🌐 Company Site - Here
🤗 Hugging Face - Here
🛟 Help Center - Here
🐳 Docker Hub - Here
Fastest:
docker pull faceplugin/document-reader:latest→ run → copy machine code → activate. Docker Hub: pull the image below → Postman / curl / Gradio demo. Need Compose or native? Contact us. Try online: Hugging Face Space (Gradio UI → your Linux API). Jump: Quick start · Start the API · SDK License · Company Overview · Setup · About SDK · Contact
- Download and run the appropriate Docker image from FacePlugin Docker Hub. See Option A for details.
- Confirm it is running:
curl -s http://127.0.0.1:8082/api/health(no license needed yet) - Contact us with your machine code to obtain a license key, then activate with
POST /api/activate— SDK License - Try it: Postman, curl, or local Gradio demo on 9002 (
python3 demo)
Docs: https://doc.faceplugin.com
FacePlugin ID Document Recognition SDK for Linux / Docker is a fully on-premise identity verification engine for ID cards, passports, and driver licenses. It runs OCR, MRZ reading, barcode and QR extraction, document detection and classification, image quality analysis, face extraction from the document, optional NFC/RFID, and authenticity / document liveness (security) checks.
All processing stays on your server. No biometric data is sent to FacePlugin cloud — built for KYC, eKYC, banking, and on-premise compliance workflows.
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. 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 (python3 demo) covering Result, Liveness, Images, and Raw JSON.
| Feature | Supported |
|---|---|
| ID Card, Passport, and Driver License recognition | ✓ |
| MRZ, Barcode, QR, and OCR data extraction | ✓ |
| Document detection and type classification | ✓ |
| Auto-capture and image quality analysis | ✓ |
| Face, portrait, and signature extraction from document | ✓ |
| NFC / RFID chip reading (where available) | ✓ |
| Platform | Repository |
|---|---|
| Android | ID-Document-Recognition-Android |
| iOS | ID-Document-Recognition-iOS |
| Windows | ID-Document-Recognition-Windows |
| Linux / Docker | ID-Document-Recognition-Docker (this repo) |
| React Native | ID-Document-Recognition-React-Native |
| Flutter | ID-Document-Recognition-Flutter |
| Ionic Capacitor | ID-Document-Recognition-Ionic-Capacitor |
| Ionic Cordova | ID-Document-Recognition-Ionic-Cordova |
| Linux / Docker (Liveness) | ID-Document-Liveness-Detection-Docker |
| Step | What you need |
|---|---|
| 1 | A Linux host or Docker (Desktop or Engine) |
| 2 | Docker Hub pull does not need Drive — see Option A |
| 3 | You do not need a license to start the API the first time. Copy the machine code from the logs or GET /api/machinecode. Send it to FacePlugin (contact) to get a license key 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 | 4 cores |
| RAM | 4 GB | 8 GB |
| Disk | 4 GB | 8 GB |
| OS | Ubuntu 20.04+ (x86_64) | Ubuntu 22.04 / 24.04 |
| GPU | — | — (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 from the log and send it to FacePlugin.
Runtime is already inside the image. No Google Drive step.
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 in the logs--shm-size=2gb is required (dcr.fpk extracts to /dev/shm). Keep --privileged and the /etc/machine-id volume as shown.
You only need this section if you want to run multiple DocumentReader containers on the same Linux host.
On Linux, mount /etc/machine-id into each container so they use the same machine code. Each container must have a different container name and host port.
For example:
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:latestYou can then activate each container using the same license key.
Note: On Docker Desktop (macOS/Windows), do not use the /etc/machine-id volume. Each container may require its own license.
Skip this if you used Docker Hub (docker pull / docker run). Runtime is already inside the image.
The ./lib/ tree is 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 runtime (Google Drive)
- Clone the repo (if you have not already):
git clone https://github.com/Faceplugin-ltd/ID-Document-Recognition-Docker.git
cd ID-Document-Recognition-Docker- Download all files from the Drive folder.
- Put every file into
./lib/cpu/— not inside a nested subfolder undercpu/.
ID-Document-Recognition-Docker/
└── lib/
└── cpu/
├── libDocSDK.so
├── libDocumentEngine.so
└── dcr.fpk
Wrong layout: lib/cpu/SomeFolder/libDocSDK.so.
ls lib/cpu/libDocSDK.so
ls lib/cpu/libDocumentEngine.so
ls lib/cpu/dcr.fpkThe steps above (Docker Hub) are enough for most teams. If you need Docker Compose with a local build, or a native Linux install without Docker Hub, contact FacePlugin and we will share the Drive runtime package and setup for your environment.
Licenses are offline and bound to your machine code.
- Start the server (above) with Docker Hub. A license is not required for the first start.
- Copy the machine code from the startup log. Copy it from the logs or
GET /api/machinecode. - Send that machine code to FacePlugin (contact). We will issue a license key for that code.
