France Driver License OCR: Extract Fields with Python
Extract visible fields from France driver license images into JSON. Map identifiers, names and dates, with a review workflow for incomplete results.
France document intake: what needs review
Keep the permis de conduire number separate from numbered field labels. Retain accents in holder names and review category-specific dates separately. In a production intake, keep the uploaded document associated with the correct application record before extraction. A legible name alone does not establish that the number, dates and address were captured correctly. Avoid filling missing values from a previous booking or a customer profile without recording that separate source.
Map France document evidence into your backend
Check the document type, printed issuing region and date labels before using the result. Keep licence class and any visible restrictions available for review. OCR reads evidence from a card; it does not check a live driving record or determine vehicle eligibility. Send the image to the driver license API and keep extracted evidence separate from your approval decision. The same endpoint handles the submitted image; the article's country or state context does not force the API to return that jurisdiction. Compare the returned country with the source before saving the result. For coverage, pricing, and the full field list, see the driver license OCR API overview, or try a photo in the free online driver license scanner.
A reviewable intake workflow
- France document intake: Keep the permis de conduire number separate from numbered field labels. Retain accents in holder names and review category-specific dates separately.
- Map fields without losing their meaning: Store document_number as text, keep surname and given_names in their own fields, and retain source images according to your document-handling policy. Date parsing failures should be reviewable instead of becoming today's date.
- Compare a resubmitted document: Keep a prior extraction and a new extraction as separate events. A change in number, name or expiry should produce a review item, not an automatic overwrite of a trusted record.
- Export only the fields your workflow uses: Map the response to your form explicitly. Keep the licence class separate from vehicle registration, insurance and employer approval.
Python request for France driver license OCR
This REST example sends a local image as Base64 JSON. Run it on a backend and keep the API key in an environment variable. The printed example below is deliberately synthetic and is not a valid document-number format specimen.
Prerequisite: Python 3, pip install requests; STRUCTOCR_API_KEY set on the server
import base64
import os
import requests
with open("france-driver-license.jpg", "rb") as source:
encoded = base64.b64encode(source.read()).decode("ascii")
response = requests.post(
"https://api.structocr.com/v1/driver-license",
headers={"x-api-key": os.environ["STRUCTOCR_API_KEY"]},
json={"img": encoded},
timeout=60,
)
response.raise_for_status()
result = response.json()
if not result.get("success"):
raise RuntimeError("Extraction was not successful; inspect the response securely")
data = result.get("data") or {}
required = ["document_number", "surname", "date_of_expiry"]
missing = [field for field in required if not data.get(field)]
# Queue incomplete records; do not log identity data in production.
print({"needs_review": bool(missing), "missing_fields": missing})Technical Specs
- •Endpoint: POST /v1/driver-license
- •Authentication: Server-side x-api-key header
- •Input: Base64 image in JSON img; use a readable JPG, PNG or WebP for this example
- •File size: Up to 4.5MB decoded
- •Standard processing: 2 credits per scan
- •Output: JSON; retain incomplete results for review
Key Features
- •Local extraction concern: Keep the permis de conduire number separate from numbered field labels. Retain accents in holder names and review category-specific dates separately.
- •Identifiers: Keep strings intact; do not coerce document numbers into numeric spreadsheet columns.
- •Dates: Validate date syntax and labels. An unexpected value needs source review, not silent correction.
- •Image evidence: Preserve all card or page edges, reduce glare and avoid cropping small text.
Illustrative response fields
Synthetic subset of the response for mapping purposes. Values and dates are examples, not a real scan or an assertion about document validity periods. Actual fields depend on the submitted document.
{
"success": true,
"data": {
"type": "drivers_license",
"region": null,
"country_code": "FRA",
"document_number": "EXAMPLE-NOT-A-REAL-ID",
"surname": "EXAMPLE",
"given_names": "PERSON",
"date_of_birth": "1990-01-15",
"date_of_issue": "2024-04-12",
"date_of_expiry": "2029-04-12",
"issuing_authority": null,
"vehicle_class": null,
"address": null,
"extra_details": {}
}
}Frequently Asked Questions
What is the main concern with France driver license intake?
Keep the permis de conduire number separate from numbered field labels. Retain accents in holder names and review category-specific dates separately.
Does extracting a number verify the document?
No. Extraction returns visible data. Authenticity checks, live registry checks and the final onboarding decision are separate processes.
What should happen when a date or name is unreadable?
Keep the record pending and request a clearer image or a manual review. Do not infer a date from an account profile or shorten a name to make it match.
Where should I check document-format references?
Use the PRADO public document reference collection as a starting point for document-format research, together with the issuing authority. Public collections may not include every country or current card version.
Can the same workflow run without Python?
Yes. Any backend that can send an authenticated JSON request can call /v1/driver-license. See the API reference for the current response contract.
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