little updates -- added some pre-baked representations in init file

.gitignore

@@ -14,4 +14,5 @@ sanity_check.py
 commands.txt
 raw_data/npz_540p_2/
 here.csv
+*.ttf
 

dronescapes_reader/__init__.py

@@ -1,3 +1,13 @@
 """init file"""
 from .multitask_dataset import MultiTaskDataset
 from .dronescapes_representations import DepthRepresentation, OpticalFlowRepresentation, SemanticRepresentation
+
+_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]]
+dronescapes_task_types = { # some pre-baked representations
+    "depth_dpt": DepthRepresentation("depth_dpt", min_depth=0, max_depth=0.999),
+    "depth_sfm_manual202204": DepthRepresentation("depth_sfm_manual202204", min_depth=0, max_depth=300),
+    "opticalflow_rife": OpticalFlowRepresentation,
+    "semantic_segprop8": SemanticRepresentation("semantic_segprop8", classes=8, color_map=_color_map),
+    "semantic_mask2former_swin_mapillary_converted":
+        SemanticRepresentation("semantic_mask2former_swin_mapillary_converted", classes=8, color_map=_color_map)}

dronescapes_reader/multitask_dataset.py

@@ -2,7 +2,7 @@
 """MultiTask Dataset module compatible with torch.utils.data.Dataset & DataLoader."""
 from __future__ import annotations
 from pathlib import Path
-from argparse import Namespace, ArgumentParser
+from argparse import ArgumentParser
 from pprint import pprint
 from natsort import natsorted
 from loguru import logger
@@ -113,8 +113,10 @@ class MultiTaskDataset(Dataset):
         self._tasks = []
         for task_name in self.task_names:
             t = self.task_types[task_name]
-            if not isinstance(t, NpzRepresentation):
+            try:
                 t = t(task_name)
+            except Exception:
+                pass
             self._tasks.append(t)
         assert all(t.name == t_n for t, t_n in zip(self._tasks, self.task_names)), (self._task_names, self._tasks)
         return self._tasks
@@ -175,7 +177,6 @@ class MultiTaskDataset(Dataset):
         logger.info(f"Found {len(all_files)} data points as union of all nodes' data ({len(nodes)} nodes).")
 
         files_per_repr = {node: [] for node in nodes}
-        in_file_names = {node: [f.name for f in in_files[node]] for node in nodes}
         for node in nodes:
             for file_name in all_files:
                 file_path = name_to_node_path[node].get(file_name, None)

scripts/dronescapes_viewer.py

@@ -2,23 +2,13 @@
 import sys
 from pathlib import Path
 sys.path.append(Path(__file__).parents[1].__str__())
-from functools import partial
-from dronescapes_reader import MultiTaskDataset, DepthRepresentation, OpticalFlowRepresentation, SemanticRepresentation
+from dronescapes_reader import MultiTaskDataset, dronescapes_task_types
 from pprint import pprint
 from torch.utils.data import DataLoader
 import random
 
 def main():
-    sema_repr = partial(SemanticRepresentation, classes=8, 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]])
-    reader = MultiTaskDataset(sys.argv[1], handle_missing_data="fill_none",
-                              task_types={"depth_dpt": DepthRepresentation("depth_dpt", min_depth=0, max_depth=0.999),
-                                          "depth_sfm_manual202204": DepthRepresentation("depth_sfm_manual202204",
-                                                                                        min_depth=0, max_depth=300),
-                                          "opticalflow_rife": OpticalFlowRepresentation,
-                                          "semantic_segprop8": sema_repr,
-                                          "semantic_mask2former_swin_mapillary_converted": sema_repr})
+    reader = MultiTaskDataset(sys.argv[1], handle_missing_data="fill_none", task_types=dronescapes_task_types)
     print(reader)
 
     print("== Shapes ==")