Based on spot testing with a few dozen random images I found online of cats & dogs it does seem impressively accurate given the trivial amount of test data that I used to generate the model. The net result is that I can now add new images to the container and then click on the classify button to run the processing script and it will tell me if it thinks the image is a dog or cat and the degree of confidence in the result.
When you click on ‘Train’, it will generate a model file which can then be exported for use in FileMaker. Create ML App includes machine learning templates for image classification, image object detection, sound classification, text classification and word tagging.įor example, I created a test image classifier project and then pointed it at a folder containing 10 sample images (5 cats & 5 dogs). The Create ML App allows you to create a machine learning model file (.mlmodel) which can be used by the new FileMaker 19 Configure Machine Learning Model script step. If you download Apple’s Xcode development suite, then you will find it is bundled with the Create ML App. Getting started with Core ML and FileMaker
Core ML is Apple’s answer to integrating machine learning models into your app. Machine learning and artificial intelligence are ushering in the next era of computing and it is exciting to see that Claris are at the forefront of providing these services in a way that can be economically used even by small businesses.Ĭlaris FileMaker 19 makes use of the MacOS’ built in machine learning tools.
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