Vehicle quotes
1. Extract vehicle quote information with photo URL input
API:
Method | URL |
---|---|
GET | https://cloud.computervision.com.vn/api/v2/ocr/document/price_quotation |
Params:
Key | Value | Description |
---|---|---|
img | https://example.com/image.png | URL of photo |
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://cloud.computervision.com.vn/api/v2/ocr/document/price_quotation?img=%s&format_type=url&get_thumb=false"% image_url,auth=(api_key, api_secret))print(response.json())
2. Extract vehicle quote information with image file input
API:
Method | URL | content-type |
---|---|---|
POST | https://cloud.computervision.com.vn/api/v2/ocr/document/price_quotation | 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 of vehicle quote to extract information |
Demo Python:
import requestsapi_key = "YOUR_API_KEY"api_secret = "YOUR_API_SECRET"image_path = '/path/to/your/image.jpg'response = requests.post("https://cloud.computervision.com.vn/api/v2/ocr/document/price_quotation?format_type=file&get_thumb=false",auth=(api_key, api_secret),files={'img': open(image_path, 'rb')})print(response.json())
3. Extract vehicle quote information with JSON input
API:
Method | URL | content-type |
---|---|---|
POST | https://cloud.computervision.com.vn/api/v2/ocr/document/price_quotation | 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://cloud.computervision.com.vn/api/v2/ocr/document/price_quotation?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": [xxxx],"errorCode": string,"errorMessage": string}
Where the data
field is a list, each element in the list corresponds to a vehicle quote (a vehicle quote can be one or more pages). Each of these elements is a JSON formatted as follows:
{"type": "price_quotation","info": [xxxx]}
The info
field is a JSON with the following fields:
estimated_delivery_date
estimated_delivery_date_box
estimated_delivery_date_confidence
image
image_table
make_model
make_model_box
make_model_confidence
name_of_garage
name_of_garage_box
name_of_garage_confidence
number_plate
number_plate_box
number_plate_confidence
quotation_date
quotation_date_box
quotation_date_confidence
sub_total
sub_total_box
sub_total_confidence
table
: As a list, each element in the list contains information for a row. Each of these elements is a JSON containing the following information:amount_total
amount_total_box
amount_total_confidence
description
description_box
description_confidence
discount
discount_box
discount_confidence
percent_discount
percent_discount_box
percent_discount_confidence
quantity
quantity_box
quantity_confidence
tax
tax_box
tax_confidence
unit_price
unit_price_box
unit_price_confidence
total_amount
total_amount_box
total_amount_confidence
vat_amount
vat_amount_box
vat_amount_confidence
Error code table:
Code | Message |
---|---|
0 | Success |
1 | The photo does not contain content |
2 | Url is unavailable |
3 | Incorrect image format |
4 | Out of requests |
5 | Incorrect api_key or api_secret |
6 | Incorrect format type |