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La API de Extractor de Texto 2D a partir de PDF es una herramienta avanzada diseñada para facilitar la conversión de documentos PDF a formatos de texto estructurados en 2D. Este proceso es crucial para los usuarios que necesitan extraer datos de documentos PDF y transformarlos en un formato accesible y manipulable. A través de esta API, desarrolladores y usuarios pueden simplificar la tarea de analizar y utilizar la información contenida en archivos PDF, que tradicionalmente pueden ser complicados debido a su naturaleza fija y no editable. La API está optimizada para conversiones rápidas y precisas de archivos PDF a texto en 2D. Al convertir contenido de PDF, la API mantiene la estructura y el formato del documento original, permitiendo una representación fiel del contenido en el formato de texto. Una de las grandes ventajas de esta API es su capacidad para interpretar y preservar el diseño estructural del texto, como tablas, columnas y secciones. Esto es especialmente útil al trabajar con documentos que contienen datos tabulares o listas detalladas. La API facilita la extracción de información específica del documento PDF.
Recibe un archivo PDF y devuelve texto estructurado en 2D.
Automatización de Facturas:
Los usuarios pueden utilizar la API para extraer datos de facturas en formato PDF y cargarlos automáticamente en sistemas de contabilidad o gestión financiera, reduciendo el trabajo manual y los errores de entrada de datos.
Análisis de Informes Financieros:
Los analistas financieros pueden convertir informes en PDF a texto estructurado para facilitar el análisis de tendencias, comparación de datos y generación de informes personalizados sin necesidad de reingresar información manualmente.
Escaneo de Documentos Legales:
Las firmas legales pueden convertir contratos y otros documentos legales a texto 2D para facilitar la búsqueda de términos específicos, el análisis de cláusulas y la integración en bases de datos legales.
Extracción de Datos de Encuestas:
Las empresas que realizan encuestas en formato PDF pueden usar la API para extraer respuestas y datos, organizándolos en un formato estructurado que facilite el análisis y la generación estadística.
Transformación de Artículos Académicos:
Investigadores y académicos pueden convertir artículos de revistas y otros trabajos de investigación en texto estructurado, facilitando la búsqueda, citación y análisis de información relevante.
Plan Básico: 500 solicitudes por minuto.
Plan Pro: 500 solicitudes por minuto.
Plan Pro Plus: 500 solicitudes por minuto.
Plan Premium: 500 solicitudes por minuto.
Plan Elite: 500 solicitudes por minuto.
Plan Ultimate: 1,000 solicitudes por minuto
Para usar este endpoint, debes indicar un texto en el parámetro texto
Por ejemplo: Subir un PDF convertido a base64
Limitación actual
El PDF es un tipo de formato de representación gráfica, el texto plano no siempre podrá coincidir o presentar los textos como un lector de PDF. El algoritmo detrás de escena hace lo mejor para considerar múltiples factores y equilibrar la apariencia general en el espacio visual 2D.
Las imágenes aún no se manejan
Las curvas y las líneas diagonales aún no se manejan
Los textos de derecha a izquierda y de arriba hacia abajo aún no se manejan
PDF EXT - Características del Endpoint
| Objeto | Descripción |
|---|---|
Cuerpo de la Solicitud |
[Requerido] Json |
<<==[[Page 1]]==>>
Comparison from the Year Ended December 31, 2022 to the Year Ended December 31, 2023
Year Ended December 31, 2023
----------------------------------------------------------------------------------------------
% Change from Prior Period
--------------------------------------------------------------
Year Ended December 31,
---------------------------------- Constant Less Constant
Less FX Currency As Hedging Less FX Currency
2022 2023 Effect Revenues Reported Effect Effect Revenues
---------------- ---------------- --------------- --------------- -------------- --------------- --------------- ---------------
United States
$ 134,814 $ 146,286 $ 0 $ 146,286 9 % 0 % 9 %
EMEA 82,062 91,038 460 90,578 11 % 1 % 10 %
APAC 47,024 51,514 (1,759) 53,273 10 % (3) % 13 %
Other Americas 16,976 18,320 (654) 18,974 8 % (4) % 12 %
---------------- ---------------- --------------- ---------------
Revenues, excluding hedging effect 280,876 307,158 (1,953) 309,111 9 % (1) % 10 %
Hedging gains (losses) 1,960 236
Total revenues (1) ---------------- ---------------- ---------------
$ 282,836 $ 307,394 $ 309,111 9 % 0 % (1) % 10 %
---------------- ---------------- ---------------
---------------- ---------------- ---------------
(1)
Total constant currency revenues of $309.1 billion for the year ended December 31, 2023 increased $28.2 billion compared to $280.9 billion in
revenues, excluding hedging effect for the year ended December 31, 2022.
