SlideShare a Scribd company logo
1 of 38
Download to read offline
Advanced Imaging on iOS
@rsebbe
Foreword
•

Don’t make any assumption about imaging on
iOS. Why?

•

Because even if you’re right today, you’ll be wrong
next year.

•

iOS is a moving platform, constantly being
optimized versions after versions.

•

Experiment, and find out the best approach for
your app.
Understanding
•

Things to have in mind at all times: execution
speed & memory consumption.

•

How to assess those: Instruments.
APIs
Core Image
Image IO
Core Animation
Core Graphics
GLKit
Core Video
AVFoundation

Many APIs but a unique
reality:
!

There’s CPU & there’s GPU
Each has pro’s & con’s.
!

Use them wisely depending
on particular app needs.
Imaging 101
•

On iOS, you typically use either PNGs and/or JPEGs.

•

PNG is lossless, typically less compressed *, CPU
decode only, prepared by Xcode if in app bundle. Usecase: UI elements.

•

JPEG is lossy, typically more compressed *, CPU or GPU
decode. Use-case: photo/textures
!

•

*: for images with single-color areas (UI), PNG can beat
JPEG by a factor of 10x !
Imaging 101
•

Image on iPhone 5/5s/5c: 3264 x 2448 pixels =
7990272 pixels = ~8MP

•

Decoded, each pixel is (R,G,B,A), 4 bytes.
Whole image is then 32MB in RAM. Original
JPEG is ~3MB.
Imaging Purpose
•

What is your purpose? Load & display (preview
thumbnails)? Load, process & display (image
editing)? Load, process & save? Process only
(augmented reality, page detection)?

•

Amount of data. Large images or small images?
Large input image, small output?
Discrete vs. UMA
Discrete
GPU (Mac)

Decode

Unified Memory
Architecture
(iOS/Mac)

Decode

Discrete
GPU
Unified
Memory
Architecture

Decode

Decode

Transfer

T

Transfer
GPU

Data go through bus, back
& forth is expensive

GPU & CPU share same memory.
Going back&forth is cheap

Display

Transfer

T

Display

CPU

Process

Process

Display

Display

Total speed depends on
relative transfer &
processing speeds
iOS being a UMA gives a
lot of flexibility
Comparisons
Draw w/
transform

Decode

Draw w/
transform

Decode

Pure GPU

Decode

Process

T

Display

Display

T

Display

CALayer/UIView
setTransform

CPU
Transfer
GPU

CGContextDrawImage
GPU
•

Fast, but has constraints.

•

Low-level APIs: OpenGL ES, GLSL

•

High-level APIs: GLKit, Sprite Kit, Core Animation, Core Image,
Core Video

•

Max OpenGL texture size is device dependent
•

4096x4096: iPad 2/mini/3/Air/mini2, iPhone 4S+

•

2048x2048: iPhone 3GS / 4 / iPad 1

•

Has fast hardware decoder for JPEG / Videos

•

Cannot run if app is in background (exception)
CPU
•

Slow, but flexible. Like “I’m 15x slower than my GPU
friend, OK, but I can be smarter”.

•

Low-level APIs: C, SIMD.

•

High-level APIs: Accelerate, Core Graphics, ImageIO.

•

Has smart JPEG decoder.

•

Can run in background.
Core Animation
•

Very efficient, GPU-accelerated 2D/3D transform of image-based
content. Foundation for UIKit’s UIView.

•

CALayer/UIView needs some visuals. How? -drawLayer: or setContents:

•

-[CALayer drawLayer:] (or -[UIView drawRect:]) uses Core
Graphics (CPU) to generate an image (slow), and that image is
then made into a GPU-backed texture that can move around
(fast).

•

If not drawing, but instead setting contents -[CALayer
setContents:] (or -[UIImageView setImage:]), you get the fast
path, that is, GPU image decoding.
Fast Path
CPU

Pure GPU

Decode

Decode

Display

T

Display

CPU
Transfer
GPU

-[CALayer drawRect:] (or UIView) +
CGContextDrawImage (or UIImage
draw)

CALayer.contents (or
UIImageView.image)
Demo 1
The Strong, the Weak, & the Ugly

Comparison of CALayer.contents / UIView drawRect: for small images
2MP, 50x
Show relative execution speed
Show Instruments Time Profiler & OpenGL ES Driver.
Core Graphics / ImageIO
•

CPU (mostly).

