slight updates to viewer

scripts/dronescapes_viewer/dronescapes_viewer.py

@@ -1,33 +1,24 @@
+#!/usr/bin/env python3
 import sys
 import os
 os.environ["STATS_PBAR"] = "1"
 os.environ["VRE_LOGLEVEL"] = "0"
+import random
 from pathlib import Path
 sys.path.append(Path.cwd().parent.__str__())
 from pprint import pprint
-import random
-from vre.readers.multitask_dataset import MultiTaskDataset, MultiTaskItem
+from vre.readers.multitask_dataset import MultiTaskDataset
 from vre.representations import Representation, ReprOut
-from vre.utils import MemoryData, reorder_dict
+from vre.utils import MemoryData, reorder_dict, lo
 import numpy as np
 import torch as tr
 from media_processing_lib.collage_maker import collage_fn
 from media_processing_lib.image import image_add_title, image_write
 import matplotlib.pyplot as plt
 
-from dronescapes_representations import dronescapes_task_types
-
-data_path = "../../data/test_set"
-stats_path = "../../data/train_set/.task_statistics.npz"
-reader = MultiTaskDataset(data_path, task_names=list(dronescapes_task_types),
-                          task_types=dronescapes_task_types, handle_missing_data="fill_nan",
-                          normalization="min_max", cache_task_stats=True, batch_size_stats=300,
-                          statistics=np.load(stats_path, allow_pickle=True)["arr_0"].item())
-print(reader)
-print("== Shapes ==")
-pprint(reader.data_shape)
+from dronescapes_representations import get_dronescapes_task_types
 
-def plot_one(data: MultiTaskItem, title: str, name_to_task: dict[str, Representation], 
+def plot_one(data: dict[str, tr.Tensor], title: str, name_to_task: dict[str, Representation], 
              order: list[str] | None = None) -> np.ndarray:
     def vre_plot_fn(rgb: tr.Tensor, x: tr.Tensor, node: Representation) -> np.ndarray:
         node.data = ReprOut(rgb.cpu().detach().numpy()[None], MemoryData(x.cpu().detach().numpy()[None]), [0])
@@ -39,13 +30,24 @@ def plot_one(data: MultiTaskItem, title: str, name_to_task: dict[str, Representa
     collage = image_add_title(collage, title, size_px=55, top_padding=110)
     return collage
 
+data_path = "../../data/test_set"
+stats_path = "../../data/train_set/.task_statistics.npz"
+dronescapes_task_types = get_dronescapes_task_types(include_semantics_original=False, include_gt=True, include_ci=False)
+reader = MultiTaskDataset(data_path, task_names=list(dronescapes_task_types),
+                          task_types=dronescapes_task_types, handle_missing_data="fill_nan",
+                          normalization="min_max", cache_task_stats=True, batch_size_stats=300,
+                          statistics=np.load(stats_path, allow_pickle=True)["arr_0"].item())
+print(reader)
+print("== Shapes ==")
+pprint(reader.data_shape)
+
 print("== Random loaded item ==")
-# rand_ix = random.randint(0, len(reader) - 1)
-rand_ix = "norway_210821_DJI_0015_full_2774.npz"
+rand_ix = random.randint(0, len(reader) - 1)
+# rand_ix = "norway_210821_DJI_0015_full_2774.npz"
 data, name = reader[rand_ix] # get a random item
 print(name)
-# collage = plot_one(data, title=name, name_to_task=reader.name_to_task)
-
+collage = plot_one(data, title=name, name_to_task=reader.name_to_task)
+print(lo(collage))
 # plt.figure(figsize=(20, 10))
 # plt.imshow(collage)
-# image_write(collage, f"collage_{name[0:-4]}.png")
+image_write(collage, f"collage_{name[0:-4]}.png")