I've re-trained a model (following this tutorial) from the google's object detection zoo (ssd_inception_v2_coco) on a WIDER Faces Dataset and it seems to work if I use
frozen_inference_graph.pb from python, but if i take
saved_model.pb and put it to tensorflow serving, it predicts a lot of detections all with confidence less than 0.10.
Another thing that I do not understand is that both files are 52Mb however the original files downloaded from the object detection zoo take 98Mb each.
Here's an example of predictions made with the
saved_model and tensorflow serving:
And here's example of predictions by the same model, but using
- So what is the actual difference between the
- Are there any ways to inspect what's wrong with the
- How the much smaller size of the re-trained model vs the original could be explained?