🌐 Company Site - Here
🤗 Hugging Face - Here
🛟 Help Center - Here
🐳 Docker Hub - Here
Ready in ~10 minutes (after Drive download or Docker Hub pull): Fastest:
docker pull faceplugin/document-reader:latest→ run → copyFPMC1.…→ activate. From source: put files inlib/cpu/→./run.sh→ Postman /python3 demo.py. Jump: Start the API · Download runtime · About SDK
Explore FacePlugin Document Reader SDK — ID cards, passports, driver licenses with OCR, MRZ, barcode and optional NFC/RFID.
This is an on-premise FacePlugin SDK. All processing stays on your server — no biometric data is sent to FacePlugin cloud.
Standalone repository — pull Docker Hub (no Drive) or clone this repo, fill lib/cpu/ from Google Drive, and run. No other FacePlugin repository is required.
One repository for Linux SDK + Docker. The native libraries are linux/amd64; the Docker image runs on Linux, Windows, and macOS hosts via Docker (Apple Silicon uses amd64 emulation).
API server in Docker — test with Postman, curl, or the local Gradio demo (demo.py).
| Feature | Supported |
|---|---|
| ID Card / Passport / Driver License | ✓ |
| MRZ / Barcode / QR / OCR | ✓ |
| Document detection & classification | ✓ |
| Auto-capture & image quality | ✓ |
| Face extraction from document | ✓ |
| NFC / RFID (where available) | ✓ |
| Platform | Repository |
|---|---|
| Android | DocumentReader-Android-App |
| iOS | DocumentReader-iOS-App |
| Windows | DocumentReader-Windows-App |
| Linux / Docker | ID-Document-Recognition |
ID-Document-Recognition is one repository: Linux SDK runtime + Docker image (same tree).
| Step | What you need |
|---|---|
| 1 | A Linux host or Docker (Desktop or Engine) |
| 2 | Docker Hub pull does not need Drive. Fill ./lib/cpu/ only for Compose / ./run.sh — see Download runtime libraries |
| 3 | You do not need a license to start the API for the first time. Simply launch it without a key, then locate the machine code ( FPMC1.…) in the logs or via GET /api/machinecode. Submit this code to FacePlugin(contact) to get activation key ( FP1.…) and unlock product endpoints. |
You do not need a license to start the API once. Product endpoints unlock after you activate.
| Item | Minimum | Recommended |
|---|---|---|
| CPU | 2 cores | 8 cores |
| RAM | 4 GB | 8 GB |
| Disk | 4 GB | 8 GB |
| OS | Ubuntu 20.04+ (x86_64) | Ubuntu 22.04 / 24.04 |
| GPU (optional) | — | — (CPU-only product) |
You can start without a license — the server prints your machine code on startup.
The API starts even if activation fails. Copy the machine code (FPMC1.…) from the log and send it to FacePlugin.
Runtime is already inside the image.
sudo docker pull faceplugin/document-reader:latest
docker run -d --name faceplugin-document-reader \
--shm-size=2gb --privileged \
-p 8082:8082 \
-v /etc/machine-id:/etc/machine-id:ro \
faceplugin/document-reader:latest
sudo docker logs -f faceplugin-document-reader
# Look for the machine code line: FPMC1.…On Linux, add -v /etc/machine-id:/etc/machine-id:ro to the docker run above so the machine code stays on that host. Then start another container with a new name and host port — same image, same FP1.… key:
sudo docker run -d --name faceplugin-document-reader-2 \
--shm-size=2gb --privileged \
-p 8083:8082 \
-v /etc/machine-id:/etc/machine-id:ro \
faceplugin/document-reader:latestActivate on each host port with the same key. On Docker Desktop (macOS/Windows) skip the machine-id volume; each container may need its own license.
Skip this if you used Docker Hub (docker pull / docker run). Runtime is already inside the image.
The ./lib/ tree is intentionally empty on GitHub because native binaries and model files are too large.
If you are building or running directly from this repository, download the CPU package into ./lib/cpu/. DocumentReader is CPU-only — there is no gpu/ package.
DocumentReader-Linux-App runtime (Google Drive)
- Clone the repo (if you have not already):
git clone https://github.com/Faceplugin-ltd/ID-Document-Recognition.git
cd ID-Document-Recognition- Open the Google Drive folder from Where to download.
