tensorflow/models · error · FileNotFoundError

Dataset {dataset_name!r} is missing required images folder:

Error message

Dataset {dataset_name!r} is missing required images folder: {images_dir}

What it means

Error "Dataset {dataset_name!r} is missing required images folder: {images_dir}" thrown in tensorflow/models.

Source

Thrown at official/projects/waste_identification_ml/data_generation/auto_labeler_pipeline/filter_sparse_images.py:193

) -> list[tuple[str, str]]:
  """Validates that each dataset has the expected input images folder.

  Args:
      dataset_directories: List of ``(dataset_name, dataset_path)`` tuples.
      input_images_folder_name: Name of the input images subfolder.

  Returns:
      A list of ``(dataset_name, images_dir)`` tuples ready for processing.

  Raises:
      FileNotFoundError: If any dataset is missing its images folder.
  """
  validated = []
  for dataset_name, dataset_path in dataset_directories:
    images_dir = os.path.join(dataset_path, input_images_folder_name)

    if not os.path.isdir(images_dir):
      raise FileNotFoundError(
          f"Dataset {dataset_name!r} is missing required images folder: "
          f"{images_dir}"
      )

    validated.append((dataset_name, images_dir))

  return validated


def validate_rejected_dir(rejected_dir: str) -> None:
  """Ensures the rejected directory does not already exist.

  Args:
      rejected_dir: Path to the rejected directory.

  Raises:
      FileExistsError: If ``rejected_dir`` already exists.
  """

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/waste_identification_ml/data_generation/auto_labeler_pipeline/filter_sparse_images.py:193 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24). Data as JSON: /api/errors/18193302ed71d79c. Report an issue: GitHub.