CODEWITHSUNDEEP
ioscoremlapple-vision
hzhou
hzhou

Reputation: 9

How to improve VNDetectRectanglesRequest to VNDetectCarRequest?

I use VNImageRequestHandler and VNDetectRectanglesRequest to handle request to find rectangles in a image. But since Vision in iOS11 only provide barcode、rectangle、face finding，but I want to find cars in an image ,what should I change code to find specify object in an image?

Upvotes: 0

Views: 861

Answers (1)

rickster
rickster

Reputation: 126107

If you’re looking for Apple to create an API named VNDetectCarRequest you should probably file a feature request. (And if it happens, I’m sure the “Apple is making a car!” rumor mill will start up again...)

For general-purpose image recognition, the path to take with Vision is to use VNCoreMLRequest and supply a machine learning model trained for the image recognition task you have in mind.

On the native programming side, all image recognition/classification tasks are the same — you can start by reusing Apple’s Classifying Images with Vision and Core ML sample code, which sets up VNCoreMLRequest and handles the VNClassificationObservation results it produces. The special sauce that changes a general “what is this” classifier into a “hotdog or not a hotdog” classifier or a “what kind of vehicle is this (if it’s one at all)” classifier is all in the model.

There might be a machine learning model that already does the task you’re looking for out there — if you find one, you can wrap it in a Core ML Model file using the scripts Apple provides.

Otherwise, you’ll need to look at one of the general purpose image classifier models out there (again, there are several already conveniently gathered on developer.apple.com) and work on specializing / retraining it to your more specific task. That part of your work is outside Apple’s API ecosystem, and there are many possible options. Web searches for “train caffe image model” or “train keras image model” or similar should be helpful there.

Once you’ve trained your model, use the Core ML tools to get it into Core ML to use with Vision.

Upvotes: 1

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