•

CGImageRef, CGImageSourceRef, CGContextRef

•

Used with -drawRect: -drawLayer:
Core Graphics / ImageIO
•

How the load CGImageRef? Either using UIImage (easier) or
CGImageSourceRef (more control)

•

How to create CGImageRef from existing pixel data?
CGDataProviderRef

•

Having a CGImage object does not mean it’s decoded. It’s
typically not, and even references mem-mapped data on disk ->
no real device memory.

•

Sometimes, you may want to have it into decoded form (repeated/
high performance drawing, access to pixel values)

•

How do I do that?
Core Graphics / ImageIO
•

Need access to pixel values: use CGBitmapContext

•

Need to draw that image repeatedly? use CGLayer,
UIGraphicsBeginImageContext(), or CGImage’s
shouldCache property.
Core Graphics / ImageIO
•

Understanding kCGImageSourceShouldCache

•

It does *not* cache your image when creating it from the
CGImageSourceRef.

•

Instead it caches it when drawing it the first time.

•

It caches possibly at different sizes simultaneously. If you
draw your image at 3 different sizes -> cached 3x.

•

Check your memory consumption when using caching,
and don’t keep that image around when not needed.
Core Graphics / ImageIO
•

Note on JPEG decoding (CPU)

•

Image divided in 8x8 blocks of pixels

•

Encoding: DCT (frequency domain)

•

Decoding: skip higher frequencies if not needed.

•

That property can be used to make CPU decoding a lot faster.
Core Graphics / ImageIO
•

If source image is 3264px wide,

•

Drawing at 1632px will trigger partial JPEG decoding (4x4
instead of 8x8) -> much faster. Drawing at 1633px
triggers full decoding + interpolation (much slower)

•

Similarly, successive power of 2 dividers have additional
speed gain. ÷8 faster than ÷4 faster than ÷2

•

If you need to draw a large image to a small size, use
Core Graphics API (CPU), not CALayer (GPU). GPU
decoding always decodes at full resolution!
I’m CPU, I’m weak
but I’m smart!
Draw small
from large
image (GPU)
Draw small
from large
image (CPU)

Decode

Decode

T

Display

Display

CALayer.contents

CGContextDrawImage (with
small target size)

Memory

Mem

CPU
Transfer
GPU
Demo 2
The Strong & Idiot vs. the Weak & Smart

11MP, 10x
Show GPU is slower. Show GPU version does entire image decoding, while CPU does smarter, reduced drawing.
Show Time Profiler function trace
Show VMTracker tool, Dirty size.
Change code to show influence of draw size on speed (+ function trace)
Core Image
•

CPU or GPU, ~20x speed difference on recent iPhone

•

Then, why using CPU? Background rendering (GPU not
available) or as OS fallback if image is too large.

•

API: CIImage, CIFilter, CIContext

•

CIImage are (immutable) recipes, do not store image data by
themselves

•

CIFilter (mutable) used to transform/combine CIImages

•

CIContext used to render into destination
Core Image
•

CIContext targets either EAGLContext or not. If not, it’s
meant to create CGImageRef, or render to CPU memory
(void*). In both cases, CIContext uses GPU to render,
unless kCIContextUseSoftwareRenderer is YES.

•

Using software rendering is slow. Very slow. Very, very
slow. Like 15x slower. Not recommended.

•

Depending on input image size / output target size, iOS
will automatically fallback to software rendering. Query
CIContext with inputImageMaximumSize /
outputImageMaximumSize
Core Image
•

-inputImageMaximumSize: 4096 (iPhone 4S+, iPad 2+),
2048 (iPhone 4-, iPad 1)

•

4000x3000 image (12MP) fits. Camera sensor is 8MP, OK.

•

5000x4000 image (20MP) does not fit.

•

How do I process images larger than the limit?
Core Image
•

Answer: Image Tiling.

•

Large CIImage & -imageByCroppingToRect? NO, CPU fallback, as
Core Image sees the original one (> limit).

•

Do the cropping on the CGImage itself
(CGImageCreateImageWithRect), and *then* create a CIImage out
of it.

•

Render tiles as CGImage from the CIContext, and render those
tiles in the large, final CGContext (> limit).

•

Art of tiling: Prizmo needs to process scanned images, that can be
> 20MP.
Core Image
GPU texture size limit
Source Image
Target Image (result)
Perspective Crop

Tiling in Prizmo: subdivide until source & target tiles
both fit GPU texture size limit
Core Image
•

Tips & Tricks

•

Core Image has access to hardware JPEG decoder, just
like Core Animation’s CALayer.contents API.

•

Core Image is not programmable on iOS. But many
unavailable functions can be expressed from the builtin
CIFilter’s.

•

Don’t find the filters you need? Give GPUImage a try.

•

Perfect team mate for OpenGL and Core Video.
CIImage’s Fast Path

Pure GPU

Decode

Process

Display

CIImage
imageWithContentsOfURL
(or CGImage)

CPU
Transfer
GPU
Core Image
•

Live processing or not? Depends.
Live Processing

Cached Processing

OpenGL Layer/View

CATiledLayer

Atomic Refresh

Visible Tiled
Rendering

Faster computation
overall

Slower computation

Slower interaction

Faster interaction
UIKit’s UIImage
•

Abstraction above CGImage / CIImage

•

Can’t be both at the same time, either CGImage-backed
or CIImage-backed.

•

Has additional properties such as scale (determines how
it’s rendered, Retina display) and imageOrientation

•

Nice utilities like -resizableImageWithCapInsets:
Core Video
•

Entry point for media. Both live camera stream & video files
decoding/encoding.

•

Defines image types, and image buffer pool concept (reuse).

•

Native format generally is YUV420v (MP4/JPEG). Luminance
plane (full size) + Cr, Cr planes (1:4)

•

You can ask to get them as GPU-enabled CVPixelBuffer for I/O

•

As of iOS7, you can render with OpenGL ES using R & RG I/O
(resp. 1 & 2 comps for L & Cr/Cr planes) -> no more
conversion needed (iPhone 4S+).
OpenGL ES
•

OpenGL - GLSL - GLKit: low level. You must load image
as a texture, create a rectangle geometry, define a shader
that tells how to map texture image to rendered fragments

•

Image processing is mostly happening in the fragment
shader.

•

GPUImage is an interesting library with so many available
filters.

•

CeedGL is a thin Obj-C wrapper for OpenGL objects
(texture, framebuffer, shader, program, etc.)
OpenGL ES
•

R / RG planes (GL2.0, iPhone 4s+)

•

Multiple Render Targets / Framebuffer Fetch (GL3.0,
iPhone 5s+)
•

MRT: before gl_FragColor.rgba = …

•

MRT: after my_FragColor.rgba = …;
my_NormalMap.xy = …, etc. in single shader pass.
GLKit Remark
•

GLKit does not seem to allow hardware decoding of
JPEGs (tested on iOS7, iPhone 5). Could change.
Conclusion
•

Use CPU / GPU for what it does best.

•

Don’t do more work than you need.

•

Overwhelming CPU or GPU is not good. Try to balance
efforts to remain fluid at all times.
Cookbook
Display
thumbnails

Have JPEGs ready with target size, use CALayer.contents
or UIImageView.image to get faster hardware decoding

Compute
thumbnails from
large image

Use CGImageSourceCreateThumbnail (or
CGBitmapContext / CGContextDrawImage)

Live processing Use CATiledLayer with cached source image (CIImage) at
& display of
various scales. Or OpenGL rendering if size < 4096 &
large images
processing can be made as a (fast) shader
Offscreen
processing of
large images

if size<=4096: GPU Core Image (or GL).
else: GPU Core Image (or GL) with custom tiling +
CGContext.
@cocoaheadsBE

More Related Content

Viewers also liked

Light ViewControllers
Light ViewControllersLight ViewControllers
Light ViewControllersachernish85
 
iOS 7 URL Session & Motion FX APIs
iOS 7 URL Session & Motion FX APIsiOS 7 URL Session & Motion FX APIs
iOS 7 URL Session & Motion FX APIsrsebbe
 
iOS GPUImage introduction
iOS GPUImage introductioniOS GPUImage introduction
iOS GPUImage introductionYi-Lung Tsai
 
Secure Multi-Party Negotiation: An Analysis for Electronic Payments in Mobile...
Secure Multi-Party Negotiation: An Analysis for Electronic Payments in Mobile...Secure Multi-Party Negotiation: An Analysis for Electronic Payments in Mobile...
Secure Multi-Party Negotiation: An Analysis for Electronic Payments in Mobile...IDES Editor
 
Встреча №9. Алгоритмы и коллекции стандартных библиотек C++, C#, Java, Object...
Встреча №9. Алгоритмы и коллекции стандартных библиотек C++, C#, Java, Object...Встреча №9. Алгоритмы и коллекции стандартных библиотек C++, C#, Java, Object...
Встреча №9. Алгоритмы и коллекции стандартных библиотек C++, C#, Java, Object...CocoaHeads
 
Core Data with Swift 3.0
Core Data with Swift 3.0Core Data with Swift 3.0
Core Data with Swift 3.0Korhan Bircan
 
Gpu Programming With GPUImage and Metal
Gpu Programming With GPUImage and MetalGpu Programming With GPUImage and Metal
Gpu Programming With GPUImage and MetalJanie Clayton
 
Core Image: The Most Fun API You're Not Using, CocoaConf Atlanta, December 2014
Core Image: The Most Fun API You're Not Using, CocoaConf Atlanta, December 2014Core Image: The Most Fun API You're Not Using, CocoaConf Atlanta, December 2014
Core Image: The Most Fun API You're Not Using, CocoaConf Atlanta, December 2014Chris Adamson
 
Digital watermarking
Digital watermarkingDigital watermarking
Digital watermarkingrupareliab14
 
Image Processing and Computer Vision in iOS
Image Processing and Computer Vision in iOSImage Processing and Computer Vision in iOS
Image Processing and Computer Vision in iOSOge Marques
 
Image Processing Basics
Image Processing BasicsImage Processing Basics
Image Processing BasicsNam Le
 
Introduction to digital image processing
Introduction to digital image processingIntroduction to digital image processing
Introduction to digital image processingHossain Md Shakhawat
 

Viewers also liked (18)

Light ViewControllers
Light ViewControllersLight ViewControllers
Light ViewControllers
 
iOS 7 URL Session & Motion FX APIs
iOS 7 URL Session & Motion FX APIsiOS 7 URL Session & Motion FX APIs
iOS 7 URL Session & Motion FX APIs
 
iOS GPUImage introduction
iOS GPUImage introductioniOS GPUImage introduction
iOS GPUImage introduction
 
Secure Multi-Party Negotiation: An Analysis for Electronic Payments in Mobile...
Secure Multi-Party Negotiation: An Analysis for Electronic Payments in Mobile...Secure Multi-Party Negotiation: An Analysis for Electronic Payments in Mobile...
Secure Multi-Party Negotiation: An Analysis for Electronic Payments in Mobile...
 
Встреча №9. Алгоритмы и коллекции стандартных библиотек C++, C#, Java, Object...
Встреча №9. Алгоритмы и коллекции стандартных библиотек C++, C#, Java, Object...Встреча №9. Алгоритмы и коллекции стандартных библиотек C++, C#, Java, Object...
Встреча №9. Алгоритмы и коллекции стандартных библиотек C++, C#, Java, Object...
 
Core Data with Swift 3.0
Core Data with Swift 3.0Core Data with Swift 3.0
Core Data with Swift 3.0
 
Image compression Algorithms
Image compression AlgorithmsImage compression Algorithms
Image compression Algorithms
 
Gpu Programming With GPUImage and Metal
Gpu Programming With GPUImage and MetalGpu Programming With GPUImage and Metal
Gpu Programming With GPUImage and Metal
 
Core Image: The Most Fun API You're Not Using, CocoaConf Atlanta, December 2014
Core Image: The Most Fun API You're Not Using, CocoaConf Atlanta, December 2014Core Image: The Most Fun API You're Not Using, CocoaConf Atlanta, December 2014
Core Image: The Most Fun API You're Not Using, CocoaConf Atlanta, December 2014
 
The Value in Trees
The Value in TreesThe Value in Trees
The Value in Trees
 
Jpeg compression
Jpeg compressionJpeg compression
Jpeg compression
 
Digital Watermarking
Digital WatermarkingDigital Watermarking
Digital Watermarking
 
Digital watermarking
Digital watermarkingDigital watermarking
Digital watermarking
 
Clean code
Clean codeClean code
Clean code
 
Image Processing and Computer Vision in iOS
Image Processing and Computer Vision in iOSImage Processing and Computer Vision in iOS
Image Processing and Computer Vision in iOS
 
JPEG Image Compression
JPEG Image CompressionJPEG Image Compression
JPEG Image Compression
 
Image Processing Basics
Image Processing BasicsImage Processing Basics
Image Processing Basics
 
Introduction to digital image processing
Introduction to digital image processingIntroduction to digital image processing
Introduction to digital image processing
 

Similar to Advanced Imaging on iOS

Performance and Memory Tuning - Part III - Transcript.pdf
Performance and Memory Tuning - Part III - Transcript.pdfPerformance and Memory Tuning - Part III - Transcript.pdf
Performance and Memory Tuning - Part III - Transcript.pdfShaiAlmog1
 
Шлигін Олександр “Розробка ігор в Unity загальні помилки” GameDev Conference ...
Шлигін Олександр “Розробка ігор в Unity загальні помилки” GameDev Conference ...Шлигін Олександр “Розробка ігор в Unity загальні помилки” GameDev Conference ...
Шлигін Олександр “Розробка ігор в Unity загальні помилки” GameDev Conference ...Lviv Startup Club
 
iOS App performance - Things to take care
iOS App performance - Things to take careiOS App performance - Things to take care
iOS App performance - Things to take careGurpreet Singh Sachdeva
 
Integrating with the Photography Ecosystem on Mac OS X
Integrating with the Photography Ecosystem on Mac OS XIntegrating with the Photography Ecosystem on Mac OS X
Integrating with the Photography Ecosystem on Mac OS Xfraserspeirs
 
Mo devtablet johncromartie-graphicsperformance
Mo devtablet johncromartie-graphicsperformanceMo devtablet johncromartie-graphicsperformance
Mo devtablet johncromartie-graphicsperformancejohncromartie
 
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法Unite2017Tokyo
 
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法Unity Technologies Japan K.K.
 
How to use qcow2 image.pdf
How to use qcow2 image.pdfHow to use qcow2 image.pdf
How to use qcow2 image.pdfDynamips Store
 
iOS Game Development With UIKit
iOS Game Development With UIKitiOS Game Development With UIKit
iOS Game Development With UIKitMartin Grider
 
[1C5]Lessons from developing a web browser for raspberry pi
[1C5]Lessons from developing a web browser for raspberry pi[1C5]Lessons from developing a web browser for raspberry pi
[1C5]Lessons from developing a web browser for raspberry piNAVER D2
 
Castro Chapter 5
Castro Chapter 5Castro Chapter 5
Castro Chapter 5Jeff Byrnes
 
What is image in Swift?/はるふ
What is image in Swift?/はるふWhat is image in Swift?/はるふ
What is image in Swift?/はるふha1f Yamaguchi
 
Everything you need to know about GraalVM Native Image
Everything you need to know about GraalVM Native ImageEverything you need to know about GraalVM Native Image
Everything you need to know about GraalVM Native ImageAlina Yurenko
 
Introduction to Computing on GPU
Introduction to Computing on GPUIntroduction to Computing on GPU
Introduction to Computing on GPUIlya Kuzovkin
 
Benchmark of common AI accelerators: NVIDIA GPU vs. Intel Movidius
Benchmark of common AI accelerators: NVIDIA GPU vs. Intel MovidiusBenchmark of common AI accelerators: NVIDIA GPU vs. Intel Movidius
Benchmark of common AI accelerators: NVIDIA GPU vs. Intel MovidiusbyteLAKE
 
19564926 graphics-processing-unit
19564926 graphics-processing-unit19564926 graphics-processing-unit
19564926 graphics-processing-unitDayakar Siddula
 

Similar to Advanced Imaging on iOS (20)

Performance and Memory Tuning - Part III - Transcript.pdf
Performance and Memory Tuning - Part III - Transcript.pdfPerformance and Memory Tuning - Part III - Transcript.pdf
Performance and Memory Tuning - Part III - Transcript.pdf
 
Flowframes
FlowframesFlowframes
Flowframes
 
Шлигін Олександр “Розробка ігор в Unity загальні помилки” GameDev Conference ...
Шлигін Олександр “Розробка ігор в Unity загальні помилки” GameDev Conference ...Шлигін Олександр “Розробка ігор в Unity загальні помилки” GameDev Conference ...
Шлигін Олександр “Розробка ігор в Unity загальні помилки” GameDev Conference ...
 
iOS App performance - Things to take care
iOS App performance - Things to take careiOS App performance - Things to take care
iOS App performance - Things to take care
 
Pc54
Pc54Pc54
Pc54
 
Integrating with the Photography Ecosystem on Mac OS X
Integrating with the Photography Ecosystem on Mac OS XIntegrating with the Photography Ecosystem on Mac OS X
Integrating with the Photography Ecosystem on Mac OS X
 
Mo devtablet johncromartie-graphicsperformance
Mo devtablet johncromartie-graphicsperformanceMo devtablet johncromartie-graphicsperformance
Mo devtablet johncromartie-graphicsperformance
 
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法
 
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法
【Unite 2017 Tokyo】インスタンシングを用いた美麗なグラフィックの実現方法
 
How to use qcow2 image.pdf
How to use qcow2 image.pdfHow to use qcow2 image.pdf
How to use qcow2 image.pdf
 
iOS Game Development With UIKit
iOS Game Development With UIKitiOS Game Development With UIKit
iOS Game Development With UIKit
 
[1C5]Lessons from developing a web browser for raspberry pi
[1C5]Lessons from developing a web browser for raspberry pi[1C5]Lessons from developing a web browser for raspberry pi
[1C5]Lessons from developing a web browser for raspberry pi
 
Castro Chapter 5
Castro Chapter 5Castro Chapter 5
Castro Chapter 5
 
What is image in Swift?/はるふ
What is image in Swift?/はるふWhat is image in Swift?/はるふ
What is image in Swift?/はるふ
 
From Web to Mobile with Stage 3D
From Web to Mobile with Stage 3DFrom Web to Mobile with Stage 3D
From Web to Mobile with Stage 3D
 
Everything you need to know about GraalVM Native Image
Everything you need to know about GraalVM Native ImageEverything you need to know about GraalVM Native Image
Everything you need to know about GraalVM Native Image
 
Introduction to Computing on GPU
Introduction to Computing on GPUIntroduction to Computing on GPU
Introduction to Computing on GPU
 
Android performance
Android performanceAndroid performance
Android performance
 
Benchmark of common AI accelerators: NVIDIA GPU vs. Intel Movidius
Benchmark of common AI accelerators: NVIDIA GPU vs. Intel MovidiusBenchmark of common AI accelerators: NVIDIA GPU vs. Intel Movidius
Benchmark of common AI accelerators: NVIDIA GPU vs. Intel Movidius
 
19564926 graphics-processing-unit
19564926 graphics-processing-unit19564926 graphics-processing-unit
19564926 graphics-processing-unit
 

Recently uploaded

WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Mattias Andersson
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationSlibray Presentation
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxLoriGlavin3
 
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfHyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfPrecisely
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteDianaGray10
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxLoriGlavin3
 
SALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICESSALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICESmohitsingh558521
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity PlanDatabarracks
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubKalema Edgar
 
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxLoriGlavin3
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Commit University
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024Stephanie Beckett
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxLoriGlavin3
 

Recently uploaded (20)

WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck Presentation
 
The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptx
 
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfHyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test Suite
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
 
SALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICESSALESFORCE EDUCATION CLOUD | FEXLE SERVICES
SALESFORCE EDUCATION CLOUD | FEXLE SERVICES
 
How to write a Business Continuity Plan
How to write a Business Continuity PlanHow to write a Business Continuity Plan
How to write a Business Continuity Plan
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding Club
 
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptxUse of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
Use of FIDO in the Payments and Identity Landscape: FIDO Paris Seminar.pptx
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
 

