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Art DesignTop 10 Best Passport Picture Software of 2026
Ranking roundup of top Passport Picture Software for compliant prints, with comparisons of Canva, Adobe Photoshop, and GIMP for editors.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Canva
Reusable design templates with automated crop and background workflows for photo exports.
Built for fits when teams need template-based photo throughput with automation and shared governance..
Adobe Photoshop
Editor pickActions plus scripting-driven batch export for repeatable background, crop, and retouch workflows.
Built for fits when teams need controlled, semi-automated passport photo edits with scripting and batch exports..
GIMP
Editor pickPython scripting via GIMP's procedural database enables repeatable crop and background workflows.
Built for fits when teams need deterministic, scripted passport photo exports without web governance requirements..
Related reading
Comparison Table
This comparison table evaluates passport picture software by integration depth, data model, and how each tool handles automation and API surface for provisioning and batch processing. It also highlights admin and governance controls such as RBAC, audit log coverage, configuration management, and extensibility that affects throughput and operational fit across teams. Use the table to compare tradeoffs across desktop editors and pipeline tools, including self-hosted and cloud-based options.
Canva
design workflowProvides an image editor and document export workflow that supports passport-style layouts and background handling via built-in templates and upload-to-canvas editing.
Reusable design templates with automated crop and background workflows for photo exports.
Canva can serve passport photo workflows by combining adjustable guidelines with fixed export settings for size and background. Batch production is practical when photo templates and layouts are treated as repeatable assets. Its data model maps images and layout elements into a design object that can be duplicated and exported per customer photo set.
A tradeoff is that deep admin governance depends more on workspace policies and role permissions than on fine-grained schema controls for photo-specific metadata. Automation is strongest for throughput via repeatable template operations rather than for pixel-verified compliance guarantees. A good usage situation is a team that needs consistent, template-driven photo creation with audit-friendly exports for customer fulfillment.
- +Template-driven passport layouts reduce per-photo manual rework
- +API and integrations support programmatic image-to-design workflows
- +Batch exports produce consistent sizes and background results
- +RBAC-style workspace roles limit who can edit shared templates
- –Hard compliance checks require external validation for regulations
- –Schema-level control over photo metadata is limited compared to DAM systems
- –Complex per-country rules need custom workflow design
Customer photo ops teams
Generate consistent passport images in batches
Fewer retakes and reprints
Product engineering teams
Automate photo creation via API workflows
More photos processed per day
Show 2 more scenarios
Design ops and agencies
Standardize client photo templates across workspaces
Lower template drift risk
Shared assets and role permissions keep edits controlled while exports stay consistent.
HR and relocation vendors
Bulk photo production for onboarding packs
Faster onboarding document assembly
Design-based exports can package photos into ready-to-print assets for onboarding timelines.
Best for: Fits when teams need template-based photo throughput with automation and shared governance.
More related reading
Adobe Photoshop
desktop image automationSupports batch processing, scripting, and pixel-level background removal for consistent passport photo outputs using repeatable actions or automated processing steps.
Actions plus scripting-driven batch export for repeatable background, crop, and retouch workflows.
Adobe Photoshop is used when passport photo output requires manual and scripted control over framing, background removal, and skin retouching. The layer model supports non-destructive edits, and guides plus rulers help enforce consistent crop geometry. Scripted actions and automation can apply transformations across a folder of images, and results export through common formats used for submission. Integration depth is strongest with file-based workflows and Adobe ecosystems, because the core passport logic is not represented as a governed schema.
A key tradeoff is that Photoshop does not provide a passport-photo data model with structured fields for face bounds, head size, and compliance rules. That means administrators must encode standards inside actions, presets, or scripts and ensure consistent input metadata. A common usage situation is a photo studio staff workflow where technicians process uploads locally, run an action for background and cropping, and export print-ready images with minimal rework.
