Classification of health insurance documents
1. Classification of health insurance documents with image URL or pdf URL input
API:
Method | URL |
---|---|
GET | https://demo.computervision.com.vn/api/v2/ocr/document/get_label_claim |
Params:
Key | Value | Description |
---|---|---|
img | https://example.com/image.png | URL of photo or pdf |
format_type | url | Type of data to pass in, receive value: url , file , base64 |
get_thumb | true /false | Returns a aligned image |
Demo Python:
import requestsapi_key = "YOUR_API_KEY"api_secret = "YOUR_API_SECRET"image_url = 'https://example.com/image.png'response = requests.get("https://demo.computervision.com.vn/api/v2/ocr/document/get_label_claim?img=%s&format_type=url&get_thumb=false"% image_url,auth=(api_key, api_secret))print(response.json())
2. Classification of health insurance documents with image file or pdf file input
API:
Method | URL | content-type |
---|---|---|
POST | https://demo.computervision.com.vn/api/v2/ocr/document/get_label_claim | multipart/form-data |
Params:
Key | Value | Description |
---|---|---|
format_type | file | Type of data to pass in, receive value: url , file , base64 |
get_thumb | true /false | Returns a aligned image |
Body:
Key | Type | Value | Description |
---|---|---|---|
img | file | example.jpg | Image file or pdf file |
Demo Python:
import requestsapi_key = "YOUR_API_KEY"api_secret = "YOUR_API_SECRET"image_path = '/path/to/your/image.jpg'response = requests.post("https://demo.computervision.com.vn/api/v2/ocr/document/get_label_claim?format_type=file&get_thumb=false",auth=(api_key, api_secret),files={'img': open(image_path, 'rb')})print(response.json())
3. Classification of health insurance documents with JSON input
API:
Method | URL | content-type |
---|---|---|
POST | https://demo.computervision.com.vn/api/v2/ocr/document/get_label_claim | application/json |
Params:
Key | Value | Description |
---|---|---|
format_type | base64 | Type of data to pass in, receive value: url , file , base64 |
get_thumb | true /false | Returns a aligned image |
Body:
{"img": "iVBORw0KGgoAAAANSU..." // string base64 of the image or pdf to extract}
Demo Python:
import base64import ioimport requestsfrom PIL import Imagedef get_byte_img(img):img_byte_arr = io.BytesIO()img.save(img_byte_arr, format='PNG')encoded_img = base64.encodebytes(img_byte_arr.getvalue()).decode('ascii')return encoded_imgapi_key = "YOUR_API_KEY"api_secret = "YOUR_API_SECRET"img_name = "path_img"encode_cmt = get_byte_img(Image.open(img_name))response = requests.post("https://demo.computervision.com.vn/api/v2/ocr/document/get_label_claim?format_type=base64&get_thumb=false",auth=(api_key, api_secret),json={'img' : encode_cmt})print(response.json())
4. Response
The response will be a JSON with the following format:
{"data": array,"errorCode": string,"errorMessage": string}
Each element in the data
array (corresponding to each extracted page) will be a JSON with the following format:
{"id": [xxxx],"label": [xxxx],"image": [xxxx]}
In there:
id
: The page order corresponds to the input file, starting from 0.label
: Label of the respective page. Currently 17 labels are supported in the insurance profile, if it does not fall into one of the 17 defined labels,label
will returnNone
.invoice
list_expense
claim_form
hospital_discharge_paper
id_doc
prescription
medical_report
discharge_report
bill
surgical_certificate
specify_vote
test_results
medical_examination
receipts
health_records
guarantee_confirmation
accident_report
image
Error code table:
Code | Message |
---|---|
0 | Success |
1 | Incorrect image format |
2 | Url is unavailable |
3 | Incorrect image format |
4 | Incorrect api_key or api_secret |
5 | Out of requests |
6 | Error when processing the request |