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How to train object detection model or classification model on custom dataset?
Hi, I have image data annotated for object detection as well on classification task. How I can train and build a object detection model and classification model on my own dataset?
A formal guideline would help me to understand the process thanks. Basically, I want to know how we can load our custom data into the Dataloader in supergradient?
Hello,
If you already have a torch data_loader implementation for your data- you can pass it to DatasetInterface (see or documentation).
After that, try and follow the same procedure you see in our walkthrough notebook example or our quickstart example.
Please let us know if you run into any problems.