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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type list<item: list<item: double>> to null
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1871, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 623, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2293, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2246, in cast_table_to_schema
arrays = [
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2247, in <listcomp>
cast_array_to_feature(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1796, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1796, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2014, in cast_array_to_feature
casted_array_values = _c(array.values, feature[0])
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1798, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2006, in cast_array_to_feature
arrays = [
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2007, in <listcomp>
_c(array.field(name) if name in array_fields else null_array, subfeature)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1798, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2006, in cast_array_to_feature
arrays = [
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2007, in <listcomp>
_c(array.field(name) if name in array_fields else null_array, subfeature)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1798, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2066, in cast_array_to_feature
casted_array_values = _c(array.values, feature.feature)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1798, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2103, in cast_array_to_feature
return array_cast(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1798, in wrapper
return func(array, *args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1951, in array_cast
raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
TypeError: Couldn't cast array of type list<item: list<item: double>> to null
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1438, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1050, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 925, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1001, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1742, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1898, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
tags sequence | description string | objects list | size dict |
|---|---|---|---|
[] | [
{
"id": 1164155991,
"classId": 11380334,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:58:10.147Z",
"updatedAt": "2023-01-18T10:58:10.147Z",
"tags": [],
"classTitle": "Back-bumper",
"points": {
"exterior": [
... | {
"height": 419,
"width": 637
} | |
[] | [
{
"id": 1164156013,
"classId": 11380323,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:58:10.147Z",
"updatedAt": "2023-01-18T10:58:10.147Z",
"tags": [],
"classTitle": "Windshield",
"points": {
"exterior": [
... | {
"height": 440,
"width": 637
} | |
[] | [
{
"id": 1164156043,
"classId": 11380322,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:58:10.147Z",
"updatedAt": "2023-01-18T10:58:10.147Z",
"tags": [],
"classTitle": "Grille",
"points": {
"exterior": [
... | {
"height": 471,
"width": 629
} | |
[] | [
{
"id": 1164156066,
"classId": 11380334,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:58:10.147Z",
"updatedAt": "2023-01-18T10:58:10.147Z",
"tags": [],
"classTitle": "Back-bumper",
"points": {
"exterior": [
... | {
"height": 476,
"width": 881
} | |
[] | [
{
"id": 1164161206,
"classId": 11380335,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:59:09.213Z",
"updatedAt": "2023-03-22T12:31:53.556Z",
"tags": [],
"classTitle": "Mirror",
"points": {
"exterior": [
... | {
"height": 479,
"width": 634
} | |
[] | [
{
"id": 1164161284,
"classId": 11380331,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:59:09.213Z",
"updatedAt": "2023-01-18T10:59:09.213Z",
"tags": [],
"classTitle": "Tail-light",
"points": {
"exterior": [
... | {
"height": 501,
"width": 902
} | |
[] | [
{
"id": 1164161241,
"classId": 11380323,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:59:09.213Z",
"updatedAt": "2023-01-18T10:59:09.213Z",
"tags": [],
"classTitle": "Windshield",
"points": {
"exterior": [
... | {
"height": 527,
"width": 699
} | |
[] | [
{
"id": 1164161256,
"classId": 11380327,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:59:09.213Z",
"updatedAt": "2023-01-18T10:59:09.213Z",
"tags": [],
"classTitle": "Back-wheel",
"points": {
"exterior": [
... | {
"height": 407,
"width": 701
} | |
[] | [
{
"id": 1164161071,
"classId": 11380317,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:59:09.213Z",
"updatedAt": "2023-01-18T10:59:09.213Z",
"tags": [],
"classTitle": "Front-wheel",
"points": {
"exterior": [
... | {
"height": 459,
"width": 701
} | |
[] | [
{
"id": 1164161274,
"classId": 11380331,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:59:09.213Z",
"updatedAt": "2023-04-01T08:15:22.539Z",
"tags": [],
"classTitle": "Tail-light",
"points": {
"exterior": [
... | {
"height": 530,
"width": 701
} | |
[] | [
{
"id": 1164161191,
"classId": 11380316,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:59:09.213Z",
"updatedAt": "2023-04-01T08:16:01.686Z",
"tags": [],
"classTitle": "Quarter-panel",
"points": {
"exterior": [
... | {
"height": 479,
"width": 702
} | |
[] | [
{
"id": 1164160853,
"classId": 11380330,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:59:09.213Z",
"updatedAt": "2023-03-22T12:51:52.204Z",
"tags": [],
"classTitle": "Fender",
"points": {
"exterior": [
... | {
"height": 406,
"width": 703
} | |
[] | [
{
"id": 1164161080,
"classId": 11380327,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:59:09.213Z",
"updatedAt": "2023-01-18T10:59:09.213Z",
"tags": [],
"classTitle": "Back-wheel",
"points": {
"exterior": [
... | {
"height": 461,
"width": 703
} | |
[] | [
{
"id": 1164156077,
"classId": 11380323,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:58:10.147Z",
"updatedAt": "2023-04-01T08:18:13.625Z",
"tags": [],
"classTitle": "Windshield",
"points": {
"exterior": [
... | {
"height": 442,
"width": 637
} | |
[] | [
{
"id": 1164160867,
"classId": 11380336,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:59:09.213Z",
"updatedAt": "2023-04-01T08:19:00.414Z",
"tags": [],
"classTitle": "Roof",
"points": {
"exterior": [
[... | {
"height": 478,
"width": 703
} | |
[] | [
{
"id": 1164160898,
"classId": 11380336,
"description": "",
"geometryType": "polygon",
"labelerLogin": "GhazalehHITL",
"createdAt": "2023-01-18T10:59:09.213Z",
"updatedAt": "2023-01-18T10:59:09.213Z",
"tags": [],
"classTitle": "Roof",
"points": {
"exterior": [
[... | {
"height": 483,
"width": 703
} |
End of preview.
Car Parts and Damages Polygon Dataset
Dataset Summary
The Car Parts and Damages Polygon Dataset consists of 1,812 high-resolution images, each annotated with polygon-based segmentation masks for either car parts or car damages. The dataset is designed to support training and evaluation of deep learning models for fine-grained object detection, instance segmentation, and automotive inspection tasks.
✅ Key Stats:
- Total images: 1,812
- Car parts: 998 images
- Car damages: 814 images
- Total polygons: 24,851
This dataset supports advanced computer vision tasks such as automated damage detection, insurance assessment, vehicle inspection, and part localization.
Classes
🧩 Car Parts (998 Images)
Annotated polygon classes include:
- Windshield
- Back-windshield
- Front-window
- Back-window
- Front-door
- Back-door
- Front-wheel
- Back-wheel
- Front-bumper
- Back-bumper
- Headlight
- Tail-light
- Hood
- Trunk
- License-plate
- Mirror
- Roof
- Grille
- Rocker-panel
- Quarter-panel
- Fender
💥 Car Damages (814 Images)
Annotated polygon classes include:
- Dent
- Cracked
- Scratch
- Flaking
- Broken part
- Paint chip
- Missing part
- Corrosion
Use Cases
This dataset is ideal for developing:
- Instance segmentation models for automotive inspection
- Damage classification and severity assessment tools
- Insurance and repair estimate systems
- Multi-class part detection and vehicle structure understanding
Dataset Format
- Annotations are provided in polygon format, compatible with tools like COCO JSON or VIA/VGG annotations.
- Each image is labeled with one of two categories: car parts or car damages, with corresponding polygon masks.
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