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- ---
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- dataset_info:
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- features:
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- - name: image
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- dtype: image
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- - name: labels
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- list: int32
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- - name: label_names
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- list: string
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- - name: num_labels
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- dtype: int32
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- splits:
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- - name: train
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- num_bytes: 2482744739
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- num_examples: 10400
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- - name: validation
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- num_bytes: 618611124
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- num_examples: 2600
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- download_size: 3100953195
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- dataset_size: 3101355863
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: data/train-*
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- - split: validation
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- path: data/validation-*
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: mit
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+ task_categories:
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+ - image-classification
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+ - multi-label-classification
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+ tags:
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+ - food-recognition
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+ - multi-label
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+ - computer-vision
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+ - food-classification
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+ size_categories:
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+ - 10K<n<100K
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+ ---
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+
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+ # Multi-Label Food Recognition Dataset
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+
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+
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+ This is a multi-label food recognition dataset generated from single-class food images.
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+ Each image contains 2-5 different food items composited together using natural composition methods.
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+
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+
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+ ## Dataset Details
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+
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+ - **Total Images**: 13,000
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+ - **Training Images**: 10,400 (80%)
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+ - **Validation Images**: 2,600 (20%)
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+ - **Number of Classes**: 90
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+ - **Labels per Image**: 2-5 labels
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+ - **Image Format**: RGB, 512x512 pixels
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+ - **File Format**: Parquet
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+
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+ ## Dataset Structure
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+
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+ Each sample contains:
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+ - `image`: PIL Image (RGB, 512x512)
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+ - `labels`: List of integer label IDs (multi-hot encoded)
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+ - `label_names`: List of string class names
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+ - `num_labels`: Number of labels in the image (2-5)
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+
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+ ## Usage
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Load dataset
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+ dataset = load_dataset("ibrahimdaud/multi-label-food-recognition")
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+
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+ # Access splits
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+ train_data = dataset['train']
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+ val_data = dataset['validation']
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+
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+ # Example: Get first training sample
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+ sample = train_data[0]
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+ print(f"Image: {sample['image']}")
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+ print(f"Labels: {sample['label_names']}")
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+ print(f"Label IDs: {sample['labels']}")
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+ ```
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+
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+ ## Citation
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+
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+ If you use this dataset, please cite:
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+
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+ ```bibtex
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+ @dataset{multi_label_food_recognition,
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+ title={Multi-Label Food Recognition Dataset},
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+ author={Your Name},
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+ year={2024},
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+ url={https://huggingface.co/datasets/ibrahimdaud/multi-label-food-recognition}
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+ }
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+ ```
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+
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+ ## License
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+
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+ MIT License