Comments (2)
- Register your dataset: https://detectron2.readthedocs.io/tutorials/datasets.html
- The default dataloader may work for you already (if you just set polygons to an empty list for instances that do not have mask annotations). If it does not you can write a new dataloader: https://detectron2.readthedocs.io/tutorials/data_loading.html
- Write a new
ROIHeads
so that it handles instances without mask annotations properly: https://detectron2.readthedocs.io/tutorials/write-models.html
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Thank you so much! I will take a look at the tutorial.
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Related Issues (20)
- export_model.py crashes with keypoints HOT 1
- export_model.py crashes with keypoints HOT 9
- Very slow training on Apple M1 Pro HOT 2
- UnpicklingError: invalid load key, '\xef'. HOT 2
- export_model.py - list_of_lines[165] = " [1344, 1344], 1344 \n" HOT 1
- Please read & provide the following HOT 2
- The comits you are making are breaking the code!!! HOT 1
- @torch.compiler.disable - AttributeError: module 'torch' has no attribute 'compiler' HOT 7
- missing config key error HOT 2
- Please read & provide the following HOT 1
- Detectron2 about rotated object detection HOT 1
- AttributeError: Cannot find field 'gt_masks' in the given Instances! HOT 1
- DensePose的apply_net.py运行dump的选项时候,如何多gpu运行呢? HOT 1
- Encountered freezing during start training at iteration 0 HOT 2
- printing label name and bbox coordinates of predicted images
- Add device argument for multi-backends access & Ascend NPU support HOT 3
- How to convert densepose model to onnx? HOT 1
- 模型跑出来的效果超出预期
- Does this project support FCOS? HOT 1
- C++ and onnx HOT 2
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