Vehicle documents
Image input standards: The system achieves the best results in both quality and processing speed with images in HD resolution (1280x720)
1. Extract information of vehicle documents with image URL or pdf URL input
API:
Method | URL |
---|---|
GET | https://cloud.computervision.com.vn/api/v2/ocr/vehicle |
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://cloud.computervision.com.vn/api/v2/ocr/vehicle?img=%s&format_type=url&get_thumb=false"% image_url,auth=(api_key, api_secret))print(response.json())
2. Extract information of vehicle documents with image file or pdf file input
API:
Method | URL | content-type |
---|---|---|
POST | https://cloud.computervision.com.vn/api/v2/ocr/vehicle | 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://cloud.computervision.com.vn/api/v2/ocr/vehicle?format_type=file&get_thumb=false",auth=(api_key, api_secret),files={'img': open(image_path, 'rb')})print(response.json())
3. Extract information of vehicle documents with JSON input
API:
Method | URL | content-type |
---|---|---|
POST | https://cloud.computervision.com.vn/api/v2/ocr/vehicle | 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/vehicle?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}
The data
field is an array, each element in the array corresponds to the information a page in a pdf file or an extracted document image.
Each element in the array will be a JSON with the following format:
{"type": string,"info": object}
type
: Type of document in the Vehicle documents to which information is extracted.
vehicle_registration_front
vehicle_registration_back
picertificate
driving_license
info
: Including extracted information, for each type of document, there will be different information returned.
Vehicle registration front - vehicle_registration_front
name
name_confidence
address
address_confidence
id
id_confidence
plate
plate_confidence
issued_at
issued_at_confidence
image
Vehicle registration back - vehicle_registration_back
name
name_confidence
address
address_confidence
address_town_code
address_district_code
address_ward_code
address_town
address_district
address_ward
engine
engine_confidence
chassis
chassis_confidence
brand
brand_confidence
model
model_confidence
color
color_confidence
capacity
capacity_confidence
issued_at
issued_at_confidence
issued_at_code
last_issue_date
last_issue_date_confidence
first_issue_date
first_issue_date_confidence
plate
plate_confidence
pay_load
pay_load_confidence
year_of_manufacture
year_of_manufacture_confidence
lie
lie_confidence
sit
sit_confidence
stand
stand_confidence
image
Vehicle registry - picertificate
chassis_number
chassis_number_confidence
commercial_use
commercial_use_confidence
design_pay_load
design_pay_load_confidence
design_towed_mass
design_towed_mass_confidence
engine_number
engine_number_confidence
inside_cargo_container_dimension
inside_cargo_container_dimension_confidence
issued_on
issued_on_confidence
issued_on_code
life_time_limit
life_time_limit_confidence
manufactured_country
manufactured_country_confidence
manufactured_year
manufactured_year_confidence
mark
mark_confidence
model_code
model_code_confidence
modification
modification_confidence
permissible_no
permissible_no_confidence
regis_date
regis_date_confidence
registration_number
registration_number_confidence
seri
seri_confidence
tire_size
tire_size_confidence
type
type_confidence
valid_until
valid_until_confidence
wheel_form
wheel_form_confidence
capacity
capacity_confidence
report_number
report_number_confidence
authorized_pay_load
authorized_pay_load_confidence
lying_place
lying_place_confidence
seat_place
seat_place_confidence
stand_place
stand_place_confidence
image
Driving license - driving_license
id
name
dob
class
nationality
issue_date
due_date
address
address_town
address_district
address_ward
address_town_code
address_district_code
address_ward_code
id_confidence
name_confidence
dob_confidence
class_confidence
nationality_confidence
issue_date_confidence
due_date_confidence
address_confidence
id_box
name_box
dob_box
class_box
nationality_box
issue_date_box
due_date_box
address_box
image
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 |