- +Layer-based editing supports repeatable crop and background fixes
- +Actions and scripting enable batch transforms across image sets
- +Measurement tools and guides help enforce consistent framing geometry
- +Extensibility via scripting supports custom retouching and exports
- –No structured passport data schema for compliance fields
- –Automation relies on scripting conventions and input file discipline
- –Head-geometry compliance checks are not expressed as governed rules
- –RBAC and audit logs are not oriented around photo-rule administration
Photo studio production technicians
Batch-process customer passport photo files
Consistent exports with reduced rework
In-house creative operations
Custom compliance framing templates
Less manual measurement work
Show 2 more scenarios
Local agencies with automation teams
Scripted export to print and portals
Higher throughput per workstation
Automate file output formatting from standardized layers and naming rules.
Design-driven photographers
Non-destructive refinement per customer
Faster revisions during approval
Use layers to keep skin and background edits editable without breaking geometry.
Best for: Fits when teams need controlled, semi-automated passport photo edits with scripting and batch exports.
GIMP
open-source image batchOffers repeatable editing with batch modes and scripting to standardize passport photo background and cropping into consistent output dimensions.
Python scripting via GIMP's procedural database enables repeatable crop and background workflows.
GIMP provides a data model built around images, layers, channels, and selections, which maps well to template-driven photo cropping and background replacement. It can load and export common raster formats for throughput in offline queues. Automation uses the GIMP scripting API in Python and command-line invocation for non-interactive batch runs. Extensibility also includes plugin workflows that can add custom filters and export presets.
A tradeoff appears in integration depth for administration because GIMP does not provide built-in RBAC, audit logs, or a centralized job scheduler. Automation is practical for controlled local or workstation environments, but governance features must be implemented around the file system and process execution. GIMP fits when an organization already has an imaging queue and needs deterministic rendering, not when a web admin console is required.
- +Layer and channel data model supports template-accurate edits
- +Python scripting and batch mode enable deterministic exports
- +Command-line batch processing fits offline photo queues
- +Plugins and presets support repeatable filter stacks
- –No native RBAC or audit log for operator governance
- –Admin controls require external orchestration and filesystem controls
- –Interactive UI work can slow throughput without scripting discipline
Internal operations teams
Batch process queued ID photo files
Consistent photo outputs at scale
Imaging workflow engineers
Integrate into existing file-based pipelines
Higher automation throughput
Show 1 more scenario
Custom tool builders
Add custom ID photo filters
Reusable internal image processing
Extends GIMP with plugins to apply organization-specific background and sizing rules.
Best for: Fits when teams need deterministic, scripted passport photo exports without web governance requirements.
ImageMagick
CLI image transformsEnables deterministic resizing, cropping, and background manipulation through command-line transforms and scriptable pipelines suitable for high-throughput photo generation.
MagickWand and CLI options allow scripted crop, resize, and background composition for batch photo sets.
ImageMagick is a command-line image processing toolkit that can serve passport photo pipelines via scripted conversion and transformations. Its integration depth comes from stable CLI options and library APIs like MagickWand, which support batch workflows and custom processing chains.
The data model is file and pixel oriented, so implementations define their own validation and metadata schema around outputs. Automation and extensibility are driven through scripting, filters, and policy configuration, with governance handled via OS-level controls and ImageMagick policy rules.
- +Scriptable CLI supports batch resizing, cropping, and background generation
- +MagickWand API enables in-app passport photo transformation pipelines
- +Policy configuration can restrict delegates and file system access
- +Predictable parameters for format, DPI, and color management
- –No built-in passport validation schema for sizes and face framing
- –Automation requires custom orchestration around CLI and output artifacts
- –Governance and audit logging are not native to the image processing step
- –Throughput depends on external job scheduling and file IO design
Best for: Fits when engineering teams need automated passport photo transforms via CLI and APIs.
Cloudinary
API image transformationsProvides hosted image transformation APIs that can standardize size, crop behavior, and background preparation for passport-style images in automated workflows.
Parameterized transformation URLs that produce consistent crops, resizing, and format outputs from stored assets.
Cloudinary performs server-side image transformation for passport photos using a parameterized delivery API and transformation pipelines. Integration depth centers on versioned API endpoints, webhooks for asynchronous events, and SDK support that maps cleanly to a media asset data model.
Automation and API surface cover upload, transformation, delivery, and metadata operations with consistent schema objects for repeatable workflows. Admin and governance controls include account roles, API key scoping patterns, and audit log visibility for operational oversight.
- +Transformation API supports passport photo crops, resizing, and format conversion
- +Delivery URLs generate deterministic outputs from stored asset identifiers
- +Webhooks allow asynchronous processing flows for new uploads
- +SDKs map to the media asset data model for consistent automation
- +Metadata and tagging support structured governance for image assets
- –Passport compliance rules require custom validation logic outside transformations
- –High-throughput transformation design needs careful caching and CDN strategy
- –Role separation depends on correct key and environment configuration discipline
- –Audit log granularity may not cover every app-level workflow event
Best for: Fits when teams need programmable passport-photo transformations with auditable media workflows.
Imgix
image delivery APIDelivers image resizing and cropping transformations through an HTTP-based delivery model that supports consistent passport photo framing rules.
Deterministic transformation URLs that enable automated multi-size rendering without storing per-variant assets.
Imgix fits teams that generate and transform passport photos as managed image assets through an HTTP image API. Imgix focuses on a data model built around image delivery, caching, and transformation parameters that can be applied consistently across multiple jurisdictions.
Automation comes through its request-based parameterization, which reduces workflow state inside the system and pushes logic into URL templates and provisioning pipelines. Integration depth is strongest when passport workflows can treat each photo variant as a deterministic render and store source media plus transformation rules.
- +Request-time transformations via HTTP parameters support deterministic passport-photo variants.
- +Caching and CDN delivery reduce repeated processing for high photo throughput.
- +URL-based schema keeps transformation rules versionable in provisioning systems.
- +Extensible image pipeline supports multi-size outputs from a single source.
- –Passport-specific framing and background constraints require external validation logic.
- –Governance relies on controlled URL construction since policy is not an embedded workflow engine.
- –RBAC and audit log coverage are limited compared with full admin workflow platforms.
- –Complex per-user customization increases template sprawl in URL-generation code.
Best for: Fits when passport photo variants can be expressed as deterministic image transformations via API requests.
FastAPI
API orchestrationProvides a programmable API surface for building passport-photo automation services that wrap image normalization logic behind versioned endpoints.
Automatic OpenAPI generation with validation tied to Pydantic request and response models
FastAPI targets high-integration picture workflows by exposing typed HTTP endpoints and JSON schemas for passport image operations. Its Pydantic models define the data model for image inputs, transformation parameters, and validation results with predictable serialization.
The framework supports synchronous and async request handling, which helps drive throughput for bursty upload and processing APIs. Extensibility via dependency injection and middleware supports automation hooks, observability, and governance controls like authentication enforcement at the API layer.
- +Typed request and response schemas via Pydantic models
- +Fast async support for high-throughput upload and processing endpoints
- +Dependency injection centralizes shared validation and service wiring
- +Middleware hooks enable logging, auth enforcement, and audit capture
- +Clear OpenAPI output for provisioning external automation clients
- –No built-in passport image rules or background enforcement
- –Admin and RBAC require custom implementation and storage
- –Automation pipelines depend on external services and orchestration
- –Throughput needs careful image size limits and resource controls
- –Audit logging patterns require custom middleware and log plumbing
Best for: Fits when teams need API-first automation for passport images with strict schemas.
Python Imaging Library fork (Pillow)
image processing librarySupports programmatic image operations for deterministic resizing, masking, and background adjustment inside custom passport-photo automation code.
Composable image operations on PIL image objects enabling deterministic crop and background generation.
Python Imaging Library fork (Pillow) turns image handling into code-level automation by providing a Python API for load, transform, and validate raster assets. It supports face cropping workflows through composable operations like resizing, padding, and applying deterministic background fills for common passport layouts.
The data model is filesystem- or byte-stream centric since images and metadata are passed as PIL image objects, so schema design and validation live in the integration code. Admin and governance controls are not built into Pillow, so RBAC, audit logging, and environment isolation must be implemented in the surrounding service.
- +Deterministic image transforms via Python API for reproducible passport output
- +Direct control over crop, resize, and padding pixel math
- +Runs in the same process as custom validation and compliance checks
- +Extensible with Python plugins for organization-specific processing steps
- –No built-in passport templates or output schema enforcement
- –No admin RBAC or audit log features inside the library
- –Throughput depends on integration architecture and image decoding settings
- –Face detection is not included, requiring external models or services
Best for: Fits when a team needs code-driven passport image processing with custom validation and templates.
OpenCV
computer vision pipelineEnables automated face detection, alignment, and geometry normalization that can be used to enforce passport-photo framing rules in pipelines.
Face detection and landmark-based alignment primitives for consistent head pose normalization.
OpenCV implements computer vision primitives like face detection, landmark estimation, and geometric transforms that can generate passport-style crops. It supports scriptable automation through Python and C++ APIs, with configuration driven by code-level parameters.
The data model is file and image based, so workflows typically manage metadata like output size and background via application schemas. Admin and governance controls are not part of the library, so teams add RBAC, audit logging, and sandboxing around their own services.
- +Face detection and cropping primitives for passport-like framing
- +Python and C++ APIs for high automation and batch throughput
- +Deterministic image transforms for consistent output geometry
- +Extensible pipeline using custom filters and heuristics
- –No built-in passport schema or output validation rules
- –Admin controls like RBAC and audit logs require external services
- –Quality constraints need custom landmark and pose tuning
- –Throughput depends on host engineering for concurrency and scaling
Best for: Fits when teams build a passport automation service with custom validation, controls, and pipelines.
Shopify Flow
workflow automationCreates rule-based automation for routing uploaded images through downstream photo-normalization steps using Shopify integrations and webhooks.
App actions embedded in Flow workflows let store events trigger cross-app steps.
Shopify Flow fits Shopify merchants who need multi-step automation tied to store events and app actions. It uses a visual workflow builder with triggers, conditions, and actions that operate on Shopify and connected app data.
The automation surface connects to app extensions and Shopify APIs through well-defined data fields, which shapes the workflow data model and reduces ambiguity. Admin and governance rely on workflow ownership, deployment scope, and auditability through Shopify’s app and store event logs rather than standalone enterprise admin consoles.
- +Visual workflow builder maps triggers, conditions, and actions without code changes
- +Tight integration with Shopify objects like orders, customers, and fulfillment
- +Extensibility through supported app actions and fields within the workflow graph
- +Config-driven automation supports repeatable setups across stores
- +Workflow execution follows Shopify event timing tied to store state changes
- –Schema is constrained by exposed fields from Shopify and connected apps
- –Throughput and retry behavior depend on event volume and downstream app responses
- –API surface is more limited than general-purpose orchestration products
- –Governance controls are narrower than dedicated automation admin centers
- –Complex branching and long chains become harder to validate at scale
Best for: Fits when Shopify teams need event-driven workflows across apps with minimal custom integration work.
How to Choose the Right Passport Picture Software
This buyer's guide covers Canva, Adobe Photoshop, GIMP, ImageMagick, Cloudinary, Imgix, FastAPI, Pillow, OpenCV, and Shopify Flow for generating passport-photo outputs and automating repeatable edits.
Each section focuses on integration depth, data model fit, automation and API surface, and admin and governance controls that affect throughput, compliance checks, and operator accountability across batches.
Software that converts uploaded headshots into passport-ready crops, backgrounds, and repeatable exports
Passport Picture Software standardizes passport-style framing by applying crop rules, background handling, sizing, and export formats through templates, batch workflows, or API transformations.
Teams use these tools to reduce per-photo manual work and to keep geometry consistent across countries where constraints differ. Canva represents a template-driven workflow with automated crop and background export steps, while Cloudinary and Imgix represent hosted transformation APIs that generate deterministic variants from stored assets.
Evaluation criteria that map to integration, governance, and automation in passport workflows
The strongest tools treat passport outputs as governed, repeatable transformations rather than ad hoc edits. Integration depth and a well-defined data model matter because automation needs stable inputs, stable rules, and predictable outputs.
Admin and governance controls decide who can change photo rules and how teams trace processing decisions. Automation and API surface decide how fast variants can be generated and how easily pipelines can attach to other systems.
Passport templates with reusable crop and background export rules
Canva excels with reusable design templates that apply automated crop and background handling during batch exports. This template structure reduces per-photo rework and keeps photo outputs consistent across runs.
Versioned transformation APIs that generate deterministic outputs from stored assets
Cloudinary provides parameterized transformation URLs that produce consistent crops, resizing, and format outputs from stored asset identifiers. Imgix offers deterministic transformation URLs that enable automated multi-size rendering without storing per-variant assets.
Automation surface built on typed schemas and OpenAPI for contract-based pipelines
FastAPI stands out with automatic OpenAPI generation tied to Pydantic request and response models. This makes integration safer when automation services need strict input validation and structured validation results.
Scripting and batch processing for deterministic, high-throughput image transforms
Adobe Photoshop supports batch exports using Actions plus scripting-driven workflows for repeatable background, crop, and retouch operations. GIMP supports Python scripting and procedural database-driven repeatable crop and background workflows, and ImageMagick supports scripted CLI transforms and MagickWand for batch pipelines.
Explicit governance controls for operator roles and operational audit needs
Canva includes RBAC-style workspace roles that limit who can edit shared templates, which directly affects rule administration risk. Cloudinary adds account roles and audit log visibility for operational oversight, while ImageMagick and Pillow require governance to be implemented outside the image processing step.
Governed compliance data model versus file or pixel-only artifacts
FastAPI and Cloudinary support clearer structured automation objects through typed schemas and media asset data model mapping, which helps keep rules aligned with inputs. Photoshop, GIMP, Pillow, and OpenCV operate primarily on file and pixel data, so teams must design compliance metadata schemas outside the core editor or library.
A control-depth and integration-depth decision framework for passport photo pipelines
Start by mapping where the passport rules should live. Template-driven batch tooling like Canva keeps rule assets centralized for shared governance, while API-first transformation platforms like Cloudinary and Imgix push logic into parameterized delivery steps.
Then match the data model and governance approach to the operating model. Scripting and libraries like ImageMagick, GIMP, Pillow, and OpenCV can deliver deterministic transforms, but governance controls like RBAC and audit logging must be built into surrounding services.
Choose the rule location: templates, transformation URLs, or code schemas
For centralized rule administration across teams, Canva uses reusable design templates with automated crop and background export workflows. For deterministic variants generated per request, Cloudinary and Imgix use parameterized transformation URLs driven by stored asset identifiers.
Lock the automation contract: schema-driven APIs versus file-driven pipelines
For integration with strict validation and predictable request and response payloads, FastAPI defines typed Pydantic models and produces OpenAPI output for provisioning automation clients. For engineering pipelines that operate on files and build their own metadata, ImageMagick, Pillow, and OpenCV keep inputs and outputs artifact-based so schema design lives in the service.
Plan batch throughput mechanics: Actions, scripted CLI runs, or async webhooks
For operator-driven batch editing with repeatable steps, Adobe Photoshop uses Actions plus scripting-driven batch exports for consistent background and crop. For hosted async processing and transformation flows, Cloudinary supports webhooks for asynchronous events after uploads and transformation readiness.
Define governance boundaries and audit expectations
If template changes must be restricted, Canva provides RBAC-style workspace roles for shared template editing. If operational oversight must include media processing events, Cloudinary offers account roles and audit log visibility, while ImageMagick, Pillow, and OpenCV require governance to be implemented in surrounding orchestration.
Handle passport compliance checks outside the image transform when the tool lacks rules
For tools that do not embed passport compliance validation, Cloudinary and Imgix require custom validation logic outside transformations because framing and background constraints need external checks. For editor tools like Photoshop and GIMP, compliance checks like face framing geometry are not governed as structured rules, so compliance validation must be implemented by the pipeline around exports.
Which teams get the best fit from each passport photo automation approach
Different passport photo workflows optimize for different control points. Template-heavy teams need centralized assets, engineering teams need deterministic transforms, and integration teams need stable API contracts.
The best fit depends on where rule changes happen and how automation chains need to validate inputs and outputs.
Teams running shared batch exports with template governance needs
Canva is the fit for teams that reuse passport-style design templates and want RBAC-style workspace roles to limit template edits. Its automated crop and background export workflows support consistent throughput across many photos.
Photo operations teams that want operator-grade retouching with batch repeatability
Adobe Photoshop fits when controlled edits matter and batch consistency comes from Actions plus scripting-driven exports. GIMP fits when deterministic scripted exports are needed without relying on web governance consoles.
