> For the complete documentation index, see [llms.txt](https://docs.datasaur.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.datasaur.ai/api/custom-ocr.md). # Custom OCR ## OCR Custom Text Extraction API This custom text extraction API is a Datasaur feature which allows creating a custom [OCR](/data-studio-projects/nlp-task-types/project-templates.md#optical-character-recognition) project using your own text extraction API. ### Request from Datasaur > **POST** | **Request headers** | | | ------------------- | ---------------------------- | | Accept | application/json, text/plain | | **Form Data Parameters** | | | ------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------- | | upload | Your document file (e.g.: [receipt.jpg](https://user-images.githubusercontent.com/1897341/108043465-b844d200-7073-11eb-9beb-a69305024e15.jpg)) | ### **Expected API Response** Datasaur can process the response differently based on the **`Content-Type`** header returned from the API response. #### Text response (`Content-Type: text/plain)` ``` SHIHLIN TAIWAN STREET SNACKS Grand Galaxy Park DATE 26/02/20 15:53 CASHIER: Reny No. Customer: 1 ``` #### JSON response (`Content-Type: application/json`) Datasaur uses [Importable format](/api/custom-ocr/importable-format.md) to process the API response. ```javascript { "cells": [ { "content": "SHIHLIN TAIWAN", "index": 0, "line": 0, "metadata": [], "tokens": [ "SHIHLIN", "TAIWAN" ] }, { "content": "STREET SNACKS", "index": 0, "line": 1, "metadata": [], "tokens": [ "STREET", "SNACKS" ] } ], "labelSets": [], "labels": [ { "startCellLine": 0, "startCellIndex": 0, "startTokenIndex": 0, "startCharIndex": 0, "endCellLine": 0, "endCellIndex": 0, "endTokenIndex": 0, "endCharIndex": 6, "layer": 0, "counter": 0, "pageIndex": 0, "type": "BOUNDING_BOX", "nodeCount": 4, "x0": 130, "y0": 154, "x1": 255, "y1": 154, "x2": 255, "y2": 186, "x3": 130, "y3": 186 }, { "startCellLine": 0, "startCellIndex": 0, "startTokenIndex": 1, "startCharIndex": 0, "endCellLine": 0, "endCellIndex": 0, "endTokenIndex": 1, "endCharIndex": 5, "layer": 0, "counter": 0, "pageIndex": 0, "type": "BOUNDING_BOX", "nodeCount": 4, "x0": 261, "y0": 154, "x1": 375, "y1": 154, "x2": 375, "y2": 186, "x3": 261, "y3": 186 } ], "name": "receipt.jpg", "pages": [ { "pageIndex": 0, "pageHeight": 619, "pageWidth": 551 } ], "type": "BOUNDING_BOX" } ``` ### Apply custom API * Upload the PDF or images through [Project Creation Wizard](/data-studio-projects/creating-a-project.md#project-creation-wizard) * In Step 2, * Select **+Add new API...** as the OCR method
* Put your API name, API URL, and the secret
* After clicking Save, the custom API will be saved to the list, and you can choose it as the OCR method * [Create a label set, assign labelers as appropriate, then launch the project](/workspace-management/workspace.md#creating-a-project) * The interface will appear side-by-side with the PDF on the left and the transcription on the right
## ASR Custom Text Extraction API This custom text extraction API is a Datasaur feature which allows creating a custom[ Audio](https://datasaurai.gitbook.io/datasaur/nlp-projects/nlp-task-types/audio-project) project using your own text extraction API. ### Request from Datasaur > **POST** | **Request headers** | | | ------------------- | ---------------------------- | | Accept | application/json, text/plain | | **Form Data Parameters** | | | ------------------------ | -------------------------------------- | | upload | Your document file (e.g.: audio2.flac) | ### **Expected API Response** Datasaur can process the response differently based on the **`Content-Type`** header returned from the API response. #### Text response (`Content-Type: text/plain)` ``` A quick brown fox jumps over a lazy dog Speaker 2: A quick brown fox jumps over a lazy dog Speaker 1: A quick brown fox jumps over a lazy dog Speaker 2: A quick brown fox jumps over a lazy dog Speaker 1: A quick brown fox jumps over a lazy dog ``` #### JSON response (`Content-Type: application/json`) Datasaur uses [Importable format](/api/custom-ocr/importable-format.md) to process the API response. ```javascript { "cells": [ { "content": "SHIHLIN TAIWAN", "index": 0, "line": 0, "metadata": [], "tokens": ["SHIHLIN", "TAIWAN"] }, { "content": "STREET SNACKS", "index": 0, "line": 1, "metadata": [], "tokens": ["STREET", "SNACKS"] } ], "labelSets": [], "labels": [ { "id": 1, "startCellLine": 0, "startCellIndex": 0, "startTokenIndex": 0, "startCharIndex": 0, "endCellLine": 0, "endCellIndex": 0, "endTokenIndex": 1, "endCharIndex": 5, "layer": 0, "counter": 0, "startTimestampMillis": 1375, "endTimestampMillis": 4250, "type": "TIMESTAMP" }, { "id": 2, "startCellLine": 1, "startCellIndex": 0, "startTokenIndex": 0, "startCharIndex": 0, "endCellLine": 1, "endCellIndex": 0, "endTokenIndex": 1, "endCharIndex": 5, "layer": 0, "counter": 0, "startTimestampMillis": 4437, "endTimestampMillis": 8218, "type": "TIMESTAMP" } ], "name": "ASR API Response Sample", "type": "TIMESTAMP" } ``` ### Apply custom API * Upload the audio files through [Project Creation Wizard](/data-studio-projects/creating-a-project.md#project-creation-wizard) * In Step 2, * Select **+Add new API...** as the ASR method
* Put your API name, API URL, and the secret
* After clicking Save, the custom API will be saved to the list, and you can choose it as the ASR method * [Create a label set, assign labelers as appropriate, then launch the project](/workspace-management/workspace.md#creating-a-project) * The interface will appear like the screenshot below, with the audio on the top and the transcription on the bottom
{% hint style="info" %} Custom API capabilities are **only supported in team workspaces**. If you would like access, please email us at . {% endhint %}