Nanonets is an AI-based workflow automation software centred around our revolutionary OCR engine. We have many pre-trained models to extract data from standard customer documents, Driver’s Licenses being one of them.
We can help extract structured information from Driver’s Licenses, including Name, Date of Birth, Sex, License Number, etc.
Note: Our pre-trained OCR model is optimised for US Driver’s Licenses but for extracting data from Driver’s Licenses of any other country, we recommend using our Zero-training OCR model, which can be set up within minutes and requires no training at all.
Here is more information on how you can use the Zero-Training Model.
The fields we support for US Driver's Licenses out-of-the-box are as follows:
| Field | Description |
|---|---|
| Issue_Date | Extracts the date the passport was issued on. |
| Height | Extracts the height of the individual. |
| Eye_Color | Extracts the eye colour of the individual. |
| Name | Extracts the first name of the individual. |
| State | Extracts the resident state of the individual. |
| DOB | Extracts the date of birth of the individual. |
| Weight | Extracts the weight of the individual. |
| Sex | Extracts the sex of the individual, (M/F/X). |
| DD_No | Extracts the security code that identifies where and when the license was issued. It uniquely identifies each card that was issued to a given individual. |
| Expiry_Date | Extracts the date the License is set to expire on. |
| Class | Denotes the class of vehicles the individual is authorised to drive. Class D is the most common. Other classes include Class A,B,C,H,N,P,S,T,X. |
| Address | Extracts the address of the individual. |
| License_No | Extracts the License number of the individual which acts as a unique identifier for the Driver’s License. |