one more

scripts/dronescapes_viewer/dronescapes_viewer.py

@@ -15,6 +15,7 @@ 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 datetime import datetime
 
 from dronescapes_representations import get_dronescapes_task_types
 
@@ -23,7 +24,12 @@ def plot_one(data: dict[str, tr.Tensor], title: str, name_to_task: dict[str, Rep
     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])
         return node.make_images()[0]
-    img_data = {k: vre_plot_fn(data["rgb"], v, name_to_task[k]) for k, v in data.items()}
+    img_data = {}
+    keys = np.random.permutation(list(data.keys()))
+    for k in keys:
+        start = datetime.now()
+        img_data[k] = vre_plot_fn(data["rgb"], data[k], name_to_task[k])
+        print(k, (datetime.now() - start).total_seconds())
     img_data = reorder_dict(img_data, order) if order is not None else img_data
     titles = [title if len(title) < 40 else f"{title[0:19]}..{title[-19:]}" for title in img_data]
     collage = collage_fn(list(img_data.values()), titles=titles, size_px=40)
@@ -33,7 +39,8 @@ def plot_one(data: dict[str, tr.Tensor], title: str, name_to_task: dict[str, Rep
 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_names = ["rgb", "semantic_mask2former_r50_mapillary_converted", "semantic_mask2former_swin_coco_converted"]
+reader = MultiTaskDataset(data_path, task_names=task_names,
                           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())
@@ -50,4 +57,5 @@ 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, out_path := f"collage_{name[0:-4]}.png")
+print(f"Stored at '{out_path}'")