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README.md
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---
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dataset_info:
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features:
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- name: ner_tags
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sequence:
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class_label:
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names:
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'0': O
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'1': B-ENERGY_KJ_100G
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'2': I-ENERGY_KJ_100G
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'3': B-VITAMIN_D_SERVING
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'4': I-VITAMIN_D_SERVING
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'5': B-SODIUM_SERVING
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'6': I-SODIUM_SERVING
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'7': B-PROTEINS_SERVING
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'8': I-PROTEINS_SERVING
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'9': B-ADDED_SUGARS_SERVING
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'10': I-ADDED_SUGARS_SERVING
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'11': B-CALCIUM_SERVING
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'12': I-CALCIUM_SERVING
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'13': B-FAT_SERVING
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'14': I-FAT_SERVING
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'15': B-ENERGY_KJ_SERVING
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'16': I-ENERGY_KJ_SERVING
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'17': B-SUGARS_100G
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'18': I-SUGARS_100G
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'19': B-SATURATED_FAT_SERVING
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'20': I-SATURATED_FAT_SERVING
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'21': B-SERVING_SIZE
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'22': I-SERVING_SIZE
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'23': B-SALT_SERVING
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'24': I-SALT_SERVING
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'25': B-ENERGY_KCAL_SERVING
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'26': I-ENERGY_KCAL_SERVING
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'27': B-FAT_100G
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'28': I-FAT_100G
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'29': B-SUGARS_SERVING
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'30': I-SUGARS_SERVING
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'31': B-FIBER_SERVING
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'32': I-FIBER_SERVING
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'33': B-TRANS_FAT_SERVING
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'34': I-TRANS_FAT_SERVING
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'35': B-POTASSIUM_SERVING
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'36': I-POTASSIUM_SERVING
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'37': B-CARBOHYDRATES_100G
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'38': I-CARBOHYDRATES_100G
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'39': B-POTASSIUM_100G
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'40': I-POTASSIUM_100G
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'41': B-IRON_SERVING
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'42': I-IRON_SERVING
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'43': B-CHOLESTEROL_100G
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'44': I-CHOLESTEROL_100G
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'45': B-TRANS_FAT_100G
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'46': I-TRANS_FAT_100G
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'47': B-ADDED_SUGARS_100G
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'48': I-ADDED_SUGARS_100G
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'49': B-FIBER_100G
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'50': I-FIBER_100G
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'51': B-CALCIUM_100G
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'52': I-CALCIUM_100G
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'53': B-SODIUM_100G
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'54': I-SODIUM_100G
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'55': B-ENERGY_KCAL_100G
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'56': I-ENERGY_KCAL_100G
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'57': B-CHOLESTEROL_SERVING
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'58': I-CHOLESTEROL_SERVING
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'59': B-CARBOHYDRATES_SERVING
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'60': I-CARBOHYDRATES_SERVING
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'61': B-SALT_100G
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'62': I-SALT_100G
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'63': B-VITAMIN_D_100G
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'64': I-VITAMIN_D_100G
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'65': B-SATURATED_FAT_100G
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'66': I-SATURATED_FAT_100G
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'67': B-PROTEINS_100G
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'68': I-PROTEINS_100G
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'69': B-IRON_100G
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'70': I-IRON_100G
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- name: tokens
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sequence: string
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- name: bboxes
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sequence:
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sequence: int64
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- name: image
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dtype: image
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- name: meta
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struct:
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- name: barcode
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dtype: string
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- name: image_id
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dtype: string
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- name: image_url
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dtype: string
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- name: split
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dtype: string
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- name: ocr_url
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dtype: string
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- name: batch
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dtype: string
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- name: label_studio_id
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dtype: int64
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- name: checked
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dtype: bool
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- name: usda_table
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dtype: bool
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- name: nutrition_text
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dtype: bool
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- name: no_nutrition_table
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dtype: bool
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- name: comment
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dtype: string
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splits:
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- name: train
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num_bytes: 607157648.1712618
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num_examples: 2884
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- name: test
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num_bytes: 41894719.82873824
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num_examples: 199
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download_size: 635258020
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dataset_size: 649052368
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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: test
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path: data/test-*
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license: cc-by-sa-3.0
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task_categories:
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- token-classification
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tags:
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- food
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size_categories:
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- 1K<n<10K
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---
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# Nutrient extraction dataset
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@@ -183,9 +183,9 @@ We removed the 'B-' and '-I' prefixes for readability, so the real number of lab
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The following fields are available for each sample:
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- `ner_tags`: a list of label IDs for each token in the input image. The label IDs are integers, and the mapping from label IDs to label names can be found in the
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- `tokens`: a list of tokens in the input image. This was extracted using Google Cloud Vision API.
