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Zhongdao / UniTrack

[NeurIPS'21] Unified tracking framework with a single appearance model. It supports Single Object Tracking (SOT), Video Object Segmentation (VOS), Multi-Object Tracking (MOT), Multi-Object Tracking and Segmentation (MOTS), Pose Tracking, Video Instance Segmentation (VIS), and class-agnostic MOT (e.g. TAO dataset).
MIT License
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Using a custom Resnet-18 Classification model #22

Closed kenrickfernandes closed 2 years ago

kenrickfernandes commented 2 years ago

I have trained a resnet-18 model on a custom dataset for classification. I also have trained YOLOX for detection on this custom dataset. How do I use my resnet-18 model as an appearance model? Since its not trained on crw,imagenet etc, what model_type should I give in the config file? And do I have to edit model/model.py to handle this model_type and load the model from my checkpoint? Thanks for your help!

Zhongdao commented 2 years ago

Hi @kenrickfernandes , I think you can specify the model_type in the config as "crw" in your case (the crw model is exactly a standard ResNet-18), and remember to let resume="PATH/TO/YOUR/MODEL/WEIGHTS". No other modifications are needed.

kenrickfernandes commented 2 years ago

Hi, Thank you for your reply! I will test out the tracking performance shortly.