Hi!
I have trained my first custom object detection model with 2 classes and 100 test/500 train images and have some questions.
Nothing has been pretrained. I’m running efficientdet_d0_coco17_tpu-32 with my own labeled images created with LabelImg.


Low initial total loss from first step (starts from 1.5)


Total loss down to 0.2 after just 2000 steps, wth? After that loss is increased if continued


Low score when predicting


Should you resize your train/test images to one size or should they be the original size?


Should initial total loss not go up when you retrain with new train/test images? Started at last checkpoint with old images removed, right now it continues on last value (0.2)


My goal is to detect vehicles/license plates, is 500 images not enough for this?


I’m using my model in react-native (expo eas), the following has been done:



Clone tensorflow models
github/tensorflow/models
Setup my configuration files, (using efficientdet_d0_coco17_tpu-32)
Train model untill loss is no longer decreasing
Export using exporter_main_v2
Converted my saved model to tensorflowjs model
github.com/tensorflow/tfjs-converter/blob/0.8.x/README.json.md

Loaded my model using bundleResourceIO
@tensorflow/tfjs-react-native - npm


Is this “the correct way” if you want to use your own custom object detection model in react-native? Maybe I should be using tflite instead?
Really appreciate the help!