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- `bboxes`: a list of bounding boxes for each token in the input image. The bounding boxes are in the format `[x_min, y_min, x_max, y_max]`, where `(x_min, y_min)` is the top-left corner and `(x_max, y_max)` is the bottom-right corner of the bounding box. The bounding boxes are in the same order as the tokens. The coordinates should be normalized between 1 and 1000 (excluded).
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- `image`: the image.
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- `meta`: a dictionary containing the following fields:
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- `barcode`: the barcode of the product.
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- `ocr_url`: the URL of the OCR result.
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- `batch`: the annotation batch (annotations were performed by batches of ~100 samples)
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- `label_studio_id`: the ID of the task in Label Studio.
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- `checked`: whether
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- `usda_table`: whether the nutrition table is from a USDA-like table
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- `nutrition_text`: whether the nutrition table is
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- `no_nutrition_table`: whether the image contains no nutrition table
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- `comment`: a comment from the annotators.
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The dataset (including the images) are licensed under the Creative Commons Attribution Share Alike license (CC-BY-SA 3.0).
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---
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dataset_info:
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features:
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- name: ner_tags
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sequence:
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class_label:
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names:
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'0': O
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'1': B-ENERGY_KJ_100G
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'2': I-ENERGY_KJ_100G
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'3': B-VITAMIN_D_SERVING
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'4': I-VITAMIN_D_SERVING
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'5': B-SODIUM_SERVING
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'6': I-SODIUM_SERVING
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'7': B-PROTEINS_SERVING
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'8': I-PROTEINS_SERVING
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'9': B-ADDED_SUGARS_SERVING
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'10': I-ADDED_SUGARS_SERVING
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'11': B-CALCIUM_SERVING
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'12': I-CALCIUM_SERVING
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'13': B-FAT_SERVING
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'14': I-FAT_SERVING
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'15': B-ENERGY_KJ_SERVING
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'16': I-ENERGY_KJ_SERVING
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'17': B-SUGARS_100G
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'18': I-SUGARS_100G
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'19': B-SATURATED_FAT_SERVING
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'20': I-SATURATED_FAT_SERVING
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'21': B-SERVING_SIZE
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'22': I-SERVING_SIZE
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'23': B-SALT_SERVING
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'24': I-SALT_SERVING
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'25': B-ENERGY_KCAL_SERVING
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'26': I-ENERGY_KCAL_SERVING
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'27': B-FAT_100G
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'28': I-FAT_100G
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'29': B-SUGARS_SERVING
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'30': I-SUGARS_SERVING
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'31': B-FIBER_SERVING
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'32': I-FIBER_SERVING
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'33': B-TRANS_FAT_SERVING
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'34': I-TRANS_FAT_SERVING
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'35': B-POTASSIUM_SERVING
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'36': I-POTASSIUM_SERVING
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'37': B-CARBOHYDRATES_100G
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'38': I-CARBOHYDRATES_100G
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'39': B-POTASSIUM_100G
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'40': I-POTASSIUM_100G
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'41': B-IRON_SERVING
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'42': I-IRON_SERVING
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'43': B-CHOLESTEROL_100G
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'44': I-CHOLESTEROL_100G
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'45': B-TRANS_FAT_100G
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'46': I-TRANS_FAT_100G
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'47': B-ADDED_SUGARS_100G
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'48': I-ADDED_SUGARS_100G
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'49': B-FIBER_100G
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'50': I-FIBER_100G
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'51': B-CALCIUM_100G
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'52': I-CALCIUM_100G
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'53': B-SODIUM_100G
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'54': I-SODIUM_100G
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'55': B-ENERGY_KCAL_100G
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'56': I-ENERGY_KCAL_100G
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'57': B-CHOLESTEROL_SERVING
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'58': I-CHOLESTEROL_SERVING
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'59': B-CARBOHYDRATES_SERVING
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'60': I-CARBOHYDRATES_SERVING
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'61': B-SALT_100G
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'62': I-SALT_100G