Total Revenues — Prior Year Comparative Periods
Comparison from the Quarter Ended December 31, 2021 to the Quarter Ended December 31, 2022
Quarter Ended December 31, 2022
----------------------------------------------------------------------------------------------
% Change from Prior Period
Quarter Ended December
Constant -------------------------------------------------------------
31, Less Constant
---------------------------------- Less FX Currency As Hedging Less FX Currency
2021 2022 Effect Revenues Reported Effect Effect Revenues...
curl --location --request POST 'https://zylalabs.com/api/4854/pdf+to+2d+text+extractor+api/6086/pdf+ext' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{
"output": "PLAIN",
"scaleX": 0.26,
"scaleY": 0.15,
"pageNos": [
1
],
"file": 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"
}'
| Encabezado | Descripción |
|---|---|
Autorización
|
[Requerido] Debería ser Bearer access_key. Consulta "Tu Clave de Acceso a la API" arriba cuando estés suscrito. |
Sin compromiso a largo plazo. Mejora, reduce o cancela en cualquier momento. La Prueba Gratuita incluye hasta 50 solicitudes.
Para usar esta API, debes indicar la URL de un nombre de dominio.
La API de Extractor de Texto 2D de PDF convierte documentos PDF en texto 2D estructurado, preservando el diseño y permitiendo la extracción de datos.
Hay diferentes planes que se adaptan a todos, incluyendo una prueba gratuita para un pequeño número de solicitudes, pero su tasa está limitada para prevenir el abuso del servicio.
Zyla proporciona una amplia gama de métodos de integración para casi todos los lenguajes de programación. Puedes utilizar estos códigos para integrarlos en tu proyecto según lo necesites.
La API devuelve texto estructurado en 2D, metadatos del proceso y posibles errores o advertencias encontrados durante la conversión.
La API devuelve texto estructurado en 2D extraído de documentos PDF, preservando el diseño, incluyendo tablas, columnas y secciones, lo que permite una fácil manipulación y análisis de los datos.
Los datos de respuesta están organizados en un formato estructurado, que típicamente incluye marcadores de página y el texto extraído, manteniendo el diseño del documento original para claridad y usabilidad.
El parámetro principal es el archivo PDF, que debe ser subido en formato base64. Los usuarios pueden personalizar las solicitudes especificando opciones adicionales para la extracción de texto, si están disponibles.
La API puede extraer varios tipos de información, incluyendo texto de facturas, informes financieros, documentos legales, respuestas a encuestas y artículos académicos, todo estructurado en un formato 2D.
Los usuarios pueden analizar el texto estructurado en busca de información específica, integrarla en bases de datos o realizar análisis de datos, lo que facilita la generación de informes o la realización de investigaciones adicionales.
Los datos se obtienen directamente de los documentos PDF proporcionados por los usuarios. La API procesa estos datos utilizando algoritmos avanzados para garantizar una extracción precisa mientras se preserva el diseño original.
La precisión de los datos se mantiene a través de algoritmos sofisticados que analizan la estructura y el contenido del PDF, asegurando que el texto extraído se asemeje estrechamente al formato y diseño originales.
Los casos de uso típicos incluyen la automatización del procesamiento de facturas, el análisis de informes financieros, el escaneo de documentos legales para cláusulas específicas, la extracción de datos de encuestas y la conversión de artículos académicos para una cita y análisis más fáciles.
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