Engineering teams building API-first passport photo automation services
FastAPI fits services that need typed schemas and OpenAPI output for contract-based integrations. ImageMagick and Pillow fit teams that implement their own compliance schema and orchestration around deterministic transforms.
Platforms that transform stored images into deterministic variants at request time
Cloudinary fits workflows that need transformation APIs, parameterized delivery outputs, and webhooks for async flows with media asset governance. Imgix fits when deterministic multi-size variants can be expressed as request parameters without storing per-variant assets.
Teams that require face alignment primitives and build compliance logic in their own pipeline
OpenCV fits when face detection, landmark estimation, and geometric transforms are needed to normalize head pose before applying crop rules. This requires external schemas, RBAC, and audit logging because OpenCV does not provide governed passport-rule administration.
Passport photo pipeline pitfalls that break governance, validation, or throughput
Several failure modes repeat across passport photo tooling choices. The most common problems come from missing passport-specific compliance validation and from governance controls that do not cover rule administration and audit needs.
Another frequent issue is treating file-based transforms as if they automatically enforce a schema for compliance metadata.
Assuming a transformation tool enforces passport compliance rules
Cloudinary and Imgix provide parameterized crops and background preparation, but passport compliance checks require custom validation logic outside transformations. Photoshop, GIMP, ImageMagick, Pillow, and OpenCV also lack passport compliance governance as structured rules, so compliance validation must be part of the surrounding pipeline.
Skipping a governance plan for template and rule changes
Canva includes RBAC-style workspace roles for shared templates, so it supports controlled template editing. ImageMagick, Pillow, and OpenCV require RBAC and audit logging to be implemented in the orchestration layer because those controls are not native to the image processing step.
Letting automation depend on undocumented file conventions instead of a schema
FastAPI avoids this by tying validation to Pydantic request and response models with OpenAPI output. For ImageMagick, Pillow, and OpenCV pipelines, teams must design their own metadata schema and enforce input discipline because the core processing operates on files and pixels.
Overcomplicating per-country variation without a repeatable rule asset strategy
Canva can handle per-batch repeatability through reusable passport templates but complex per-country rules may require custom workflow design. In code-first tools like GIMP, ImageMagick, and OpenCV, per-country branching becomes difficult unless transformation parameters and compliance rules are modeled explicitly in the service layer.
How We Selected and Ranked These Tools
We evaluated Canva, Adobe Photoshop, GIMP, ImageMagick, Cloudinary, Imgix, FastAPI, Pillow, OpenCV, and Shopify Flow by scoring features, ease of use, and value for building passport-photo automation workflows. Features carried the most weight at 40% because passport production depends on deterministic crop and background handling, and the remaining scoring split gave ease of use 30% and value 30%. This ranking reflects editorial research on named capabilities like Canva reusable templates, Cloudinary transformation URLs with webhooks, and FastAPI OpenAPI generation tied to Pydantic schemas.
Canva separated itself from the lower-ranked tools because it pairs reusable design templates with automated crop and background export workflows and includes RBAC-style workspace roles for template governance, which lifted the tool across features and ease of use through consistent batch throughput.
Frequently Asked Questions About Passport Picture Software
Which passport picture tools support API-driven transformations instead of manual edits?
Can automation workflows keep photo outputs consistent across large batches?
How do these tools differ in their underlying data model for automation?
Which options are better when teams need tight control over retouching quality and measurements?
What approach works best for enforcing governance, RBAC, and audit logging around passport photo processing?
How should systems handle data migration when moving from a file-based pipeline to an API delivery pipeline?
Which tools provide extensibility for custom validation, background rules, and jurisdiction-specific constraints?
How can integrations process passport photos using asynchronous events and webhooks?
What is the tradeoff between using desktop editors and server-side image pipelines for security isolation?
Which tool fits event-driven automation for passport photo generation tied to business workflows?
Conclusion
After evaluating 10 art design, Canva stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
Tools reviewed
Primary sources checked during evaluation.
cloudinary.comimgix.comshopify.comReferenced in the comparison table and product reviews above.
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