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[ { "box": [ 61, 127, 143, 211 ], "text": "", "label": "other", "words": [ { "box": [ 61, 127, 143, 211 ], "text": "" } ], "linking": [], "id": 0 }, { "box": [ 102, 3...
[ { "box": [ 75, 140, 93, 153 ], "text": "TO:", "label": "question", "words": [ { "box": [ 75, 140, 93, 153 ], "text": "TO:" } ], "linking": [ [ 0, 26 ] ], ...
[ { "box": [ 94, 200, 114, 214 ], "text": "TO:", "label": "question", "words": [ { "box": [ 94, 200, 114, 214 ], "text": "TO:" } ], "linking": [ [ 0, 13 ] ], ...
[ { "box": [ 362, 304, 379, 315 ], "text": "17", "label": "answer", "words": [ { "box": [ 362, 304, 379, 315 ], "text": "17" } ], "linking": [ [ 5, 0 ] ], ...
[ { "box": [ 547, 143, 588, 163 ], "text": "AUG 4", "label": "question", "words": [ { "box": [ 547, 143, 588, 163 ], "text": "AUG 4" } ], "linking": [ [ 18, 0 ] ...
[ { "box": [ 570, 901, 672, 928 ], "text": "82253058", "label": "other", "words": [ { "box": [ 570, 901, 672, 928 ], "text": "82253058" } ], "linking": [], "id": 0 }, { "box": [ ...
[ { "box": [ 36, 95, 57, 108 ], "text": "TO:", "label": "question", "words": [ { "box": [ 36, 95, 57, 108 ], "text": "TO:" } ], "linking": [ [ 0, 22 ] ], ...
[ { "box": [ 60, 88, 78, 102 ], "text": "TO:", "label": "question", "words": [ { "box": [ 60, 88, 78, 102 ], "text": "TO:" } ], "linking": [ [ 0, 44 ] ], ...
[ { "box": [ 78, 124, 100, 139 ], "text": "TO:", "label": "question", "words": [ { "box": [ 78, 124, 100, 139 ], "text": "TO:" } ], "linking": [ [ 0, 14 ] ], ...
[ { "box": [ 105, 196, 157, 207 ], "text": "COURT:", "label": "question", "words": [ { "box": [ 105, 196, 157, 207 ], "text": "COURT:" } ], "linking": [ [ 0, 16 ]...
[ { "box": [ 113, 198, 163, 211 ], "text": "COURT:", "label": "question", "words": [ { "box": [ 113, 198, 163, 211 ], "text": "COURT:" } ], "linking": [ [ 0, 16 ]...
[ { "box": [ 118, 249, 238, 309 ], "text": "Fax", "label": "header", "words": [ { "box": [ 118, 249, 238, 309 ], "text": "Fax" } ], "linking": [], "id": 0 }, { "box": [ 272...
[ { "box": [ 641, 722, 665, 821 ], "text": "82573104", "label": "other", "words": [ { "box": [ 641, 722, 665, 821 ], "text": "82573104" } ], "linking": [], "id": 0 }, { "box": [ ...
[ { "box": [ 140, 186, 179, 200 ], "text": "DATE:", "label": "question", "words": [ { "box": [ 140, 186, 179, 200 ], "text": "DATE:" } ], "linking": [ [ 0, 9 ] ...
[ { "box": [ 91, 223, 127, 238 ], "text": "DATE:", "label": "question", "words": [ { "box": [ 91, 223, 127, 238 ], "text": "DATE:" } ], "linking": [ [ 0, 15 ] ...
[ { "box": [ 253, 154, 294, 169 ], "text": "Sender", "label": "question", "words": [ { "box": [ 253, 154, 294, 169 ], "text": "Sender" } ], "linking": [ [ 0, 16 ]...
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YAML Metadata Warning: The task_categories "optical-character-recognition" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

FUNSD benchmark (DocLD)

Test set for the FUNSD benchmark used with DocLD: 50 form images and 50 ground-truth annotation JSON files.

  • images/ — 50 PNG form images (FUNSD test set).
  • annotations/ — 50 JSON files (FUNSD format: entities with text, box, label).

Code and full benchmark: github.com/Doc-LD/funsd-bench.

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