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README.md
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# Bird Detection Dataset
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This dataset contains images and corresponding labels for a binary classification task: identifying whether a given image contains a bird or not. It is designed for use in computer vision tasks such as image classification, detection, or transfer learning.
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## Dataset Structure
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- **Total Images:** 4,410
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- 2,973 images containing birds (`bird`)
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- 1,437 images not containing birds (`no_bird`)
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- **Split:** 80% training (`train.csv`), 20% testing (`test.csv`)
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### Folder Layout
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my-bird-dataset/
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├── train.csv
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├── test.csv
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├── bird/ # Contains images named bird-0001.jpg, ..., bird-2973.jpg
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├── no_bird/ # Contains images named no_bird-0001.jpg, ..., no_bird-1437.jpg
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less
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## CSV Format
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Each CSV (`train.csv` or `test.csv`) has the following columns:
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| image | image_id | caption | label |
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|-----------------------|--------------|---------------------------------------|----------|
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| path/to/image.jpg | bird-0001 | This image contains a bird. | bird |
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| path/to/image.jpg | no_bird-0001 | This image does not contain a bird. | no_bird |
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- `image`: Relative path to the image file
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- `image_id`: Unique image identifier
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- `caption`: Description of the image contents
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- `label`: Class label (`bird` or `no_bird`)
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## How to Use
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You can load this dataset using the [datasets](https://huggingface.co/docs/datasets) library:
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```python
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from datasets import load_dataset
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dataset = load_dataset("ravisri/BirdBinaryClassification")
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train = dataset['train']
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test = dataset['test']
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Or, load the CSV directly:
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python
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train = load_dataset("ravisri/BirdBinaryClassification", data_files="train.csv")['train']
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License
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Include your license here (e.g., MIT, CC BY 4.0). If unknown, please specify.
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Citation
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If you use this dataset in your work, please cite:
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ini
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@dataset{your_name_2024_bird_detection,
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title = {BirdBinaryClassification},
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author = {ravisri},
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year = {2024},
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url = {https://huggingface.co/datasets/ravisri/BirdBinaryClassification},
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}
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Contact
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For questions, please open an issue or contact [ravisripallam@gmail.com].
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