Datasets:

gfermoto
/

birdlense-annotations

Error code:   StreamingRowsError
Exception:    ValueError
Message:      Invalid string class label birdlense-annotations@828a8e99ab5cfd87a18f48cf7e793dcefe24e9c3
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2240, in __iter__
                  example = _apply_feature_types_on_example(
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2157, in _apply_feature_types_on_example
                  encoded_example = features.encode_example(example)
                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2152, in encode_example
                  return encode_nested_example(self, example)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1437, in encode_nested_example
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1460, in encode_nested_example
                  return schema.encode_example(obj) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1143, in encode_example
                  example_data = self.str2int(example_data)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1080, in str2int
                  output = [self._strval2int(value) for value in values]
                            ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1101, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label birdlense-annotations@828a8e99ab5cfd87a18f48cf7e793dcefe24e9c3

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BirdLense Annotations

Dataset of bird annotations from feeders for the BirdLense Hub project — a bird feeder monitoring system with detection (YOLO, BirdNET).

Description

Images of birds and squirrels captured by BirdLense cameras at feeders. Annotations in YOLO format (bounding boxes) for training and fine-tuning detection models. Data is collected by community members through confirming and correcting automatic detections.

Dataset Structure

train/
  images/     # Training images
  labels/     # YOLO annotations (.txt)
val/
  images/
  labels/
data.yaml     # Class configuration and paths

Classes

Species list is defined in data.yaml. Typical categories: birds (tits, sparrows, woodpeckers, etc.), squirrels, mice.

Usage

Download

from huggingface_hub import snapshot_download

path = snapshot_download(
    repo_id="gfermoto/birdlense-annotations",
    repo_type="dataset",
    local_dir="./birdlense-data",
)

YOLO Training

yolo detect train data=./birdlense-data/data.yaml model=yolov8n.pt epochs=100

Data Source

BirdLense Hub — open-source bird feeder monitoring system
Detection: YOLO + BirdNET
Labeling: user confirmation/correction in the UI

License

CC BY-NC-ND 4.0 — attribution required, non-commercial, no derivatives without permission.