Hi I trained the model through Firebase MLKit. I have selected the option to train him for 13 hours. And despite this, when I get into the details, Firebase only shows me 1 hour during training hours. And after uploading to Android device, CameraX is detecting images incorrectly. The same when I test the model in Firebase also incorrectly detects. I use photos from here: https://www.kaggle.com/grassknoted/asl-alphabet/data
How can I improve the detection and classification of photos?
I will try to help with my version, what you need to know is that MLkit runs on TensorFlow. MLKit can use the cloud model or ondevice, when you use your own model you must first upload it to the cloud (if you use MLKit), but if you use TensorFlowLite then you can put the model and label directly on the device.
Errors may occur when you make a model, you can use this tool to make your own model easily https://teachablemachine.withgoogle.com/train . After that, upload your model on the MLKit Firebase, and apply it to the Android / iOS application using this sample method https://firebase.google.com/docs/ml-kit/use-custom-models
i have sample project using MLKit & its work for more detail check my article here https://medium.com/@rakaadinugroho/face-image-cropper-with-machine-learning-c448f9d19858
