Description
This is a Form Recognition / Key Value extraction model, trained on the summary page of SEC 10K filings. It extracts KEY, VALUE or HEADER as entities, being HEADER the title on the filing.
Predicted Entities
KEY, VALUE, HEADER
How to use
binary_to_image = BinaryToImage()\
.setOutputCol("image") \
.setImageType(ImageType.TYPE_3BYTE_BGR)
img_to_hocr = ImageToHocr()\
.setInputCol("image")\
.setOutputCol("hocr")\
.setIgnoreResolution(False)\
.setOcrParams(["preserve_interword_spaces=0"])
tokenizer = HocrTokenizer()\
.setInputCol("hocr")\
.setOutputCol("token")
doc_ner = VisualDocumentNerV21()\
.pretrained("visualner_keyvalue_10kfilings", "en", "clinical/ocr")\
.setInputCols(["token", "image"])\
.setOutputCol("entities")
draw = ImageDrawAnnotations() \
.setInputCol("image") \
.setInputChunksCol("entities") \
.setOutputCol("image_with_annotations") \
.setFontSize(10) \
.setLineWidth(4)\
.setRectColor(Color.red)
# OCR pipeline
pipeline = PipelineModel(stages=[
binary_to_image,
img_to_hocr,
tokenizer,
doc_ner,
draw
])
import pkg_resources
bin_df = spark.read.format("binaryFile").load('data/t01.jpg')
bin_df.show()
results = pipeline.transform(bin_df).cache()
res = results.collect()
## since pyspark2.3 doesn't have element_at, 'getItem' is involked
path_array = f.split(results['path'], '/')
# from pyspark2.4
# results.withColumn("filename", f.element_at(f.split("path", "/"), -1)) \
results.withColumn('filename', path_array.getItem(f.size(path_array)- 1)) \
.withColumn("exploded_entities", f.explode("entities")) \
.select("filename", "exploded_entities") \
.show(truncate=False)
Results
+--------+---------------------------------------------------------------------------------------------------------------------------------------------------------+
|filename|exploded_entities |
+--------+---------------------------------------------------------------------------------------------------------------------------------------------------------+
|t01.jpg |{named_entity, 268, 269, OTHERS, {confidence -> 96, width -> 14, x -> 822, y -> 1101, word -> of, token -> of, height -> 34}, []} |
|t01.jpg |{named_entity, 271, 273, OTHERS, {confidence -> 89, width -> 33, x -> 837, y -> 1112, word -> the, token -> the, height -> 13}, []} |
|t01.jpg |{named_entity, 275, 277, OTHERS, {confidence -> 89, width -> 30, x -> 874, y -> 1113, word -> Act., token -> act, height -> 12}, []} |
|t01.jpg |{named_entity, 280, 282, KEY-B, {confidence -> 94, width -> 26, x -> 910, y -> 1113, word -> Yes, token -> yes, height -> 12}, []} |
|t01.jpg |{named_entity, 284, 285, VALUE-B, {confidence -> 45, width -> 13, x -> 944, y -> 1112, word -> LI, token -> li, height -> 13}, []} |
|t01.jpg |{named_entity, 287, 288, KEY-B, {confidence -> 83, width -> 22, x -> 963, y -> 1113, word -> No, token -> no, height -> 12}, []} |
|t01.jpg |{named_entity, 290, 295, HEADER-B, {confidence -> 96, width -> 89, x -> 1493, y -> 13, word -> UNITED, token -> united, height -> 16}, []} |
|t01.jpg |{named_entity, 297, 302, HEADER-I, {confidence -> 95, width -> 83, x -> 1590, y -> 13, word -> STATES, token -> states, height -> 16}, []} |
|t01.jpg |{named_entity, 304, 313, HEADER-B, {confidence -> 95, width -> 221, x -> 1186, y -> 45, word -> SECURITIES, token -> securities, height -> 25}, []} |
|t01.jpg |{named_entity, 315, 317, HEADER-I, {confidence -> 95, width -> 80, x -> 1415, y -> 45, word -> AND, token -> and, height -> 25}, []} |
|t01.jpg |{named_entity, 319, 326, HEADER-I, {confidence -> 96, width -> 212, x -> 1507, y -> 45, word -> EXCHANGE, token -> exchange, height -> 25}, []} |
|t01.jpg |{named_entity, 328, 337, HEADER-I, {confidence -> 95, width -> 249, x -> 1732, y -> 45, word -> COMMISSION, token -> commission, height -> 25}, []} |
|t01.jpg |{named_entity, 339, 348, HEADER-B, {confidence -> 96, width -> 125, x -> 1461, y -> 86, word -> Washington,, token -> washington, height -> 21}, []} |
|t01.jpg |{named_entity, 351, 351, HEADER-I, {confidence -> 93, width -> 43, x -> 1595, y -> 86, word -> D.C., token -> d, height -> 16}, []} |
|t01.jpg |{named_entity, 356, 360, HEADER-I, {confidence -> 93, width -> 59, x -> 1646, y -> 86, word -> 20549, token -> 20549, height -> 16}, []} |
|t01.jpg |{named_entity, 362, 365, HEADER-B, {confidence -> 93, width -> 112, x -> 1484, y -> 159, word -> FORM, token -> form, height -> 25}, []} |
|t01.jpg |{named_entity, 367, 368, HEADER-I, {confidence -> 91, width -> 77, x -> 1609, y -> 159, word -> 10-K, token -> 10, height -> 25}, []} |
+--------+---------------------------------------------------------------------------------------------------------------------------------------------------------+
Model Information
| Model Name: | visualner_keyvalue_10kfilings |
| Type: | ocr |
| Compatibility: | Visual NLP 4.0.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 744.3 MB |
References
Sec 10K filings