- Download all files in that folder (Drive: select all → Download, or download as a zip).
- Put every file into
./lib/cpu/— not inside a nested subfolder undercpu/.
Correct layout (CPU-only; no gpu/):
ID-Document-Recognition/
└── lib/
└── cpu/
├── libDocSDK.so
├── libDocumentEngine.so
├── dcr.fpk
└── .. (other files from Drive)
Wrong layout: lib/cpu/SomeFolder/libDocSDK.so (an extra nested folder breaks Docker build and local runs).
- Quick check:
ls lib/cpu/libDocSDK.so
ls lib/cpu/libDocumentEngine.so
ls lib/cpu/dcr.fpkIf those paths exist, you are ready to start.
Requires ./lib/cpu/ filled from Drive.
cd ID-Document-Recognition
# macOS/Windows Docker Desktop: remove the /etc/machine-id volume from docker-compose.yml first
sudo docker compose up --build -d
sudo docker compose logs -f
# Look for the machine code line: FPMC1.…
# Detached Compose has no TTY — there is no license prompt. Activate with curl (below).Requires ./lib/cpu/ filled from Drive.
cd ID-Document-Recognition
./run.sh
# or: python3 app.py
# The machine code (FPMC1.…) is printed in the terminal on startup.Licenses are offline and bound to your app identifier.
- Start the server (above) — Docker or local. A license is not required for the first start.
- Copy the machine code from the startup log (container logs or the local terminal). It looks like
FPMC1.…. - Send that machine code to FacePlugin (contact). We will issue an your license key license for that code.
- Activate with the license key:
# Paste the FP1. key into ./license.txt (overwrite the file).
# Docker Hub (A) and Compose (B) both expose the API on this host port.
# `docker compose up -d` does not activate — the container is already running
# with no TTY, so it will not re-read license.txt. POST the key instead:
curl -s -X POST http://127.0.0.1:8082/api/activate \
-H 'Content-Type: text/plain' \
--data-binary @license.txt
# Compose alternative: after writing license.txt, restart so startup activates:
# sudo docker compose restart
# Local (Option C): stop the process (Ctrl+C), then:
./run.shUse the machine code from the environment you will run in production. Docker and local host codes are different — if you run in Docker, send the Docker machine code.
curl -s http://127.0.0.1:8082/api/healthImport [postman/DocumentReader-API.postman_collection.json](postman/DocumentReader-API.postman_collection.json).
Default base URL: http://127.0.0.1:8082
Canonical protocol: /api/* (see FacePlugin Protocol). No version segment in route paths.
The Docker image is API/SDK server only (no Gradio). For a simple browser test UI on the host (API must already be running on port 8082):
pip3 install -r requirements-demo.txt
DEMO_PORT=9002 API_BASE=http://127.0.0.1:8082 python3 demo.pyOpen http://127.0.0.1:9002. Examples when present: assets/examples/samples/.
The Result tab shows document status plus an extracted-field table (OCR / MRZ / Barcode). The Images tab shows portrait / signature / cropped pages from the API. The Raw JSON tab shows the full API response.
Use the Python bindings in [sdk.py](sdk.py). Return code 0 means success.
First, obtain the machine code for activation and request a license based on the machine code.
import sdk
machine_code = sdk.get_machine_code()
print("machineCode:", machine_code) # FPMC1.…Next, activate the SDK with the path to your license file (license.txt containing your license key).
ret = sdk.activate("license.txt")If activation is successful, the return value will be 0. Otherwise, an error value will be returned.
After activation, call the initialization function of the SDK.
ret = sdk.init_sdk()If initialization is successful, the return value will be 0. Otherwise, an error value will be returned.
result = sdk.document_process(
[{"image": base64_front}],
rfid="",
options={"response": {"OCR": "normal", "MRZ": "normal", "Barcode": "normal"}},
)
# Front + back (two images)
result = sdk.document_process(
[
{"image": base64_front, "page_idx": 0},
{"image": base64_back, "page_idx": 1},
],
rfid="",
options={"response": {"OCR": "normal", "MRZ": "normal", "Barcode": "normal"}},
)Optional session APIs (same opcodes as Android): sdk.start_new_session(), sdk.start_new_page(), sdk.unload().
result = sdk.general_process(base64_image, options={})- Face Recognition with Liveness Detection-Android (Java, Kotlin)
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