_y],
+                region=right_region,
+                band_coords=cst.BAND_CLASSIF,
+                interpolator_img=interpolator_classif,
+                interpolator_mask=interpolator_mask,
+            )
 
     return (
         left_dataset,

cars/pipelines/sensor_to_dense_dsm/sensor_to_dense_dsm_pipeline.py

@@ -673,6 +673,7 @@ def run(self):  # noqa C901
                 # with any order. the .1 will be performed before the .2
                 pairs[pair_key]["holes_classif"] = []
                 pairs[pair_key]["holes_poly_margin"] = 0
+                add_classif = False
                 if self.dense_matches_filling_1.used_method == "plane":
                     pairs[pair_key][
                         "holes_classif"
@@ -681,6 +682,7 @@ def run(self):  # noqa C901
                         pairs[pair_key]["holes_poly_margin"],
                         self.dense_matches_filling_1.get_poly_margin(),
                     )
+                    add_classif = True
                 if self.dense_matches_filling_2.used_method == "plane":
                     pairs[pair_key][
                         "holes_classif"
@@ -689,6 +691,7 @@ def run(self):  # noqa C901
                         pairs[pair_key]["holes_poly_margin"],
                         self.dense_matches_filling_2.get_poly_margin(),
                     )
+                    add_classif = True
 
                 pairs[pair_key]["holes_bbox_left"] = []
                 pairs[pair_key]["holes_bbox_right"] = []
@@ -717,6 +720,7 @@ def run(self):  # noqa C901
                         tile_width=None,
                         tile_height=None,
                         add_color=False,
+                        add_classif=add_classif,
                     )
 
                     # Generate the holes polygons in epipolar images
@@ -1233,6 +1237,7 @@ def run(self):  # noqa C901
                     tile_width=optimum_tile_size,
                     tile_height=optimum_tile_size,
                     add_color=True,
+                    add_classif=True,
                     epipolar_roi=epipolar_roi,
                 )
 

cars/pipelines/sensor_to_sparse_dsm/sensor_to_sparse_dsm_pipeline.py

@@ -370,6 +370,7 @@ def run(self):
                     tile_width=None,
                     tile_height=None,
                     add_color=False,
+                    add_classif=False,
                 )
 
                 # Run epipolar sparse_matching application