tensorflow/models · error · FileNotFoundError
Dataset {dataset_name!r} is missing required input folder: {
Error message
Dataset {dataset_name!r} is missing required input folder: {source_folder} What it means
Error "Dataset {dataset_name!r} is missing required input folder: {source_folder}" thrown in tensorflow/models.
Source
Thrown at official/projects/waste_identification_ml/data_generation/auto_labeler_pipeline/split_train_val.py:122
dataset_directories: List of ``(dataset_name, dataset_path)`` tuples.
input_images_folder_name: Name of the input images subfolder.
train_val_folder_name: Name of the train/val output subfolder.
Returns:
A list of ``(dataset_name, source_folder, output_folder)`` tuples ready
for processing.
Raises:
FileNotFoundError: If a dataset is missing its input folder.
FileExistsError: If a dataset's output folder already exists.
"""
validated = []
for dataset_name, dataset_path in dataset_directories:
source_folder = os.path.join(dataset_path, input_images_folder_name)
output_folder = os.path.join(dataset_path, train_val_folder_name)
if not os.path.isdir(source_folder):
raise FileNotFoundError(
f"Dataset {dataset_name!r} is missing required input folder: "
f"{source_folder}"
)
if os.path.exists(output_folder):
raise FileExistsError(
f"Dataset {dataset_name!r} already has an output folder: "
f"{output_folder}. Remove or rename it before re-running."
)
validated.append((dataset_name, source_folder, output_folder))
return validated
# ── Image discovery and filtering ───────────────────────────────────────────
View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/projects/waste_identification_ml/data_generation/auto_labeler_pipeline/split_train_val.py:122 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/a648989aa86df3d9.
Report an issue: GitHub.