Advanced Imaging on iOS

  • 1. Advanced Imaging on iOS @rsebbe
  • 2. Foreword • Don’t make any assumption about imaging on iOS. Why? • Because even if you’re right today, you’ll be wrong next year. • iOS is a moving platform, constantly being optimized versions after versions. • Experiment, and find out the best approach for your app.
  • 3. Understanding • Things to have in mind at all times: execution speed & memory consumption. • How to assess those: Instruments.
  • 4. APIs Core Image Image IO Core Animation Core Graphics GLKit Core Video AVFoundation Many APIs but a unique reality: ! There’s CPU & there’s GPU Each has pro’s & con’s. ! Use them wisely depending on particular app needs.
  • 5. Imaging 101 • On iOS, you typically use either PNGs and/or JPEGs. • PNG is lossless, typically less compressed *, CPU decode only, prepared by Xcode if in app bundle. Usecase: UI elements. • JPEG is lossy, typically more compressed *, CPU or GPU decode. Use-case: photo/textures ! • *: for images with single-color areas (UI), PNG can beat JPEG by a factor of 10x !
  • 6. Imaging 101 • Image on iPhone 5/5s/5c: 3264 x 2448 pixels = 7990272 pixels = ~8MP • Decoded, each pixel is (R,G,B,A), 4 bytes. Whole image is then 32MB in RAM. Original JPEG is ~3MB.
  • 7. Imaging Purpose • What is your purpose? Load & display (preview thumbnails)? Load, process & display (image editing)? Load, process & save? Process only (augmented reality, page detection)? • Amount of data. Large images or small images? Large input image, small output?
  • 8. Discrete vs. UMA Discrete GPU (Mac) Decode Unified Memory Architecture (iOS/Mac) Decode Discrete GPU Unified Memory Architecture Decode Decode Transfer T Transfer GPU Data go through bus, back & forth is expensive GPU & CPU share same memory. Going back&forth is cheap Display Transfer T Display CPU Process Process Display Display Total speed depends on relative transfer & processing speeds iOS being a UMA gives a lot of flexibility
  • 9. Comparisons Draw w/ transform Decode Draw w/ transform Decode Pure GPU Decode Process T Display Display T Display CALayer/UIView setTransform CPU Transfer GPU CGContextDrawImage
  • 10. GPU • Fast, but has constraints. • Low-level APIs: OpenGL ES, GLSL • High-level APIs: GLKit, Sprite Kit, Core Animation, Core Image, Core Video • Max OpenGL texture size is device dependent • 4096x4096: iPad 2/mini/3/Air/mini2, iPhone 4S+ • 2048x2048: iPhone 3GS / 4 / iPad 1 • Has fast hardware decoder for JPEG / Videos • Cannot run if app is in background (exception)
  • 11. CPU • Slow, but flexible. Like “I’m 15x slower than my GPU friend, OK, but I can be smarter”. • Low-level APIs: C, SIMD. • High-level APIs: Accelerate, Core Graphics, ImageIO. • Has smart JPEG decoder. • Can run in background.
  • 12. Core Animation • Very efficient, GPU-accelerated 2D/3D transform of image-based content. Foundation for UIKit’s UIView. • CALayer/UIView needs some visuals. How? -drawLayer: or setContents: • -[CALayer drawLayer:] (or -[UIView drawRect:]) uses Core Graphics (CPU) to generate an image (slow), and that image is then made into a GPU-backed texture that can move around (fast). • If not drawing, but instead setting contents -[CALayer setContents:] (or -[UIImageView setImage:]), you get the fast path, that is, GPU image decoding.
  • 13. Fast Path CPU Pure GPU Decode Decode Display T Display CPU Transfer GPU -[CALayer drawRect:] (or UIView) + CGContextDrawImage (or UIImage draw) CALayer.contents (or UIImageView.image)
  • 14. Demo 1 The Strong, the Weak, & the Ugly Comparison of CALayer.contents / UIView drawRect: for small images 2MP, 50x Show relative execution speed Show Instruments Time Profiler & OpenGL ES Driver.
  • 15. Core Graphics / ImageIO • CPU (mostly). • CGImageRef, CGImageSourceRef, CGContextRef • Used with -drawRect: -drawLayer:
  • 16. Core Graphics / ImageIO • How the load CGImageRef? Either using UIImage (easier) or CGImageSourceRef (more control) • How to create CGImageRef from existing pixel data? CGDataProviderRef • Having a CGImage object does not mean it’s decoded. It’s typically not, and even references mem-mapped data on disk -> no real device memory. • Sometimes, you may want to have it into decoded form (repeated/ high performance drawing, access to pixel values) • How do I do that?
  • 17. Core Graphics / ImageIO • Need access to pixel values: use CGBitmapContext • Need to draw that image repeatedly? use CGLayer, UIGraphicsBeginImageContext(), or CGImage’s shouldCache property.
  • 18. Core Graphics / ImageIO • Understanding kCGImageSourceShouldCache • It does *not* cache your image when creating it from the CGImageSourceRef. • Instead it caches it when drawing it the first time. • It caches possibly at different sizes simultaneously. If you draw your image at 3 different sizes -> cached 3x. • Check your memory consumption when using caching, and don’t keep that image around when not needed.
  • 19. Core Graphics / ImageIO • Note on JPEG decoding (CPU) • Image divided in 8x8 blocks of pixels • Encoding: DCT (frequency domain) • Decoding: skip higher frequencies if not needed. • That property can be used to make CPU decoding a lot faster.
  • 20. Core Graphics / ImageIO • If source image is 3264px wide, • Drawing at 1632px will trigger partial JPEG decoding (4x4 instead of 8x8) -> much faster. Drawing at 1633px triggers full decoding + interpolation (much slower) • Similarly, successive power of 2 dividers have additional speed gain. ÷8 faster than ÷4 faster than ÷2 • If you need to draw a large image to a small size, use Core Graphics API (CPU), not CALayer (GPU). GPU decoding always decodes at full resolution!
