Remove PIL fallback from GR00T preprocessing

src/lerobot/policies/groot/processor_groot.py

@@ -24,7 +24,6 @@ import numpy as np
 import torch
 import torchvision.transforms.v2.functional as tv_functional
 from einops import rearrange
-from PIL import Image
 from torchvision.transforms import InterpolationMode
 
 from lerobot.utils.import_utils import _transformers_available, require_package
@@ -750,13 +749,13 @@ def _build_n1_7_processor(model_name: str = GROOT_N1_7_BACKBONE_MODEL) -> Proces
 
 
 def _transform_n1_7_image_for_vlm_albumentations(
-    image: np.ndarray | Image.Image,
+    image: np.ndarray,
     *,
     image_crop_size: list[int] | None,
     image_target_size: list[int] | None,
     shortest_image_edge: int | None,
     crop_fraction: float | None,
-) -> np.ndarray | Image.Image:
+) -> np.ndarray:
     """cv2/INTER_AREA eval transform mirroring Isaac-GR00T's albumentations preprocessing.
 
     Used only for checkpoints saved with ``use_albumentations=True``. cv2 is
@@ -778,16 +777,11 @@ def _transform_n1_7_image_for_vlm_albumentations(
             "GR00T N1.7 checkpoints with use_albumentations=True require opencv-python-headless."
         ) from exc
 
-    if isinstance(image, Image.Image):
-        if image.mode != "RGB":
-            image = image.convert("RGB")
-        image_np = np.asarray(image)
-    else:
-        image_np = np.asarray(image)
-        if image_np.ndim == 2:
-            image_np = np.repeat(image_np[:, :, None], 3, axis=2)
-        elif image_np.shape[-1] == 4:
-            image_np = image_np[:, :, :3]
+    image_np = np.asarray(image)
+    if image_np.ndim == 2:
+        image_np = np.repeat(image_np[:, :, None], 3, axis=2)
+    elif image_np.ndim == 3 and image_np.shape[-1] == 4:
+        image_np = image_np[:, :, :3]
 
     if not image_np.flags.c_contiguous:
         image_np = np.ascontiguousarray(image_np)