little updates -- added some pre-baked representations in init file
Browse files- .gitignore +1 -0
- dronescapes_reader/__init__.py +10 -0
- dronescapes_reader/multitask_dataset.py +4 -3
- scripts/dronescapes_viewer.ipynb +0 -0
- scripts/dronescapes_viewer.py +2 -12
.gitignore
CHANGED
@@ -14,4 +14,5 @@ sanity_check.py
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commands.txt
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raw_data/npz_540p_2/
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here.csv
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commands.txt
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raw_data/npz_540p_2/
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here.csv
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*.ttf
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dronescapes_reader/__init__.py
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@@ -1,3 +1,13 @@
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"""init file"""
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from .multitask_dataset import MultiTaskDataset
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from .dronescapes_representations import DepthRepresentation, OpticalFlowRepresentation, SemanticRepresentation
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"""init file"""
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from .multitask_dataset import MultiTaskDataset
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from .dronescapes_representations import DepthRepresentation, OpticalFlowRepresentation, SemanticRepresentation
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_color_map=[[0, 255, 0], [0, 127, 0], [255, 255, 0], [255, 255, 255],
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[255, 0, 0], [0, 0, 255], [0, 255, 255], [127, 127, 63]]
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dronescapes_task_types = { # some pre-baked representations
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"depth_dpt": DepthRepresentation("depth_dpt", min_depth=0, max_depth=0.999),
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"depth_sfm_manual202204": DepthRepresentation("depth_sfm_manual202204", min_depth=0, max_depth=300),
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"opticalflow_rife": OpticalFlowRepresentation,
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"semantic_segprop8": SemanticRepresentation("semantic_segprop8", classes=8, color_map=_color_map),
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"semantic_mask2former_swin_mapillary_converted":
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SemanticRepresentation("semantic_mask2former_swin_mapillary_converted", classes=8, color_map=_color_map)}
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dronescapes_reader/multitask_dataset.py
CHANGED
@@ -2,7 +2,7 @@
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"""MultiTask Dataset module compatible with torch.utils.data.Dataset & DataLoader."""
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from __future__ import annotations
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from pathlib import Path
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from argparse import
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from pprint import pprint
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from natsort import natsorted
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from loguru import logger
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@@ -113,8 +113,10 @@ class MultiTaskDataset(Dataset):
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self._tasks = []
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for task_name in self.task_names:
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t = self.task_types[task_name]
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-
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t = t(task_name)
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self._tasks.append(t)
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assert all(t.name == t_n for t, t_n in zip(self._tasks, self.task_names)), (self._task_names, self._tasks)
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return self._tasks
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@@ -175,7 +177,6 @@ class MultiTaskDataset(Dataset):
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logger.info(f"Found {len(all_files)} data points as union of all nodes' data ({len(nodes)} nodes).")
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files_per_repr = {node: [] for node in nodes}
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in_file_names = {node: [f.name for f in in_files[node]] for node in nodes}
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for node in nodes:
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for file_name in all_files:
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file_path = name_to_node_path[node].get(file_name, None)
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"""MultiTask Dataset module compatible with torch.utils.data.Dataset & DataLoader."""
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from __future__ import annotations
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from pathlib import Path
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from argparse import ArgumentParser
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from pprint import pprint
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from natsort import natsorted
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from loguru import logger
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self._tasks = []
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for task_name in self.task_names:
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t = self.task_types[task_name]
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try:
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t = t(task_name)
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except Exception:
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pass
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self._tasks.append(t)
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assert all(t.name == t_n for t, t_n in zip(self._tasks, self.task_names)), (self._task_names, self._tasks)
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return self._tasks
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logger.info(f"Found {len(all_files)} data points as union of all nodes' data ({len(nodes)} nodes).")
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files_per_repr = {node: [] for node in nodes}
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for node in nodes:
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for file_name in all_files:
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file_path = name_to_node_path[node].get(file_name, None)
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scripts/dronescapes_viewer.ipynb
CHANGED
The diff for this file is too large to render.
See raw diff
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scripts/dronescapes_viewer.py
CHANGED
@@ -2,23 +2,13 @@
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import sys
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from pathlib import Path
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sys.path.append(Path(__file__).parents[1].__str__())
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from
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from dronescapes_reader import MultiTaskDataset, DepthRepresentation, OpticalFlowRepresentation, SemanticRepresentation
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from pprint import pprint
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from torch.utils.data import DataLoader
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import random
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def main():
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[255, 255, 255], [255, 0, 0], [0, 0, 255],
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[0, 255, 255], [127, 127, 63]])
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reader = MultiTaskDataset(sys.argv[1], handle_missing_data="fill_none",
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task_types={"depth_dpt": DepthRepresentation("depth_dpt", min_depth=0, max_depth=0.999),
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"depth_sfm_manual202204": DepthRepresentation("depth_sfm_manual202204",
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min_depth=0, max_depth=300),
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"opticalflow_rife": OpticalFlowRepresentation,
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"semantic_segprop8": sema_repr,
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"semantic_mask2former_swin_mapillary_converted": sema_repr})
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print(reader)
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print("== Shapes ==")
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import sys
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from pathlib import Path
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sys.path.append(Path(__file__).parents[1].__str__())
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from dronescapes_reader import MultiTaskDataset, dronescapes_task_types
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from pprint import pprint
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from torch.utils.data import DataLoader
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import random
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def main():
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reader = MultiTaskDataset(sys.argv[1], handle_missing_data="fill_none", task_types=dronescapes_task_types)
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print(reader)
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print("== Shapes ==")
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