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Cannot get the config names for the dataset.
Error code: ConfigNamesError
Exception: ValueError
Message: Couldn't infer the same data file format for all splits. Got {NamedSplit('train'): ('json', {}), NamedSplit('validation'): ('imagefolder', {})}
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 65, in compute_config_names_response
for config in sorted(get_dataset_config_names(path=dataset, token=hf_token))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 351, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1512, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1489, in dataset_module_factory
return HubDatasetModuleFactoryWithoutScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1054, in get_module
module_name, default_builder_kwargs = infer_module_for_data_files(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 513, in infer_module_for_data_files
raise ValueError(f"Couldn't infer the same data file format for all splits. Got {split_modules}")
ValueError: Couldn't infer the same data file format for all splits. Got {NamedSplit('train'): ('json', {}), NamedSplit('validation'): ('imagefolder', {})}Need help to make the dataset viewer work? Open a discussion for direct support.
AutoTrain Dataset for project: coffee-beans
Dataset Description
This dataset has been automatically processed by AutoTrain for project coffee-beans.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<224x224 RGB PIL image>",
"feat_width": 224,
"feat_height": 224,
"target": 1,
"feat_xmin": 22,
"feat_ymin": 61,
"feat_xmax": 140,
"feat_ymax": 160
},
{
"image": "<224x224 RGB PIL image>",
"feat_width": 224,
"feat_height": 224,
"target": 1,
"feat_xmin": 34,
"feat_ymin": 13,
"feat_xmax": 205,
"feat_ymax": 164
}
]
Dataset Fields
The dataset has the following fields (also called "features"):
{
"image": "Image(decode=True, id=None)",
"feat_width": "Value(dtype='int64', id=None)",
"feat_height": "Value(dtype='int64', id=None)",
"target": "ClassLabel(names=['defect', 'good'], id=None)",
"feat_xmin": "Value(dtype='int64', id=None)",
"feat_ymin": "Value(dtype='int64', id=None)",
"feat_xmax": "Value(dtype='int64', id=None)",
"feat_ymax": "Value(dtype='int64', id=None)"
}
Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
|---|---|
| train | 3348 |
| valid | 1237 |
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