Datasets:

Sycamorers
/

Strawba-YOLO-Dataset

Error code:   DatasetGenerationError
Exception:    IndexError
Message:      list index out of range
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1859, in _prepare_split_single
                  original_shard_lengths[original_shard_id] += len(table)
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
              IndexError: list index out of range
              
              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 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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End of preview.

Strawba YOLO strawberry detection dataset

This dataset accompanies Strawba YOLO, a five-class object detector for top-down field imagery. It contains 1,928 annotated images and 40,665 YOLO-format bounding boxes. Images were collected at the University of Florida/IFAS Plant Science Research and Education Unit (PSREU) in Citra, Florida, and the Gulf Coast Research and Education Center (GCREC) in Wimauma, Florida. The corresponding manuscript is Strawba YOLO: A Specialized Mamba-based YOLO Model for Strawberry Detection by Zijing Huang, Won Suk Lee, and Peigeng Zhang.

Splits and classes

Split	Images
Train	1,541
Validation	192
Test	195

ID	Class	Bounding boxes
0	Flower (FL)	4,278
1	Green fruit (G)	14,767
2	White fruit (W)	12,283
3	Pink fruit (P)	1,925
4	Red fruit (R)	7,412

The manuscript describes a site-stratified 80/10/10 train/validation/test split after screening temporally adjacent video frames. Keep these existing splits when comparing results with the paper. The class frequencies reflect field observations; green and white fruit are more common than pink fruit.

Files and annotation format

data.yaml
images/{train,val,test}/*.jpg
labels/{train,val,test}/*.txt

Each image has a same-stem .txt annotation file. Each line is class_id x_center y_center width height, with coordinates normalized to [0, 1] in YOLO detection format. The class order is fixed in data.yaml. All 1,928 images and annotation files were checked for matching names, readable images, five-field labels, class IDs 0–4, and valid normalized coordinates before upload.

Download the repository as a dataset, then pass the absolute path of its data.yaml to the Strawba YOLO training or validation script:

hf download Sycamorers/Strawba-YOLO-Dataset --repo-type dataset --local-dir ./strawberry-5
python scripts/strawba.py val --variant s --data "$(pwd)/strawberry-5/data.yaml" --device 0

The data are provided in their YOLO training layout. This repository contains the dataset rather than the model code or weights; the linked GitHub repository contains both Strawba YOLO variants and their setup instructions.

Collection and limitations

The source images were captured from a top-down view in field production environments under natural illumination, with early- and late-season PSREU imagery and mid-season GCREC imagery. The dataset is dominated by small fruit instances and has strong class imbalance. Site, season, camera, and lighting differences can affect generalization; evaluations on new farms should be reported separately.

Citation

If you use the dataset, cite the accompanying Strawba YOLO manuscript by Zijing Huang, Won Suk Lee, and Peigeng Zhang. A DOI is not available in the source manuscript yet.

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