updates to these

scripts/dronescapes_viewer/dronescapes_representations.py

@@ -1,26 +1,26 @@
 import sys
 from pathlib import Path
-from vre.representations.cv_representations import (
-    DepthRepresentation, NormalsRepresentation, SemanticRepresentation, ColorRepresentation, HSVRepresentation,
-    EdgesRepresentation, OpticalFlowRepresentation)
+from vre.representations.cv_representations import (DepthRepresentation, NormalsRepresentation, ColorRepresentation,
+                                                    HSVRepresentation, EdgesRepresentation, OpticalFlowRepresentation)
+from vre.representations.semantic_segmentation import SemanticRepresentation
 from vre.representations import Representation
-sys.path.append(str(Path(__file__).parents[1] / "semantic_mapper"))
-from semantic_mapper import (
-    get_new_semantic_mapped_tasks, m2f_mapillary, m2f_coco, m2f_r50_mapillary,
-    BinaryMapper, mapillary_classes, coco_classes)
 
 def get_gt_tasks() -> dict[str, Representation]:
     color_map = [[0, 255, 0], [0, 127, 0], [255, 255, 0], [255, 255, 255],
                 [255, 0, 0], [0, 0, 255], [0, 255, 255], [127, 127, 63]]
     classes_8 = ["land", "forest", "residential", "road", "little-objects", "water", "sky", "hill"]
     tasks = [
-        SemanticRepresentation("semantic_segprop8", classes=classes_8, color_map=color_map),
-        DepthRepresentation("depth_sfm_manual202204", min_depth=0, max_depth=300),
-        NormalsRepresentation("camera_normals_sfm_manual202204"),
+        SemanticRepresentation("semantic_output", classes=classes_8, color_map=color_map),
+        DepthRepresentation("depth_output", min_depth=0, max_depth=300),
+        NormalsRepresentation("camera_normals_output"),
     ]
     return {t.name: t for t in tasks}
 
 def get_other_tasks(include_semantics_original: bool, include_ci: bool) -> dict[str, Representation]:
+    sys.path.append(str(Path(__file__).parents[1] / "semantic_mapper"))
+    from semantic_mapper import (
+        m2f_mapillary, m2f_coco, m2f_r50_mapillary,
+        BinaryMapper, mapillary_classes, coco_classes)
     tasks = [
         rgb := ColorRepresentation("rgb"),
         OpticalFlowRepresentation("opticalflow_rife"),
@@ -61,6 +61,8 @@ def get_other_tasks(include_semantics_original: bool, include_ci: bool) -> dict[
 
 def get_dronescapes_task_types(include_semantics_original: bool, include_gt: bool,
                                include_ci: bool) -> dict[str, Representation]:
+    sys.path.append(str(Path(__file__).parents[1] / "semantic_mapper"))
+    from semantic_mapper import get_new_semantic_mapped_tasks
     res = {
         **get_new_semantic_mapped_tasks(),
         **get_other_tasks(include_semantics_original, include_ci),

scripts/semantic_mapper/semantic_mapper.py

@@ -300,7 +300,8 @@ class SemanticMedian(TaskMapper, NpIORepresentation):
 
     @overrides
     def make_images(self, data: ReprOut) -> np.ndarray:
-        return colorize_semantic_segmentation(data.output.argmax(-1), self.classes, self.color_map)
+        data_output = data.output.argmax(-1) if np.issubdtype(data.output.dtype, np.floating) else data.output
+        return colorize_semantic_segmentation(data_output, self.classes, self.color_map)
 
 class SafeLandingAreas(BinaryMapper, NpIORepresentation):
     def __init__(self, name: str, depth: DepthRepresentation, camera_normals: NormalsRepresentation,

vre_dronescapes/.gitignore

@@ -1,4 +1,5 @@
 *.npz
 .logs/
 .collage/
+collages/