Hive’s OCR moderation model outputs semantically grouped and ordered text blocks in their natural reading order accompanied by a set of classifications, timestamps and indexes.
{
"id": "2dfe7430-5b08-11ed-a11f-d7bc8b3c8807",
"code": 200,
"project_id": 41566,
"user_id": 3121654,
"created_on": "2022-11-02T23:43:42.368Z",
"status": [
{
"status": {
"code": "0",
"message": "SUCCESS"
},
"response": {
"input": {
"id": "2dfe7430-5b08-11ed-a11f-d7bc8b3c8807",
"created_on": "2022-11-02T23:43:40.787Z",
"user_id": 3121654,
"project_id": 41566,
"charge": 0.003,
"model": "v0_3",
"model_version": 1,
"model_type": "OCR_MODERATION",
"inference_client_version": "6.1.0",
"hash": "ff509aa1d605b8fb4e03f1ad88693f37",
"media": {
"url": null,
"filename": "SanFranciscoNeighborhoods.jpeg",
"type": "PHOTO",
"mime_type": "jpeg",
"mimetype": "image/jpeg",
"width": 1600,
"height": 1314,
"num_frames": 1,
"duration": 0
}
},
"output": [
{
"time": 0,
"frame_results": [
{
"language": "EN",
"block_text": "San Francisco NORTH california WATERSRONT MARINA RUSSIAN PRESIDIO HOLLOW HILL BEACH COW FINANCIAL DISTRICT PACIFIC NOB HILL BARBARY COAST PRESIDIO HEIGHTS MA HEIGHTS HEIGHTS DOWNTOWN STREET LOWER PACIFIC LINCOLN LAKE ИАСКСИ PARK PARK LAUREL HERGHTS TENDERLOIN BUENA SOUTH BEACH ANZA WESTERN CENTER CENTRAL INNER VISTA ADDITION RICHMOND LONE OUTER RICHMOND MOUNTAIN RICHMOND NORTH SQUARE PANHANDLE SOUTH OF HAYES MARKET NAIGHT ANHBURY VALLEY MISSION GOLDEN GATE PARK BAY INNER MISSION DOLORES SUNSET OUTER CENTRAL VALLEY FOREST DOLDIES HEIGHTS POTRERO HILL SUNSET SUNSET KNOLLS TWIN PEAKS INNER MISSION CENTRAL WATERFRONT DOGPATCH FOREST TERRACE VALLEY NOE OUTER PARKSIDE INNER PARKSIDE PARKSIDE WEST PORTAL MIRALOMA HEIGHTS BERNAL HUNTERS HEIGHTS SANT PARK PARK PINE LAKE PARK WEE GLEN MANOIR SUNNYSIDE SILVER LAKE STONESTOWN LAKESIDE INGUESIDE TERRACE WESTWOOD MISSION EXCELSIOR PORTOLA BAYVIEW POINT SHORE MERCED INGLESIDE HEIGHTS MEA사엘 HEIGHTS OCEANVIEW MISSION VISITACION INGLESIDE HEIGHTS CROCKER VALLEY CANDLESTICK POINT AMAZON",
"start_char_index": 0,
"end_char_index": 1033,
"custom_classes": [],
"text_filters": [],
"pii_entities": [],
"urls": [],
"classes": [
{
"class": "spam",
"score": 0
},
{
"class": "sexual",
"score": 0
},
{
"class": "hate",
"score": 0
},
{
"class": "violence",
"score": 0
},
{
"class": "bullying",
"score": 0
},
{
"class": "promotions",
"score": 0
},
{
"class": "gibberish",
"score": 0
},
{
"class": "child_exploitation",
"score": 0
},
{
"class": "phone_number",
"score": 0
}
],
"bounding_poly": [
{
"classes": [
{
"class": "San",
"score": 0.9999999484711606
}
],
"dimensions": {
"left": 1130.8434218203035,
"right": 1229.3265023337224,
"top": 54.65066586841236,
"bottom": 96.17978518659417
},
"vertices": [
{
"x": 1130.8434218203035,
"y": 96.17978518659417
},
{
"x": 1130.8434218203035,
"y": 54.65066586841236
},
{
"x": 1229.3265023337224,
"y": 54.65066586841236
},
{
"x": 1229.3265023337224,
"y": 96.17978518659417
}
],
"meta": {
"score": 0.9997242093086243,
"label": "text"
}
},
{
"classes": [
{
"class": "Francisco",
"score": 0.9999999422877002
}
],
"dimensions": {
"left": 1265.0711967619604,
"right": 1545.1178712077012,
"top": 55.93030897053805,
"bottom": 96.05957033417442
},
"vertices": [
{
"x": 1265.0711967619604,
"y": 96.05957033417442
},
{
"x": 1265.0711967619604,
"y": 55.93030897053806
},
{
"x": 1545.1178712077012,
"y": 55.93030897053805
},
{
"x": 1545.1178712077012,
"y": 96.05957033417442
}
],
"meta": {
"score": 0.9998077750205994,
"label": "text"
}
},
{
"classes": [
{
"class": "NORTH",
"score": 0.9999999608380823
}
],
"dimensions": {
"left": 944.3767320595099,
"right": 987.3172221411902,
"top": 133.31049624356356,
"bottom": 144.5093598799272
},
"vertices": [
{
"x": 944.3767320595099,
"y": 144.5093598799272
},
{
"x": 944.3767320595099,
"y": 133.31049624356356
},
{
"x": 987.3172221411902,
"y": 133.31049624356356
},
{
"x": 987.3172221411902,
"y": 144.5093598799272
}
],
"meta": {
"score": 0.9777765274047852,
"label": "text"
}
},
{
"classes": [
{
"class": "AMAZON",
"score": 0.9999999422877008
}
],
"dimensions": {
"left": 677.5199186843641,
"right": 762.4674099329055,
"top": 1207.510659131137,
"bottom": 1222.442477312955
},
"vertices": [
{
"x": 677.5199186843641,
"y": 1222.442477312955
},
{
"x": 677.5199186843641,
"y": 1207.510659131137
},
{
"x": 762.4674099329055,
"y": 1207.510659131137
},
{
"x": 762.4674099329055,
"y": 1222.442477312955
}
],
"meta": {
"score": 0.9990476965904236,
"label": "text"
}
}
]
}
]
}
]
}
}
],
"from_cache": false
}
| Name | Description |
|---|---|
| frame_results[j].bounding_poly[i].classes.0.class | Contains the transcribed characters for the detected word. |
| frame_results[j].bounding_poly[i].classes.0.score | Contains the confidence score for the transcribed word. |
| frame_results[j].bounding_poly[i].meta.score | Contains the confidence score for the detected word — irrespective of the transcription of that word. |
| frame_results[j].classes | List of dictionaries of all output classes. Each dictionary contains the class name and the score. The scores range from 0 to 3 with 3 being the most severe. |
| frame_results[j].classes.class | Name of predicted class. |
| frame_results[j].classes.score | Score of predicted class. |
| frame_results[j].classes.start_char_index | First character processed. |
| frame_results[j].classes.end_char_index | Last character processed. |