- Activate with the license key:
# Paste the license key into ./license.txt (overwrite the file).
# Detached Docker will not re-read license.txt on its own — POST the key:
curl -s -X POST http://127.0.0.1:8082/api/activate \
-H 'Content-Type: text/plain' \
--data-binary @license.txt
Use 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.
After activation, GET /api/licenseStatus reports what the key unlocks. The Gradio demo shows the same summary as License: … at the top of the page.
| Capability | Meaning |
|---|---|
| Recognition | OCR, MRZ, barcode/QR, and document type classification |
| Liveness (authenticity) | Document authenticity: physical document, security patterns, photo origin, barcode format |
Typical labels:
- Recognition + Liveness — full identity verification (Result + Liveness tabs)
- Recognition — OCR, MRZ, and barcode only; Security stays empty / not checked
- Liveness — authenticity / document liveness only; OCR/MRZ/barcode stays empty / not checked
- Not licensed — machine code only until you activate
Check status anytime:
curl -s http://127.0.0.1:8082/api/licenseStatusRequest authenticity in documentProcess with "Authenticity": "normal". "none" turns Liveness off. The demo and Postman default to "normal".
Live ZeroGPU Document Reader (OCR, MRZ, barcode, security) — same Linux SDK as this repo:
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/*. No version segment in route paths.
The Docker image is API/SDK server only (no Gradio). For a local FacePlugin Document Reader demo in the browser — Result, Liveness, Images, and Raw JSON — on the host (API must already be running on port 8082):
pip3 install -r requirements-demo.txt
./run_demo.shOr:
pip3 install -r requirements-demo.txt
DEMO_PORT=9002 API_BASE=http://127.0.0.1:8082 python3 demoOpen http://127.0.0.1:9002. Examples when present: assets/examples/samples/. The header shows License: (for example Recognition + Liveness) from /api/licenseStatus.
- Result — document type, country, verification, image quality, and OCR / MRZ / barcode fields
- Security — overall and per-page authenticity: photo origin, physical document, security patterns, barcode format (
Authenticity: "normal"; needs a Liveness-capable license) - Images — portrait, signature, ghost portrait, barcodes, and cropped pages
- Raw JSON — full
/api/documentProcessresponse for integration
Two paths. You do not need the Gradio demo in production.
HTTP (any language) — start the API (Option A above), then call:
curl -s -X POST http://127.0.0.1:8082/api/documentRecognition \
-H 'Content-Type: application/json' \
-d '{"images":[{"image":"<BASE64>"}]}'
curl -s -X POST http://127.0.0.1:8082/api/documentLiveness \
-H 'Content-Type: application/json' \
-d '{"images":[{"image":"<BASE64>"}]}'
curl -s -X POST http://127.0.0.1:8082/api/documentProcess \
-H 'Content-Type: application/json' \
-d '{"images":[{"image":"<BASE64>"}],"response":{"OCR":"normal","MRZ":"normal","Barcode":"normal","Authenticity":"normal"}}'Python in-process — keep lib/cpu/ beside [sdk.py](sdk.py):
import sdk
machine_code = sdk.get_machine_code() # machine code
sdk.activate("license.txt")
sdk.init_sdk()
result = sdk.document_process(
[{"image": base64_front}],
rfid="",
options={"response": {"OCR": "normal", "MRZ": "normal", "Barcode": "normal", "Authenticity": "normal"}},
)Use the Python bindings in [sdk.py](sdk.py). Return code 0 means success.
import sdk
machine_code = sdk.get_machine_code()
print("machineCode:", machine_code) # machine code
ret = sdk.activate("license.txt")
ret = sdk.init_sdk()
result = sdk.document_recognition([{"image": base64_front}])
result = sdk.document_liveness([{"image": base64_front}])
result = sdk.document_process(
[{"image": base64_front}],
rfid="",
options={"response": {"OCR": "normal", "MRZ": "normal", "Barcode": "normal", "Authenticity": "normal"}},
)
# Front + back
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", "Authenticity": "normal"}},
)
result = sdk.general_process(base64_image, options={})
print(sdk.get_license_status()) # recognition / authenticity flags + labelOptional session APIs: sdk.start_new_session(), sdk.start_new_page(), sdk.unload().
HTTP endpoints: /api/health, /api/machinecode, /api/licenseStatus, /api/backend, /api/activate, /api/documentRecognition, /api/documentLiveness, /api/documentProcess, /api/generalProcess.
FacePlugin builds on-premises biometric AI SDKs for face recognition, face liveness detection (presentation-attack detection), deepfake detection, ID document recognition (OCR / MRZ / barcode), ID document liveness, and full eKYC / identity verification workflows.
Deploy on your own servers, private cloud, or fully on-device. Biometric data never leaves your infrastructure. Face matching is NIST FRVT-evaluated; liveness targets iBeta Level 2 class PAD. License once for unlimited on-prem inference — no per-call fees.
- Website: faceplugin.com
- Docs: doc.faceplugin.com
- Hugging Face demo: ID-Document-Recognition-SDK
- Docker Hub: faceplugin/document-reader
Request a license, machine-code activation (machine code → license key), or integration help:






