The development team is thrilled to announce the release of PixLab API 2, a massive upgrade to our machine vision and media processing platform with now featuring a brand-new API Portal and over 150 powerful endpoints designed for businesses, developers, and creators.

From document extraction APIs, background removal, and dynamic PDF creation plus a brand new Vision Platform backed by state-of-the-art vision-language models, PixLab API 2 offers unmatched capabilities to analyze, transform, and automate visual content at scale.

👉 Explore the new API Portal now: pixlab.io/api-portal

👉 Explore the comprehensive list of API endpoints and their documentation: pixlab.io/api-endpoints

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What’s New in PixLab API 2?

✅ All-New Developer Portal

• Modern UI for key management, usage monitoring, and testing API calls in real time.
• Comprehensive API Reference & Endpoint List with code samples and quickstart guides for every service.

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🔍 Featured API Categories & Endpoints

ID Scan & Extract API

Scan official documents effortlessly with PixLab’s ID Scan & Extract API: - Comprehensive ID Support: Quickly scan & extract data from passports, driver's licenses, and 11,000+ document types from 197+ countries. - Structured JSON Output: Get parsed ID fields (name, DOB, MRZ, face, etc.) in a clean, machine-readable format.

👉 Explore DOCSCAN Documentation

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FACEIO – Face Recognition & Authentication

Secure and frictionless passwordless authentication: - Facial Login: Enable seamless access with facial authentication. - Liveness Detection: Block spoofing with advanced anti-fraud checks. - Age Verification: Instantly validate user age for compliance.

👉 FACEIO Integration Guide

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🖼️ Background Removal API

Remove image backgrounds with pixel-perfect precision: - Ultra-Fast Processing: Background-free images in seconds. - Automated & Scalable: Integrate into any web or mobile app.

👉 View Background Removal Docs

Try also the bulk version: BG Remove App ↗

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NSFW & Content Moderation API

Keep your platform safe and compliant: - Blur, Pixelate, or Block harmful images or frames. - Detect adult, violent, or graphic content using advanced AI models.

👉 Content Moderation Docs

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👁️‍🗨️ Vision-Language Models (VLMs)

Check out these insights from documents using Vision + NLP via the Vision Platform: - Document understanding with layout awareness - Great for invoices, contracts, ID cards, and more. Featured new Vision API endpoints:

• QUERY - Get natural language responses to image-related queries, and is documented at pixlab.io/endpoints/query

• DESCRIBE - Generate a natural language description of image content, and is documented at pixlab.io/endpoints/describe

• CHAT - An OpenAI compatible API (chat) interface, and powered by state-of-the-art LLM models. Documentation is available at: pixlab.io/endpoints/chat

👉 and a whole lot more Explore Vision APIs

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📄 Rich PDF Generation API

Create beautiful PDFs at scale:

• PDFGEN Endpoint: Convert HTML/Markdown to professional PDFs.
• PDFTOIMG Endpoint: Preview and convert PDFs to image formats, as documented here.

👉 View Rich PDF Generation APIs

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🛠️ Online Tools Backed by PixLab APIs

Explore our growing suite of web apps, each powered by PixLab’s infrastructure:

• Convert Box – Universal file format converter (HEIC, MP4, PDF…)
• Vision Workspace – AI office suite for OCR & document analysis
• AI Photo Editor – Edit photos via text prompts
• Annotate – Image annotation & segmentation
• BG-Remove – Bulk background remover
• App UI Maker – Mobile UI/UX views, interface, and code generator
• Tilemap Editor – 2D level editor for games
• Creative Toolbox – All-in-one visual creator's suite

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For Developers, Creators, and Businesses

PixLab API version 2 is now production-ready, SDK-free, and tightly integrated, making it ideal for:

• Fintechs & KYC providers
• E-commerce & SaaS platforms
• AI developers & researchers
• Content creators & automation teams

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🔑 Get Your API Key & Start Your Integration Phase

Head to the PixLab Console to:

• Generate your first API key
• Integrate with over 150+ endpoints
• Access complete documentation & live API testing tools

Join thousands of developers and businesses using PixLab to power the next generation of intelligent visual applications.

🧠 Build smarter, automate faster, and scale confidently with PixLab API 2.

— The PixLab Team

The PixLab Development Team is thrilled to announce the release of the next-generation DOCSCAN API, the core engine behind the newly rebranded PixLab ID Scan Platform.

Built from the ground up with Vision Language Models and hosted on the powerful PixLab Vision infrastructure, this update brings unmatched simplicity, security, and intelligence to identity document processing.

🌍 A Platform Re-imagined

Say goodbye to complex SDK integrations. The new DOCSCAN API requires no client-side SDKs, just a single HTTPS-enabled REST endpoint that supports both GET and POST requests. This means you can call DOCSCAN from any programming environment, whether you're using Python, Java, PHP, Go, or even a shell script.

• New Home Page: pixlab.io/id-scan-api/
• New Documentation: pixlab.io/id-scan-api/docscan

⚡ What's New in This Version?

✅ Powered by Vision Language Models

The new DOCSCAN API harnesses the full power of PixLab’s Vision Language Models to extract structured, high-quality data from scanned documents with increased accuracy and robustness.

✅ No SDK Required

Forget installing SDKs or maintaining device-specific libraries. DOCSCAN is pure REST—simple, fast, and universal.

✅ Single Endpoint Simplicity

Use a single, unified API endpoint for both document scanning and data extraction. No need to juggle multiple APIs or chained requests.

✅ Supports GET & POST

Whether you prefer URL-based GET requests or multipart POST uploads, DOCSCAN supports both with full flexibility.

✅ TLS 1.3 Secured

All API traffic is encrypted end-to-end using TLS 1.3, ensuring maximum security and compliance from the first byte.

🚀 Built for Developers

The updated documentation at pixlab.io/id-scan-api/docscan has been completely restructured to be developer-first. Clear examples, copy-ready code snippets, and real-world integration guides will help you get up and running in minutes.

🧩 Use Cases

• ID verification in finance, healthcare, or government
• Digital onboarding for apps and services
• Automated customer registration flows
• Global document scanning with consistent output formats

🛠 Start Building Today

Head to the PixLab Console to generate your API key and begin integrating the new DOCSCAN API in minutes.

Whether you're modernizing your on-boarding flow or automating ID verification at scale, the new DOCSCAN API offers unmatched speed, simplicity, and intelligence—without the SDK overhead.

🔗 Learn more: pixlab.io/id-scan-api/
📚 REST API Documentation: pixlab.io/id-scan-api/docscan

🌍 Universal Document Support

The DOCSCAN API provides robust support for a wide array of officially issued identification documents. This includes, but is not limited to:

• Passports
• ID Cards (Citizen ID, Resident ID, Immigration Card, etc.)
• Driving Licenses
• Visas
• Birth & Death Certificates

The API covers documents from nearly all UN-recognized countries, offering unparalleled versatility. This release expands the API's capabilities to handle over 11,094 ID document variations originating from more than 197 countries. Below is a list of supported countries by DOCSCAN :

• Afghanistan
• Albania
• Algeria
• Andorra
• Angola
• Antigua and Barbuda
• Argentina
• Armenia
• Australia
• Austria
• Azerbaijan
• Bahamas
• Bahrain
• Bangladesh
• Barbados
• Belarus
• Belgium
• Belize
• Benin
• Bhutan
• Bolivia
• Bosnia and Herzegovina
• Botswana
• Brazil
• Brunei
• Bulgaria
• Burkina Faso
• Burundi
• Cabo Verde
• Cambodia
• Cameroon
• Canada
• Central African Republic
• Chad
• Chile
• China
• Colombia
• Comoros
• Congo (Brazzaville)
• Congo (Kinshasa)
• Costa Rica
• Cote d'Ivoire
• Croatia
• Cuba
• Cyprus
• Czechia
• Denmark
• Djibouti
• Dominica
• Dominican Republic
• Ecuador
• Egypt
• El Salvador
• Equatorial Guinea
• Eritrea
• Estonia
• Eswatini
• Ethiopia
• Fiji
• Finland
• France
• Gabon
• Gambia
• Georgia
• Germany
• Ghana
• Greece
• Grenada
• Guatemala
• Guinea
• Guinea-Bissau
• Guyana
• Haiti
• Honduras
• Hungary
• Iceland
• India
• Indonesia
• Iran
• Iraq
• Ireland
• Israel
• Italy
• Jamaica
• Japan
• Jordan
• Kazakhstan
• Kenya
• Kiribati
• Kuwait
• Kyrgyzstan
• Laos
• Latvia
• Lebanon
• Lesotho
• Liberia
• Libya
• Liechtenstein
• Lithuania
• Luxembourg
• Madagascar
• Malawi
• Malaysia
• Maldives
• Mali
• Malta
• Marshall Islands
• Mauritania
• Mauritius
• Mexico
• Micronesia
• Moldova
• Monaco
• Mongolia
• Montenegro
• Morocco
• Mozambique
• Myanmar
• Namibia
• Nauru
• Nepal
• Netherlands
• New Zealand
• Nicaragua
• Niger
• Nigeria
• North Korea
• North Macedonia
• Norway
• Oman
• Pakistan
• Palau
• Panama
• Papua New Guinea
• Paraguay
• Peru
• Philippines
• Poland
• Portugal
• Qatar
• Romania
• Russia
• Rwanda
• Saint Kitts and Nevis
• Saint Lucia
• Saint Vincent and the Grenadines
• Samoa
• San Marino
• Sao Tome and Principe
• Saudi Arabia
• Senegal
• Serbia
• Seychelles
• Sierra Leone
• Singapore
• Slovakia
• Slovenia
• Solomon Islands
• Somalia
• South Africa
• South Korea
• South Sudan
• Spain
• Sri Lanka
• Sudan
• Suriname
• Sweden
• Switzerland
• Syria
• Taiwan
• Tajikistan
• Tanzania
• Thailand
• Timor-Leste
• Togo
• Tonga
• Trinidad and Tobago
• Tunisia
• Turkey
• Turkmenistan
• Tuvalu
• Uganda
• Ukraine
• United Arab Emirates
• United Kingdom
• United States
• Uruguay
• Uzbekistan
• Vanuatu
• Vatican City
• Venezuela
• Vietnam
• Yemen
• Zambia
• Zimbabwe

The PixLab Optical Character Recognition team is thrilled to announce that its document scanning API endpoint /DOCSCAN, is now able to scan U.S. Driver’s licenses and driving permits issued by jurisdictions from all the 50 U.S. states.

The /DOCSCAN API endpoint now allows any Website that is presented with a U.S Driver’s License, International Passport or ID Card to verify that the inputted information by the end user matches those present on the submitted or uploaded ID document image.

Usage & Code Samples

Given an input U.S driver’s license image issued by any of the 50 U.S. states, crop the license holder face, and extract fields of interest as follow:

Input U.S driver’s license image Car Vectors by Vecteezy

Extracted Fields Showcase

The extracted fields after successful call to the /DOCSCAN API endpoint are:

• License holder cropped face. This image will be stored on an AWS S3 bucket of your choice if you connect your target bucket from the PixLab Console.
• Issuing Country (USA obviously).
• Issuing State Name.
• Issuing State Two-Letter Code.
• License Number.
• License Holder’s Full Name.
• License Holder’s Address.
• License Holder’s Date of Birth (yyyy-mm-dd).
• License Issuing Date (yyyy-mm-dd).
• License Expiry Date (yyyy-mm-dd).
• License Holder’s Gender.

The code samples that is used to achieve such results are available via the following Gists:

• Python Gist. Also available on the PixLab Gitub Repository:
• PHP Gist. Also available on the PixLab Gitub Repository:

Algorithms Under the hood

• Face extraction is automatically performed using the /FACEDETECT API endpoint.
• /DOCSCAN already supports GET & POST HTTP methods so you can upload your document images directly from your application without relying on a foreign server. Refer to this Gist on how to do so.
• Upon the image processed on our server, it is automatically deleted. We do not keep trace or any log of your input images.
• Internally, we mainly rely on PP-OCR which is a practical ultra-lightweight OCR system that is mainly composed of three parts: Text Detection, Bounding Box Isolation, & Text Recognition. This combination produces highly accurate results in less than 5 seconds of processing.

Further Reading

• The official endpoint documentation is available to consult here, and the reader is more than encouraged to take a look at our production ready, code samples, available in various programming languages on the PixLab Code Samples Page.

The PixLab Document Scanner, development team is pleased to announce that is now fully support scanning Emirates (UAE) ID & Residence Cards via the /DOCSCAN API endpoint at real-time using your favorite programming language.

When invoked, the /DOCSCAN HTTP API endpoint shall Extract (crop) any detected face and transform the raw UAE ID/Residence Card content such as holder name, nationality, ID number, etc. into a JSON object ready to be consumed by your app.

Below, a typical output result of the /DOCSCAN API endpoint for an Emiratis (UAE) ID card input sample:

The code samples used to achieve such result are available to consult via the following gists:

• Python Code Samples for Scanning UAE ID Card: uae_emirates_id_card_scan.py
• PHP Code Samples for Scanning UAE ID Card: uae_emirates_id_card_scan.php
• PixLab Github Repository: github.com/symisc/pixlab

The same logic applies to scanning official travel documents like Visas, Passports, and ID Cards from many others countries in an unified manner, regardless of the underlying programming language used on your backend (Python, PHP, Ruby, JS, etc.) thanks to the DOCSCAN API endpoint as shown in previous blog posts:

• Passports & Travel Document Scan: Blog Announcement & Code Sample.
• Malaysia & Singapore ID Card Scan: Blog Announcement & Code Sample.
• Aadhar India ID Card Scan: Blog Announcement & Code Sample.

Algorithm Details

Internally, PixLab's document scanner engine is based on PP-OCR which is a practical ultra-lightweight OCR system, mainly composed of three parts: DB text detection, detection frame correction, and CRNN text recognition. DB stands for Real-time Scene Text Detection.

The system adopts 19 effective strategies from 8 aspects including backbone network selection and adjustment, prediction head design, data augmentation, learning rate transformation strategy, regularization parameter selection, pre-training model use, and automatic model tailoring and quantization to optimize and slim down the models of each module.

In PP-OCR, Differentiable Binarization (DB) is used as text detector which is based on a simple segmentation network. It integrates feature extraction and sequence modeling. It adopts the Connectionist Temporal Classification (CTC) loss to avoid the inconsistency between prediction and label.

The algorithm is further optimized in five aspect where the detection model adopts the CML (Collaborative Mutual Learning) knowledge distillation strategy and CopyPaste data expansion strategy. The recognition model adopts the LCNet lightweight backbone network, U-DML knowledge distillation strategy and enhanced CTC loss function improvement, which further improves the inference speed and prediction effect.

A Passport is a document that almost everyone has at some point in their lives. It is issued by the country’s government to its citizens and mainly being used for traveling purposes. It also serves as proof of nationality, name, and more importantly an Universally Unique ID for its owner.

Many services have been long-time accepting passports as identification documents from their customers to complete their KYC (Know Your Customer) form as required by the legislation in force. This is especially true and enforced for the Finance, HR or Travel sectors. In most cases, a human operator will verify the authenticity of the submitted document and grant validation or reject it.

Things can get really complicated if you have hundreds of KYC forms to checks, but also if your clients differ in nationality. Quickly, you will find yourself drowning in physical copies of passports in different languages that you can not even understand. Let alone the potential legal problems you can face with passport copies laying around the office. This is why, an automated & safe solution for Passports processing is required!

Modern Passport Structure

From the 1980s on wards, most countries started issuing passports containing an MRZ. MRZ stands for the Machine Readable Zone and is usually located at the bottom of the Passport as shown below:

Passports that contain an MRZ are referred to as MRPs, machine-readable passports (Almost all modern issued Passports have one). The structure of the MRZ is standardized by the ICAO Document 9303 and the International Electro-technical Commission as ISO/IEC 7501-1.

The MRZ is an area on the document that can easily be read by a machine using an OCR Reader Application or API. It’s not important for you to understand how it works, but if you look at it carefully, you will see that it contains most of the relevant information on the document, combined with additional characters and a checksum that can be extracted programmatically and automatically via API as we will see in the next section.

Once parsed, the following information are automatically extracted from the target MRZ and made immediately available to your app, thanks to the /docscan API endpoint:

• issuingCountry: The issuing country or organization, encoded in three characters.
• fullName: Passport holder full name. The name is entirely upper case.
• documentNumber: This is the passport number, as assigned by the issuing country. Each country is free to assign numbers using any system it likes.
• checkDigit: Check digits are calculated based on the previous field. Thus, the first check digit is based on the passport number, the next is based on the date of birth, the next on the expiration date, and the next on the personal number. The check digit is calculated using this algorithm.
• nationality: The issuing country or organization, encoded in three characters.
• dateOfBirth: The date of the passport holder's birth in YYMMDD form. Year is truncated to the least significant two digits. Single digit months or days are perpended with 0.
• sex: Sex of the passport holder, M for males, F for females, and < for non-specified.
• dateOfExpiry: The date the passport expires in YYMMDD form. Year is truncated to the least significant two digits. Single digit months or days are perpended with 0.
• personalNumber: This field is optional and can be used for any purpose that the issuing country desires.
• finalcheckDigit: This is a check digit for positions 1 to 10, 14 to 20, and 22 to 43 on the second line of the MRZ. Thus, the nationality and sex are not included in the check. The check digit is calculated using this algorithm.

Automatic Passport Processing

Fortunately for the developer wishing to automate Passports scanning, PixLab can automatically scan & extract passport MRZ but also help to detect possible fraudulent documents. This is made possible thanks to the /docscan API endpoint which let you in a single call scan government issued documents such as Passports, Visas or ID Cards from various countries.

Besides extracting MRZ, the /docscan API endpoint shall automatically crop any detected face and transform binary Machine Readable Zone into stream of text content (i.e. full name, issuing country, document number, date of expiry, etc.) ready to be consumed by your app in the JSON format.

Below, a typical output result of the /docscan endpoint for a passport input image:

What follow is the gist used to achieve such result:

Other document scanning code samples are available to consult via the following Github links:

• Python code for scanning Passports: passport_scan.py.
• PHP code for scanning Passports: passport_scan.php.

Face extraction is automatically performed using the /facedetect API endpoint. For a general purpose Optical Character Recognition engine, you should rely on the /OCR API endpoint instead. If you are dealing with PDF documents, you can convert them at first to raw images via the /pdftoimg endpoint.

Conclusion

The era we are in is more digitized than ever. Tasks that are repetitive are slowly being replaced by computers and robots. In many cases, they can perform these tasks faster, with a smaller amount of mistakes and in a more cost-effective manner. At PixLab we focus on building software to replace manual repetitive labor in administrative business processes. The processing and checking of passports can be very time-consuming. Using /docscan to automate your passport processing will enable you to save cost, on-board customers faster and reduce errors in administrative processes.

The PixLab development team is pleased to announce the immediate availability of the PixLab API 1.9.72.

Since its launch on 2017, PixLab have already processed over 450 Millions of users contents whether static images, GIF or Videos Frames. This milestone release introduces new API endpoints, various minor bug fixes, processing speed improvements by up to 5% and many innovative features. Let's start with the one we are existed about in no particular order:

• Passports & ID Cards Scan: While documents scanning were introduced in earlier version of the PixLab API via the /docscan endpoint. This release pushes further the accuracy of the OCR engine. A 5MB raw Passport sample now takes less than 3 seconds to execute including face detection & extraction, MRZ (Machine Readable Zone) extraction and finally transformation of the Raw MRZ data into textual content. You can try out the accuracy of the Passport scanning engine using these Python and PHP scripts to see it in action.
• DNS infrastructure moved to Cloudflare for faster than ever response times.
• Full support for HTTP/2 and HTTP/3 (QUIC).
• Up to three layers of redundancy for the standard PixLab OCR engine for faster, accurate & guaranteed scan results.
• A fresh update of the adult & gore content detection ML model which is used to power the famous PixLab /NSFW API endpoint that have already analyzed over 100 millions of user contents with high accuracy.
• Face Detection (including facial landmarks extraction) & Emotion Pattern (including gender & age) extraction are now using the RetinaFace Model which scores the highest on the LFW dataset.
• The /docscan API endpoint now fully support scanning ID cards from Malaysia & Singapore and many other countries (at users request) as well the brand new India Aadhar ID card. Find out more information about Aadhard fully support via our blog announcement here.
• Finally, a brand new, high performance custom image processing layer written in C/C++ and powered by ImageMagick and our Embedded computer Vision Library SOD is integrated directly into our cloud API.

Pixlab customers are more than advised to take a look at The official API endpoints documentation, The Samples Page, The Github repository for additional information.

Finally, for potentially interested users, you are more than welcome to start a 7 days free trial to see the API in action. Simply head to the PixLab Dashboard and activate your free trial from there.

The PixLab OCR team is pleased to introduce the /docscan API endpoint which let you in a single call scan government issued documents such as Passports, Visas or ID Cards from various countries.

Besides its accurate text scanning capabilities, the /docscan API endpoint shall automatically extract any detected face and transform binary data such as Passport Machine Readable Zone (MRZ) into stream of text payload (i.e. full name, issuing country, document number, date of expiry, etc.) ready to be consumed by your app in the JSON format.

Below, a typical output result of the /docscan endpoint for a passport input image:

The code samples used to achieve such result are available to consult via the following Github links:

• Python code for scanning Passports: passport_scan.py.
• PHP code for scanning Passports: passport_scan.php.

Face extraction is automatically performed using the /facedetect API endpoint. For a general purpose Optical Character Recognition engine, you should rely on the /OCR endpoint instead. If you are dealing with PDF documents, you can convert them at first to raw images via the /pdftoimg endpoint.

Below, a typical Python code snippet for scanning passports:

import requests
import json

# Given a government issued passport document, extract the user face and parse all MRZ fields.
#
# PixLab recommend that you connect your AWS S3 bucket via your dashboard at https://pixlab.io/dashboard
# so that any cropped face or MRZ crop is stored automatically on your S3 bucket rather than the PixLab one.
# This feature should give you full control over your analyzed media files.
#
# https://pixlab.io/#/cmd?id=docscan for additional information.

req = requests.get('https://api.pixlab.io/docscan',params={
    'img':'https://i.stack.imgur.com/oJY2K.png', # Passport sample
    'type':'passport', # Type of document we are a going to scan
    'key':'Pixlab_key'
})
reply = req.json()
if reply['status'] != 200:
    print (reply['error'])
else:
    print ("User Cropped Face: " + reply['face_url'])
    print ("MRZ Cropped Image: " + reply['mrz_img_url'])
    print ("Raw MRZ Text: " + reply['mrz_raw_text'])
    print ("MRZ Fields: ")
    # Display all parsed MRZ fields
    print ("\tIssuing Country: " + reply['fields']['issuingCountry'])
    print ("\tFull Name: "       + reply['fields']['fullName'])
    print ("\tDocument Number: " + reply['fields']['documentNumber'])
    print ("\tCheck Digit: "   + reply['fields']['checkDigit'])
    print ("\tNationality: "   + reply['fields']['nationality'])
    print ("\tDate Of Birth: " + reply['fields']['dateOfBirth'])
    print ("\tSex: "           + reply['fields']['sex'])
    print ("\tDate Of Expiry: "    + reply['fields']['dateOfExpiry'])
    print ("\tPersonal Number: "   + reply['fields']['personalNumber'])
    print ("\tFinal Check Digit: " + reply['fields']['finalcheckDigit'])

Finally, the official endpoint documentation is available to consult at pixlab.io/cmd?id=docscan and a set of working samples in various programming language are available at the PixLab samples pages.

The PixLab OCR team is pleased to announce that is now fully support scanning India Aadhar ID Cards besides Malaysia (MyKad) and Singapore identity cards as well governments issued Passports from all over the world via the /docscan API endpoint.

When invoked, the /docscan API endpoint shall Extract (crop) any detected face and transform the raw Aadhar ID card content such as holder name, gender, date of birth, ID number, etc. into a JSON object ready to be consumed by your app.

Below, a typical output result of the /docscan API endpoint for a Aadhar ID card input sample:

The same API call applies for Passports as well different ID cards from supported countries (you just specify the country name or ISO code):

The code samples used to achieve such result are available to consult via the following Github links:

• Python code for scanning Aadhar ID cards (as well other ID cards from different countries): id_card_scan.py.
• PHP code for scanning Aadhar ID cards: id_card_scan.php.
• Python code for scanning Passports: passport_scan.py.
• PHP code for scanning Passports: passport_scan.php.
• For converting PDF documents to raw images, you can rely on the /pdftoimg API endpoint as shown in this Python or PHP gist.

Face extraction is automatically performed using the /facedetect API endpoint. If you are dealing with PDF documents, you can convert them at first to raw images via the /pdftoimg endpoint.

Finally, the official endpoint documentation is available to consult at pixlab.io/cmd?id=docscan and a set of working samples in various programming language are available at the PixLab samples pages.

The PixLab OCR team is pleased to announce that it fully support now scanning ID cards from Malaysia (MyKad), Singapore, India Aadhaar, Emirates (UAE) ID & GCC Residence Card, US Driver's License, as well governments issued Passports from all over the world via the /docscan API endpoint.

Besides its robust text scanning features, the /docscan API endpoint shall Extract (crop) any detected face and transform the extracted text content such as ID card fields (name, ID number, address, etc.) or Passport Machine Readable Zone (MRZ) into JSON object fields ready to be consumed by your code.

Below, a typical output result of the /docscan endpoint for a Malaysian ID card (MyKad) input image:

The same applies for Passports:

The code samples used to achieve such result are available to consult via the following Github links:

• Python code for scanning ID cards: id_card_scan.py.
• PHP code for scanning ID cards: id_card_scan.php.
• Python code for scanning Passports: passport_scan.py.
• PHP code for scanning Passports: passport_scan.php.
• For converting PDF documents to raw images, you can rely on the /pdftoimg API endpoint as shown in this Python or PHP gist.

Face extraction is automatically performed using the /facedetect API endpoint. If you are dealing with PDF documents, you can convert them at first to raw images via the /pdftoimg endpoint.

Finally, the official endpoint documentation is available to consult at pixlab.io/cmd?id=docscan and a set of working samples in various programming language are available at the PixLab samples pages.