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Quickstart: Extract printed text (OCR) using the Computer Vision REST API with Go

Note

If you're extracting English language text, consider using the new Read operation. A Go quickstart is available.

In this quickstart, you will extract printed text with optical character recognition (OCR) from an image using the Computer Vision REST API. With the OCR method, you can detect printed text in an image and extract recognized characters into a machine-usable character stream.

Prerequisites

  • An Azure subscription - Create one for free
  • Go
  • Once you have your Azure subscription, create a Computer Vision resource in the Azure portal to get your key and endpoint. After it deploys, click Go to resource.
    • You will need the key and endpoint from the resource you create to connect your application to the Computer Vision service. You'll paste your key and endpoint into the code below later in the quickstart.
    • You can use the free pricing tier (F0) to try the service, and upgrade later to a paid tier for production.

Create and run the sample

To create and run the sample, do the following steps:

  1. Copy the following code into a text editor.
  2. Replace the values of key and endpoint with your Computer Vision key and endpoint.
  3. Optionally, replace the value of imageUrl with the URL of a different image that you want to analyze.
  4. Save the code as a file with a .go extension. For example, get-printed-text.go.
  5. Open a command prompt window.
  6. At the prompt, run the go build command to compile the package from the file. For example, go build get-printed-text.go.
  7. At the prompt, run the compiled package. For example, get-printed-text.
package main

import (
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
    "os"
    "strings"
    "time"
)

func main() {
    // Add your Computer Vision key and endpoint to your environment variables.
    // Add your Computer Vision key and endpoint to your environment variables.
    key := "PASTE_YOUR_COMPUTER_VISION_KEY_HERE"
    endpoint := "PASTE_YOUR_COMPUTER_VISION_ENDPOINT_HERE"

    uriBase := endpoint + "vision/v3.1/ocr"
    const imageUrl = "https://upload.wikimedia.org/wikipedia/commons/thumb/a/af/" +
        "Atomist_quote_from_Democritus.png/338px-Atomist_quote_from_Democritus.png"

    params := "?language=unk&detectOrientation=true"
    uri := uriBase + params
    const imageUrlEnc = "{\"url\":\"" + imageUrl + "\"}"

    reader := strings.NewReader(imageUrlEnc)

    // Create the Http client
    client := &http.Client{
        Timeout: time.Second * 2,
    }

    // Create the Post request, passing the image URL in the request body
    req, err := http.NewRequest("POST", uri, reader)
    if err != nil {
        panic(err)
    }

    // Add headers
    req.Header.Add("Content-Type", "application/json")
    req.Header.Add("Ocp-Apim-Subscription-Key", key)

    // Send the request and retrieve the response
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }

    defer resp.Body.Close()

    // Read the response body.
    // Note, data is a byte array
    data, err := ioutil.ReadAll(resp.Body)
    if err != nil {
        panic(err)
    }

    // Parse the Json data
    var f interface{}
    json.Unmarshal(data, &f)

    // Format and display the Json result
    jsonFormatted, _ := json.MarshalIndent(f, "", "  ")
    fmt.Println(string(jsonFormatted))
}

Examine the response

A successful response is returned in JSON. The sample application parses and displays a successful response in the command prompt window, similar to the following example:

{
  "language": "en",
  "orientation": "Up",
  "regions": [
    {
      "boundingBox": "21,16,304,451",
      "lines": [
        {
          "boundingBox": "28,16,288,41",
          "words": [
            {
              "boundingBox": "28,16,288,41",
              "text": "NOTHING"
            }
          ]
        },
        {
          "boundingBox": "27,66,283,52",
          "words": [
            {
              "boundingBox": "27,66,283,52",
              "text": "EXISTS"
            }
          ]
        },
        {
          "boundingBox": "27,128,292,49",
          "words": [
            {
              "boundingBox": "27,128,292,49",
              "text": "EXCEPT"
            }
          ]
        },
        {
          "boundingBox": "24,188,292,54",
          "words": [
            {
              "boundingBox": "24,188,292,54",
              "text": "ATOMS"
            }
          ]
        },
        {
          "boundingBox": "22,253,297,32",
          "words": [
            {
              "boundingBox": "22,253,105,32",
              "text": "AND"
            },
            {
              "boundingBox": "144,253,175,32",
              "text": "EMPTY"
            }
          ]
        },
        {
          "boundingBox": "21,298,304,60",
          "words": [
            {
              "boundingBox": "21,298,304,60",
              "text": "SPACE."
            }
          ]
        },
        {
          "boundingBox": "26,387,294,37",
          "words": [
            {
              "boundingBox": "26,387,210,37",
              "text": "Everything"
            },
            {
              "boundingBox": "249,389,71,27",
              "text": "else"
            }
          ]
        },
        {
          "boundingBox": "127,431,198,36",
          "words": [
            {
              "boundingBox": "127,431,31,29",
              "text": "is"
            },
            {
              "boundingBox": "172,431,153,36",
              "text": "opinion."
            }
          ]
        }
      ]
    }
  ],
  "textAngle": 0
}

Next steps

Explore the Computer Vision API used to analyze an image, detect celebrities and landmarks, create a thumbnail, and extract printed and handwritten text. To rapidly experiment with the Computer Vision API, try the Open API testing console.