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Thanks for the author's contribution
We noticed that the author mentioned in Features that CutLER can learn unsupervised object detectors and instance segmentors solely on ImageNet-1K.
Whether CutLER can be used for our datasets, which is not included in the ImageNet-1K?
The text was updated successfully, but these errors were encountered:
Hi, CutLER can be used for custom datasets! You can follow the pipeline of training CutLER on ImageNet-1k:
Cut: Use MaskCut to provide segmentation masks for multiple instances of each image, following this section. And place the json file under "DETECTRON2_DATASETS/YOUR-DATASET/annotations/".
Learn: after getting all pseudo labels on your datasets, you can follow this section to start the unsupervised model learning process. Note: 1) If your dataset is very small, it is recommended to load our ImageNet pretrained model weights and fine-tune the model on your dataset. 2) you need to follow detectron2 to understand how to train a model on custom datasets.
Thanks for the author's contribution
We noticed that the author mentioned in Features that CutLER can learn unsupervised object detectors and instance segmentors solely on ImageNet-1K.
Whether CutLER can be used for our datasets, which is not included in the ImageNet-1K?
The text was updated successfully, but these errors were encountered: