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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    UnidentifiedImageError
Message:      cannot identify image file <_io.BytesIO object at 0x7f2bc0db0630>
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 2567, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2103, in __iter__
                  batch = formatter.format_batch(pa_table)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 472, in format_batch
                  batch = self.python_features_decoder.decode_batch(batch)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/formatting/formatting.py", line 234, in decode_batch
                  return self.features.decode_batch(batch, token_per_repo_id=self.token_per_repo_id) if self.features else batch
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2254, in decode_batch
                  decode_nested_example(self[column_name], value, token_per_repo_id=token_per_repo_id)
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1508, in decode_nested_example
                  return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/image.py", line 190, in decode_example
                  image = PIL.Image.open(bytes_)
                          ^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/PIL/Image.py", line 3498, in open
                  raise UnidentifiedImageError(msg)
              PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x7f2bc0db0630>

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IndoLepAtlas — Indian Lepidoptera & Host Plants Dataset

A large-scale computer vision dataset of Indian butterflies, moths, and their larval host plants. Sourced from ifoundbutterflies.org with public CC-licensed photographs.

Inspired by: iNaturalist | Domain: Indian Wildlife & Biodiversity

Dataset Overview

Butterflies Host Plants Total
Species ~967 ~127 ~1,094
Images ~60,000 ~700 ~60,700
Source ifoundbutterflies.org ifoundbutterflies.org

Motivation

Existing CV datasets (ImageNet, iNaturalist) under-represent Indian biodiversity. India hosts ~1,500 butterfly species — many endemic and poorly documented in digital datasets. This dataset enables:

  • Species classification of Indian butterflies and host plants
  • Object detection with auto-generated bounding boxes
  • Ecological analysis of butterfly-plant host relationships
  • Diagnostic analysis using pretrained models

Directory Structure

IndoLepAtlas/
├── data/
│   ├── butterflies/
│   │   ├── raw/              # Original images (with overlays)
│   │   ├── images/           # Clean trimmed images
│   │   └── metadata.csv      # Enriched per-image metadata
│   └── plants/
│       ├── raw/
│       ├── images/
│       └── metadata.csv
├── annotations/
│   ├── butterflies/*.txt     # YOLO format
│   ├── plants/*.txt          # YOLO format
│   ├── annotations.json      # COCO format (combined)
│   └── classes.txt           # Species→ID mapping
├── splits/
│   ├── train.txt (70%)
│   ├── val.txt   (15%)
│   └── test.txt  (15%)
├── docs/
│   ├── class_definitions.json
│   ├── annotation_guide.md
│   ├── data_card.md
│   └── distribution_stats.md
├── README.md
└── LICENSE

Metadata Fields

Butterflies (metadata.csv)

image_id, filename, species, common_name, family, subfamily, genus, order, life_stage, sex, media_code, location, state, date, credit, source_url, source, split

Plants (metadata.csv)

image_id, filename, species, family, genus, image_type, media_code, location, state, date, credit, butterfly_hosts, source_url, source, split

Annotation Format

  • YOLO (per image): <class_id> <x_center> <y_center> <width> <height> (normalized)
  • COCO (annotations.json): standard format with images, categories, annotations
  • Classes: Species-level (~1,094 classes). See annotations/classes.txt

Classes

  • The dataset contains images for individual butterfly species:
    • ~1,000 Butterfly Species
    • 410 BUtterfly Families
    • ~500 Butterfly Species with substantial (>40) images
    • ~700 Plant species
  • The hero images for each species, each class here, are avialable under the data tab.

Ethical Guidelines

  • All images are from publicly available sources (ifoundbutterflies.org)
  • Photographer credits are preserved in metadata via OCR extraction
  • No human faces or personal information in the dataset
  • Source URLs and attribution maintained for every image

Citation

@dataset{indolepatlas2026,
  title={IndoLepAtlas: Indian Lepidoptera and Host Plants Dataset},
  year={2026},
  source={ifoundbutterflies.org},
  license={CC BY-NC-SA 4.0}
}

License

This dataset is released under CC BY-NC-SA 4.0.

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