China Passport OCR: Extract Fields with Python

China document intake: what needs review

Preserve the distinction between printed local-script names and the Latin spelling used for travel records. 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 China document evidence into your backend

Capture the full identity page, including the visual fields and machine-readable area. Keep entry stamps and visa pages out of the input used for passport data. Compare ambiguous names or dates against the source; OCR is not chip authentication. Send the image to the passport 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.

A reviewable intake workflow

• China document intake: Preserve the distinction between printed local-script names and the Latin spelling used for travel records.
• Map fields without losing their meaning: Store passport_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 nationality separate from issuing country and place of birth.

Python request for China passport 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("china-passport.jpg", "rb") as source:
    encoded = base64.b64encode(source.read()).decode("ascii")

response = requests.post(
    "https://api.structocr.com/v1/passport",
    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 = ["passport_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})

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": {
    "country_code": "CHN",
    "passport_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,
    "nationality": "CHN"
  }
}