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'63': B-VITAMIN_D_100G
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'64': I-VITAMIN_D_100G
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'65': B-SATURATED_FAT_100G
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'66': I-SATURATED_FAT_100G
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'67': B-PROTEINS_100G
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'68': I-PROTEINS_100G
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'69': B-IRON_100G
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'70': I-IRON_100G
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- name: tokens
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sequence: string
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- name: bboxes
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sequence:
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sequence: int64
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- name: image
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dtype: image
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- name: meta
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struct:
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- name: barcode
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dtype: string
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- name: image_id
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dtype: string
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- name: image_url
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dtype: string
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- name: split
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dtype: string
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- name: ocr_url
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dtype: string
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- name: batch
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dtype: string
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- name: label_studio_id
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dtype: int64
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- name: checked
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dtype: bool
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- name: usda_table
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dtype: bool
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- name: nutrition_text
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dtype: bool
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- name: no_nutrition_table
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dtype: bool
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- name: comment
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dtype: string
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splits:
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- name: train
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num_bytes: 607157648.1712618
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num_examples: 2884
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- name: test
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num_bytes: 41894719.82873824
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num_examples: 199
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+
download_size: 635258020
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dataset_size: 649052368
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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: test
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path: data/test-*
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license: cc-by-sa-3.0
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task_categories:
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- token-classification
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tags:
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- food
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size_categories:
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- 1K<n<10K
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---
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# Nutrient extraction dataset
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The following fields are available for each sample:
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- `ner_tags`: a list of label IDs for each token in the input image. The label IDs are integers, and the mapping from label IDs to label names can be found in the HuggingFace dataset metadata. It's automatically available when loading the dataset using the `datasets` library.
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- `tokens`: a list of tokens in the input image. This was extracted using Google Cloud Vision API.
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- `bboxes`: a list of bounding boxes for each token in the input image. The bounding boxes are in the format `[x_min, y_min, x_max, y_max]`, where `(x_min, y_min)` is the top-left corner and `(x_max, y_max)` is the bottom-right corner of the bounding box. The bounding boxes are in the same order as the tokens. The coordinates should be normalized between 1 and 1000 (excluded). This was extracted from Google Cloud Vision OCR result as well.
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- `image`: the image.
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- `meta`: a dictionary containing the following fields:
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- `barcode`: the barcode of the product.
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- `ocr_url`: the URL of the OCR result.
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- `batch`: the annotation batch (annotations were performed by batches of ~100 samples)
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- `label_studio_id`: the ID of the task in Label Studio.
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- `checked`: whether a second annotator checked the annotation.
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- `usda_table`: whether the nutrition table is from a USDA-like table, as annotated by the annotators.
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- `nutrition_text`: whether the nutrition table is has a text structure (not a table), as annotated by the annotators.
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- `no_nutrition_table`: whether the image contains no nutrition table, as annotated by the annotators.
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- `comment`: a comment from the annotators.
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The dataset (including the images) are licensed under the Creative Commons Attribution Share Alike license (CC-BY-SA 3.0).
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