  • 21. I’m CPU, I’m weak but I’m smart! Draw small from large image (GPU) Draw small from large image (CPU) Decode Decode T Display Display CALayer.contents CGContextDrawImage (with small target size) Memory Mem CPU Transfer GPU
  • 22. Demo 2 The Strong & Idiot vs. the Weak & Smart 11MP, 10x Show GPU is slower. Show GPU version does entire image decoding, while CPU does smarter, reduced drawing. Show Time Profiler function trace Show VMTracker tool, Dirty size. Change code to show influence of draw size on speed (+ function trace)
  • 23. Core Image • CPU or GPU, ~20x speed difference on recent iPhone • Then, why using CPU? Background rendering (GPU not available) or as OS fallback if image is too large. • API: CIImage, CIFilter, CIContext • CIImage are (immutable) recipes, do not store image data by themselves • CIFilter (mutable) used to transform/combine CIImages • CIContext used to render into destination
  • 24. Core Image • CIContext targets either EAGLContext or not. If not, it’s meant to create CGImageRef, or render to CPU memory (void*). In both cases, CIContext uses GPU to render, unless kCIContextUseSoftwareRenderer is YES. • Using software rendering is slow. Very slow. Very, very slow. Like 15x slower. Not recommended. • Depending on input image size / output target size, iOS will automatically fallback to software rendering. Query CIContext with inputImageMaximumSize / outputImageMaximumSize
  • 25. Core Image • -inputImageMaximumSize: 4096 (iPhone 4S+, iPad 2+), 2048 (iPhone 4-, iPad 1) • 4000x3000 image (12MP) fits. Camera sensor is 8MP, OK. • 5000x4000 image (20MP) does not fit. • How do I process images larger than the limit?
  • 26. Core Image • Answer: Image Tiling. • Large CIImage & -imageByCroppingToRect? NO, CPU fallback, as Core Image sees the original one (> limit). • Do the cropping on the CGImage itself (CGImageCreateImageWithRect), and *then* create a CIImage out of it. • Render tiles as CGImage from the CIContext, and render those tiles in the large, final CGContext (> limit). • Art of tiling: Prizmo needs to process scanned images, that can be > 20MP.
  • 27. Core Image GPU texture size limit Source Image Target Image (result) Perspective Crop Tiling in Prizmo: subdivide until source & target tiles both fit GPU texture size limit
  • 28. Core Image • Tips & Tricks • Core Image has access to hardware JPEG decoder, just like Core Animation’s CALayer.contents API. • Core Image is not programmable on iOS. But many unavailable functions can be expressed from the builtin CIFilter’s. • Don’t find the filters you need? Give GPUImage a try. • Perfect team mate for OpenGL and Core Video.
  • 29. CIImage’s Fast Path Pure GPU Decode Process Display CIImage imageWithContentsOfURL (or CGImage) CPU Transfer GPU
  • 30. Core Image • Live processing or not? Depends. Live Processing Cached Processing OpenGL Layer/View CATiledLayer Atomic Refresh Visible Tiled Rendering Faster computation overall Slower computation Slower interaction Faster interaction
  • 31. UIKit’s UIImage • Abstraction above CGImage / CIImage • Can’t be both at the same time, either CGImage-backed or CIImage-backed. • Has additional properties such as scale (determines how it’s rendered, Retina display) and imageOrientation • Nice utilities like -resizableImageWithCapInsets:
  • 32. Core Video • Entry point for media. Both live camera stream & video files decoding/encoding. • Defines image types, and image buffer pool concept (reuse). • Native format generally is YUV420v (MP4/JPEG). Luminance plane (full size) + Cr, Cr planes (1:4) • You can ask to get them as GPU-enabled CVPixelBuffer for I/O • As of iOS7, you can render with OpenGL ES using R & RG I/O (resp. 1 & 2 comps for L & Cr/Cr planes) -> no more conversion needed (iPhone 4S+).
  • 33. OpenGL ES • OpenGL - GLSL - GLKit: low level. You must load image as a texture, create a rectangle geometry, define a shader that tells how to map texture image to rendered fragments • Image processing is mostly happening in the fragment shader. • GPUImage is an interesting library with so many available filters. • CeedGL is a thin Obj-C wrapper for OpenGL objects (texture, framebuffer, shader, program, etc.)
  • 34. OpenGL ES • R / RG planes (GL2.0, iPhone 4s+) • Multiple Render Targets / Framebuffer Fetch (GL3.0, iPhone 5s+) • MRT: before gl_FragColor.rgba = … • MRT: after my_FragColor.rgba = …; my_NormalMap.xy = …, etc. in single shader pass.
  • 35. GLKit Remark • GLKit does not seem to allow hardware decoding of JPEGs (tested on iOS7, iPhone 5). Could change.
  • 36. Conclusion • Use CPU / GPU for what it does best. • Don’t do more work than you need. • Overwhelming CPU or GPU is not good. Try to balance efforts to remain fluid at all times.
  • 37. Cookbook Display thumbnails Have JPEGs ready with target size, use CALayer.contents or UIImageView.image to get faster hardware decoding Compute thumbnails from large image Use CGImageSourceCreateThumbnail (or CGBitmapContext / CGContextDrawImage) Live processing Use CATiledLayer with cached source image (CIImage) at & display of various scales. Or OpenGL rendering if size < 4096 & large images processing can be made as a (fast) shader Offscreen processing of large images if size<=4096: GPU Core Image (or GL). else: GPU Core Image (or GL) with custom tiling + CGContext.