Is it possible to do very basic image recognition to compare an image against a database of images(resource folder images or any web servers images if we have) and determine which image in the database is the best match? I don't need to do any processing of any of the images, but simply differentiate between a finite list of images.
Is it any open source code available ?
I would recommend using OpenCV if you simply want to compare images (i.e. decide if two images are the same).
Here is a similar question on SO:
iOS image comparison
I would also go about reading a little bit about what Core Image (the iOS image library) has to offer, before going about OpenCV or other 3rd party.
I hope this helps.
Related
First, you need to know that I'm a beginner in this subject. Initially, I'm an Embedded System Developpers but I never worked with image recognition.
Let me expose my main goal:
I would like to create my own database of Logos and be able to
recognize them in a larger image. Typical application would be, for
example, to make a database of pepsi logos and coca-cola logos and
when I take a photo of a bottle of Soda, it tells me if it one of
them or an another.
So, here is my problem:
I first wanted to use the Auto ML Kit of Google. I gave him my
databases so it could train itself on it. My first attempt was to
take photos of bottle entirely and then compare. It was ok but not
too efficient. I then tried to give him only logos but after
training, it couldnt recognize anything in the whole image of a
bottle.
I think I didn't give enough images in the first case. But I'd prefer to use the second case (by giving only logo) so that the machine would search something similar in the image.
Finally, my questions:
If you've worked with ML Kit from Google, were you able to train a
model by giving images that should be recognized in a larger image?
If yes, do you have any hints to give me?
Do you know reliable software that could help me to perform tests of this kind? I thought about Azure Machine Learning Studio from
Microsoft (since I develop on Visual Studio).
In a first time, I'd like to code as few as I can just for testing. Maybe later I could try to code my own Machine Learning System but I think it's a big challenge.
I also thought that I would need to split my image in smaller image and then send each of this images into the Machine but it would be time consuming and I need a fast reaction (like < 2 seconds).
Thanks in advance for your answer. I don't need complete answer with full tutorial (Stack Overflow is not intended for that anyway ^^) but just some advices would already be good.
Have a good day!
Azure’s Custom Vision is great for this: https://www.customvision.ai
Let’s say you want to detect a pepsi logo. Upload 70 images of products with the logo on them. Use Custom Vision to draw a box around the logo for each photo. Click “train”, and you get a tensorflow model with code.
Look up any tutorial for it, it’s pretty incredible and really easy to use.
I am trying to make a photo editing application for iOS, but am not sure where to start looking. I have attached an image made in Word... that hopefully simply depicts what I am trying to achieve. It will involved manipulating individual pixels of a shape/image and masking/clipping. WHow should I start and what resources are available to me other than the developer docs?
Cheers
If you are not new to programming I would suggest a trial and run kind of approach. If it was me, I would follow a approach like this
Figuring out what to do/ what not to do
Do I need to develop the tech I want from scratch or can I use some pods ?
What are the good reads and example apps - (Try this)
Development approach
Build a photo gallery to pick images from
Build a EDIT mode screen
Get set of template overlay images
Figure out how to overlay them on top of each other
Export the final picture as one picture
The developer documentation is essential when it comes to learning new APIs, but sometimes it can be a little overwhelming. You can try reading raywenderlich.com tutorials on Core Image first to get an idea (link here) or find a book on computer graphics. It is essential to understand at least the underlying techniques to efficiently program image processing code. In many cases you'll find there is a more elegant technique than just looping on pixels and modifying one-by-one.
Then you can continue with reading on image compositing using core image for example.
What is the role of Augmented Images Database?
I am using arcoreimg tool to generate the img database, but why do need to generate it. I know it is a very basic question please provide your guidance
I am new to AR following Google AR SDK, Please help.
The role of the AugmentedImageDatabase is to store a compressed representation of the images you'd like to track. This is used by ARCore to detect images in the real world.
Generating a database at compile time with the arcoreimg tool has several advantages:
Your app no longer needs to bundle the original PNG or JPEG files. Your app would instead include a smaller database file, resulting in a smaller APK size.
Your app no longer needs to decode the original PNG or JPEG files to extract the image's feature points at runtime. This is an operation which takes roughly ~30ms for each image.
I have a JPEG image stored in memory as a blob and am looking to apply some basic transformations to it (e.g. resize, convert to greyscale, rotate etc.)
I am currently using Google Scripts which doesn't have a native image library as far as I can tell.
Are there standard algorithms or similar which would allow me to work with the raw binary array, knowing it represents a JPEG image, to achieve such a transformation?
Not the answer you are looking for I guess, but...
To be able to do image processing using JPEG files as input, you need to decode the images. Well, actually, 90/180/270 degree rotation, flipping and cropping is possible as lossless operations, and thus without decoding the image data. But for anything more advanced, like resizing, you need to work with a decoded image.
Both the file structure (JIF/JFIF) and algorithms used to compress the image data in standard JPEG format are well defined and properly documented. But at the same time, the specification is quite complex. It's certainly doable if you have the time and know what you are doing. And if you are lucky, and your JPEG blobs are all written the same way, you might get away with implementing only some of the spec. But even then, you will need to (re-)implement large parts of the spec, and it might just not be worth it.
Using a 3rd party service to convert it for you, or create your own using a known library, like libjpeg or Java's ImageIO, etc. might be your best bets, if you need a quick solution, and don't have too strict requirements for performance.
There are no straightfoward image processing capabilities available in Apps Script. You'll have either expose your Python as a web service and call it from Apps Script or use the Drive REST API to access the files from your Python app or use any api webservices.
GAE Python has Image processing capabilities check the below url:
https://developers.google.com/appengine/docs/python/images/
Available image transformations
The Images service can resize, rotate, flip, and crop images, and enhance photographs. It can also composite multiple images into a single image.
I am new to iOS programming and am interested in working with images. Basically, I want to be able to obtain the (0,255) and RGB tuples of every pixel in a given image. What would be the best way of doing this? Would I need to use Open GL, or something similar?
Thanks
If you want to work with images, get a copy of Apple's 'Quartz 2D Programming Guide'. If you want even more detailed how-to, get a copy of the "Programming with Quartz" book on Amazon (its says Mac in the title as it predates iOS).
Essentially you are going to take images, draw them into bit map contexts, then determine the rgba layout by querying the image.
If you want to use system resources to assist you in making certain types of changes to images, there is a OSX framework recently moved to iOS called the Accelerate Framework. and it has a lot of functions in it for image manipulation (vImage).
For reading and writing images to the file system look at Apple's 'Image I/O Guide'. For advanced filtering there is Core Image, which allows you to apply filters to images.
EDIT: If you have any interest in really fast accellerated code that uses the GPU to perform some sophisticated filtering, you can checkout Brad Larson's GPU Image project on github.