Hi,
I am trying to train and evaluate pre-trained Faster R-CNN model with standard coco dataset. I am getting the following error
TypeError: RandomIoUCrop() requires input sample to contain tensor or PIL images and bounding boxes. Sample can also contain masks.
Here are the high level steps
- Downloaded the COCO 2017 dataset
- Prepared PyTorch dataset using standard steps from Transforms v2: End-to-end object detection/segmentation example — Torchvision main documentation
- Training and evaluating Faster R-CNN model using steps from TorchVision Object Detection Finetuning Tutorial — PyTorch Tutorials 2.2.1+cu121 documentation
Any help will be appreciated. Thanks.