In this quickstart, you'll use the Azure Form Recognizer REST API with Python to extract and identify relevant information on business cards.
If you don't have an Azure subscription, create a free account before you begin.
To complete this quickstart, you must have:
- Python installed (if you want to run the sample locally).
- An image of a business card. You can use a sample image for this quickstart.
Note
This quickstart uses a local file. To use a remote business card image accessed by URL instead, see the reference documentation.
Go to the Azure portal and create a new Form Recognizer resource . In the Create pane, provide the following information:
| Name | A descriptive name for your resource. We recommend using a descriptive name, for example MyNameFormRecognizer. |
| Subscription | Select the Azure subscription which has been granted access. |
| Location | The location of your cognitive service instance. Different locations may introduce latency, but have no impact on the runtime availability of your resource. |
| Pricing tier | The cost of your resource depends on the pricing tier you choose and your usage. For more information, see the API pricing details. |
| Resource group | The Azure resource group that will contain your resource. You can create a new group or add it to a pre-existing group. |
Note
Normally when you create a Cognitive Service resource in the Azure portal, you have the option to create a multi-service subscription key (used across multiple cognitive services) or a single-service subscription key (used only with a specific cognitive service). However currently Form Recognizer is not included in the multi-service subscription.
When your Form Recognizer resource finishes deploying, find and select it from the All resources list in the portal. Your key and endpoint will be located on the resource's key and endpoint page, under resource management. Save both of these to a temporary location before going forward.
To start analyzing a business card, you call the Analyze Business Card API using the Python script below. Before you run the script, make these changes:
-
Replace
<endpoint>with the endpoint that you obtained with your Form Recognizer subscription. -
Replace
<path to your business card>with the local path to your business card image or PDF. -
Replace
<subscription key>with the subscription key you copied from the previous step. -
Replace
<file type>with 'image/jpeg', 'image/png', 'application/pdf', or 'image/tiff'.########### Python Form Recognizer Async Business Cards ############# import json import time from requests import get, post # Endpoint URL endpoint = r"<endpoint>" apim_key = "<subscription key>" post_url = endpoint + "/formrecognizer/v2.1/prebuilt/businessCard/analyze" source = r"<path to your business card>" content_type = "<file type>" headers = { # Request headers 'Content-Type': content_type, 'Ocp-Apim-Subscription-Key': apim_key, } params = { "includeTextDetails": True # True to output all recognized text } with open(source, "rb") as f: data_bytes = f.read() try: resp = post(url = post_url, data = data_bytes, headers = headers, params = params) if resp.status_code != 202: print("POST analyze failed:\n%s" % resp.text) quit() print("POST analyze succeeded:\n%s" % resp.headers) get_url = resp.headers["operation-location"] except Exception as e: print("POST analyze failed:\n%s" % str(e)) quit()
-
Save the code in a file with a .py extension. For example, form-recognizer-businesscards.py.
-
Open a command prompt window.
-
At the prompt, use the
pythoncommand to run the sample. For example,python form-recognizer-businesscards.py.
You'll receive a 202 (Success) response that includes an Operation-Location header, which the script will print to the console. This header contains a result ID that you can use to query the status of the long running operation and get the results. In the following example value, the string after operations/ is the result ID.
https://westus.api.cognitive.microsoft.com/formrecognizer/v2.1/prebuilt/businessCard/analyzeResults/41d82152-f55c-45ce-8d92-1ed70300f360After you've called the Analyze Business Card API, you call the Get Analyze Business Card Result API to get the status of the operation and the extracted data. Add the following code to the bottom of your Python script. This uses the result ID value in a new API call. This script calls the API at regular intervals until the results are available. We recommend an interval of one second or more.
n_tries = 10
n_try = 0
wait_sec = 6
while n_try < n_tries:
try:
resp = get(url = get_url, headers = {"Ocp-Apim-Subscription-Key": apim_key})
resp_json = json.loads(resp.text)
if resp.status_code != 200:
print("GET Business card results failed:\n%s" % resp_json)
quit()
status = resp_json["status"]
if status == "succeeded":
print("Business card Analysis succeeded:\n%s" % resp_json)
quit()
if status == "failed":
print("Analysis failed:\n%s" % resp_json)
quit()
# Analysis still running. Wait and retry.
time.sleep(wait_sec)
n_try += 1
except Exception as e:
msg = "GET analyze results failed:\n%s" % str(e)
print(msg)
quit()- Save the script.
- Again use the
pythoncommand to run the sample. For example,python form-recognizer-businesscards.py.
This sample illustrates the JSON output returned by Form Recognizer. It has been truncated for readability.
{
"status": "succeeded",
"createdDateTime": "2020-06-04T08:19:29Z",
"lastUpdatedDateTime": "2020-06-04T08:19:35Z",
"analyzeResult": {
"version": "2.1.1",
"readResults": [
{
"page": 1,
"angle": -17.0956,
"width": 4032,
"height": 3024,
"unit": "pixel"
}
],
"documentResults": [
{
"docType": "prebuilt:businesscard",
"pageRange": [
1,
1
],
"fields": {
"ContactNames": {
"type": "array",
"valueArray": [
{
"type": "object",
"valueObject": {
"FirstName": {
"type": "string",
"valueString": "Avery",
"text": "Avery",
"boundingBox": [
703,
1096,
1134,
989,
1165,
1109,
733,
1206
],
"page": 1
},
"text": "Dr. Avery Smith",
"boundingBox": [
419.3,
1154.6,
1589.6,
877.9,
1618.9,
1001.7,
448.6,
1278.4
],
"confidence": 0.993
}
]
},
"Emails": {
"type": "array",
"valueArray": [
{
"type": "string",
"valueString": "avery.smith@contoso.com",
"text": "avery.smith@contoso.com",
"boundingBox": [
2107,
934,
2917,
696,
2935,
764,
2126,
995
],
"page": 1,
"confidence": 0.99
}
]
},
"Websites": {
"type": "array",
"valueArray": [
{
"type": "string",
"valueString": "https://www.contoso.com/",
"text": "https://www.contoso.com/",
"boundingBox": [
2121,
1002,
2992,
755,
3014,
826,
2143,
1077
],
"page": 1,
"confidence": 0.995
}
]
}
}
}
]
}
}The script will print responses to the console until the Analyze Business Card operation completes.
The "readResults" node contains all of the recognized text. Text is organized by page, then by line, then by individual words. The "documentResults" node contains the business-card-specific values that the model discovered. This is where you'll find useful contact information like the company name, first name, last name, phone number, and so on.
In this quickstart, you used the Form Recognizer REST API with Python to extract the content of a business card. Next, see the reference documentation to explore the Form Recognizer API in more depth.