feat(dataset): dynamic compress_level depending on the type of dataset (video or image) (#2517)
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@@ -110,8 +110,8 @@ def worker_thread_loop(queue: queue.Queue):
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if item is None:
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queue.task_done()
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break
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image_array, fpath = item
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write_image(image_array, fpath)
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image_array, fpath, compress_level = item
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write_image(image_array, fpath, compress_level)
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queue.task_done()
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@@ -169,11 +169,13 @@ class AsyncImageWriter:
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p.start()
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self.processes.append(p)
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def save_image(self, image: torch.Tensor | np.ndarray | PIL.Image.Image, fpath: Path):
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def save_image(
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self, image: torch.Tensor | np.ndarray | PIL.Image.Image, fpath: Path, compress_level: int = 1
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):
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if isinstance(image, torch.Tensor):
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# Convert tensor to numpy array to minimize main process time
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image = image.cpu().numpy()
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self.queue.put((image, fpath))
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self.queue.put((image, fpath, compress_level))
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def wait_until_done(self):
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self.queue.join()
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@@ -1092,13 +1092,15 @@ class LeRobotDataset(torch.utils.data.Dataset):
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def _get_image_file_dir(self, episode_index: int, image_key: str) -> Path:
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return self._get_image_file_path(episode_index, image_key, frame_index=0).parent
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def _save_image(self, image: torch.Tensor | np.ndarray | PIL.Image.Image, fpath: Path) -> None:
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def _save_image(
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self, image: torch.Tensor | np.ndarray | PIL.Image.Image, fpath: Path, compress_level: int = 1
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) -> None:
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if self.image_writer is None:
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if isinstance(image, torch.Tensor):
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image = image.cpu().numpy()
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write_image(image, fpath)
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write_image(image, fpath, compress_level=compress_level)
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else:
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self.image_writer.save_image(image=image, fpath=fpath)
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self.image_writer.save_image(image=image, fpath=fpath, compress_level=compress_level)
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def add_frame(self, frame: dict) -> None:
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"""
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@@ -1136,7 +1138,8 @@ class LeRobotDataset(torch.utils.data.Dataset):
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)
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if frame_index == 0:
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img_path.parent.mkdir(parents=True, exist_ok=True)
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self._save_image(frame[key], img_path)
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compress_level = 1 if self.features[key]["dtype"] == "video" else 6
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self._save_image(frame[key], img_path, compress_level)
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self.episode_buffer[key].append(str(img_path))
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else:
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self.episode_buffer[key].append(frame[key])
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