feat(dataset): dynamic compress_level depending on the type of dataset (video or image) (#2517)

This commit is contained in:
Steven Palma
2025-11-25 19:11:12 +01:00
committed by GitHub
parent 18b32dced9
commit 87bee86640
2 changed files with 13 additions and 8 deletions

View File

@@ -110,8 +110,8 @@ def worker_thread_loop(queue: queue.Queue):
if item is None:
queue.task_done()
break
image_array, fpath = item
write_image(image_array, fpath)
image_array, fpath, compress_level = item
write_image(image_array, fpath, compress_level)
queue.task_done()
@@ -169,11 +169,13 @@ class AsyncImageWriter:
p.start()
self.processes.append(p)
def save_image(self, image: torch.Tensor | np.ndarray | PIL.Image.Image, fpath: Path):
def save_image(
self, image: torch.Tensor | np.ndarray | PIL.Image.Image, fpath: Path, compress_level: int = 1
):
if isinstance(image, torch.Tensor):
# Convert tensor to numpy array to minimize main process time
image = image.cpu().numpy()
self.queue.put((image, fpath))
self.queue.put((image, fpath, compress_level))
def wait_until_done(self):
self.queue.join()

View File

@@ -1092,13 +1092,15 @@ class LeRobotDataset(torch.utils.data.Dataset):
def _get_image_file_dir(self, episode_index: int, image_key: str) -> Path:
return self._get_image_file_path(episode_index, image_key, frame_index=0).parent
def _save_image(self, image: torch.Tensor | np.ndarray | PIL.Image.Image, fpath: Path) -> None:
def _save_image(
self, image: torch.Tensor | np.ndarray | PIL.Image.Image, fpath: Path, compress_level: int = 1
) -> None:
if self.image_writer is None:
if isinstance(image, torch.Tensor):
image = image.cpu().numpy()
write_image(image, fpath)
write_image(image, fpath, compress_level=compress_level)
else:
self.image_writer.save_image(image=image, fpath=fpath)
self.image_writer.save_image(image=image, fpath=fpath, compress_level=compress_level)
def add_frame(self, frame: dict) -> None:
"""
@@ -1136,7 +1138,8 @@ class LeRobotDataset(torch.utils.data.Dataset):
)
if frame_index == 0:
img_path.parent.mkdir(parents=True, exist_ok=True)
self._save_image(frame[key], img_path)
compress_level = 1 if self.features[key]["dtype"] == "video" else 6
self._save_image(frame[key], img_path, compress_level)
self.episode_buffer[key].append(str(img_path))
else:
self.episode_buffer[key].append(frame[key])