Inference

Open ghost opened this issue 5 years ago • 2 comments

How do I run inference with a custom model and custom dataset, where the input is a folder of images, and the output is folders with 1 cluster per folder?

Sep 08 '20 17:09 ghost

You can use calculate_predictions() function from training_functions.py. You can modify torch_DCEC.py to do that. Switch last lines to use calculate_predictions() on the loaded model and dataloader.

Sep 11 '20 12:09 michaal94

Oh could please list the line which I need to delete? I'm not sure if I'm deleting the wrong lines. Also, for me, after pretraining, my program at first uses 100% cpu, but then drops to no utilization. Is the pretraining model okay for inference?

Sep 12 '20 04:09 ghost