fix(vlabench): resize images to declared observation_space shape

VLABench's load_env doesn't always honor render_resolution, so the
returned rgb frames may not match our declared (h, w, 3) observation
space. gymnasium's SyncVectorEnv.concatenate then raises
"Output array is the wrong shape". Resize to the declared (h, w).

Made-with: Cursor

src/lerobot/envs/vlabench.py

@@ -237,11 +237,16 @@ class VLABenchEnv(gym.Env):
                     else:  # HWC
                         images["image"] = rgb.astype(np.uint8)
 
-        # Fill missing cameras with zeros
+        # VLABench's native render size may not match our declared observation_space.
+        # Resize each image to (h, w) so gymnasium's vector env concatenate succeeds.
         h, w = self.render_resolution
         for key in ["image", "second_image", "wrist_image"]:
             if key not in images:
                 images[key] = np.zeros((h, w, 3), dtype=np.uint8)
+            elif images[key].shape[:2] != (h, w):
+                import cv2
+
+                images[key] = cv2.resize(images[key], (w, h), interpolation=cv2.INTER_AREA).astype(np.uint8)
 
         # Extract end-effector state
         ee_state = obs.get("ee_state", np.zeros(7, dtype=np.float64))