Updated formatting

lerobot/common/datasets/transforms.py

@@ -47,11 +47,15 @@ class RandomSubsetApply(Transform):
 
 def make_transforms(cfg):
     image_transforms = []
-    if 'colorjitter' in cfg.list:
-        image_transforms.append(v2.ColorJitter(brightness=cfg.colorjitter_factor, contrast=cfg.colorjitter_factor))
-    if 'sharpness' in cfg.list:
+    if "colorjitter" in cfg.list:
+        image_transforms.append(
+            v2.ColorJitter(brightness=cfg.colorjitter_factor, contrast=cfg.colorjitter_factor)
+        )
+    if "sharpness" in cfg.list:
         image_transforms.append(v2.RandomAdjustSharpness(cfg.sharpness_factor, p=cfg.sharpness_p))
-    if 'blur' in cfg.list:
+    if "blur" in cfg.list:
         image_transforms.append(v2.RandomAdjustSharpness(cfg.blur_factor, p=cfg.blur_p))
 
-    return v2.Compose([RandomSubsetApply(image_transforms, n_subset=cfg.n_subset), v2.ToDtype(torch.float32, scale=True)])
+    return v2.Compose(
+        [RandomSubsetApply(image_transforms, n_subset=cfg.n_subset), v2.ToDtype(torch.float32, scale=True)]
+    )

lerobot/scripts/show_image_transforms.py

@@ -1,15 +1,14 @@
-
-from lerobot.common.utils.utils import init_hydra_config
-from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
-from lerobot.common.datasets.transforms import make_transforms
-
 from pathlib import Path
 
 import matplotlib.pyplot as plt
 
+from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
+from lerobot.common.datasets.transforms import make_transforms
+from lerobot.common.utils.utils import init_hydra_config
 
 DEFAULT_CONFIG_PATH = "configs/default.yaml"
 
+
 def show_image_transforms(cfg, repo_id, episode_index=0, output_dir="outputs/show_image_transforms"):
     """
     Apply a series of image transformations to a frame from a dataset and save the transformed images.
@@ -41,7 +40,8 @@ def show_image_transforms(cfg, repo_id, episode_index=0, output_dir="outputs/sho
                 "image_transform.enable=True",
                 "image_transform.n_subset=1",
                 f"image_transform.{transform}_p=1",
-            ])
+            ],
+        )
 
         cfg = cfg.image_transform
 
@@ -53,13 +53,14 @@ def show_image_transforms(cfg, repo_id, episode_index=0, output_dir="outputs/sho
 
         # Save transformed frame
         plt.imshow(transformed_frame)
-        plt.savefig(f'{base_filename}_max_transform_{transform}.png')
+        plt.savefig(f"{base_filename}_max_transform_{transform}.png")
         plt.close()
 
     frame = frame.permute(1, 2, 0).numpy()
+
     # Save original frame
     plt.imshow(frame)
-    plt.savefig(f'{base_filename}_original.png')
+    plt.savefig(f"{base_filename}_original.png")
     plt.close()
 
-    print(f"Saved transformed images.")
+    print("Saved transformed images.")