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I have searched related issues but cannot get the expected help.
2. I have read the FAQ documentation but cannot get the expected help.
3. The bug has not been fixed in the latest version.
Describe the bug
I'm using mmdeploy to convert pretrained RTMDet-Ins-tiny model to ONNX and TorchScript, and both conversions are successful. However, when I convert the model to CoreML, the output bboxes and scores are correct, but the mask output's position and size are incorrect.
output_pytorch
output_onnxruntime
output_coreml
Reproduction
Add a configuration base_instance-seg_coreml.py for deployment.
Checklist
Describe the bug
I'm using mmdeploy to convert pretrained RTMDet-Ins-tiny model to ONNX and TorchScript, and both conversions are successful. However, when I convert the model to CoreML, the output bboxes and scores are correct, but the mask output's position and size are incorrect.
output_pytorch
output_onnxruntime
output_coreml
Reproduction
Add a configuration
base_instance-seg_coreml.py
for deployment.Download prebuilt arm64 libtorch via link
Install the following packages via pip
coremltools==8.1
torch==2.2.0
torchvision==0.17.0
numpy==1.26.4
PyYAML==6.0.1
openmim==0.3.9
wheel==0.43.0
coremltools==8.1
scikit-learn==1.1.2
ipyplot==1.1.2
opencv-python
Install mmengine
mim install mmengine
mim install "mmcv>=2.0.0rc4, <2.2.0"
I followed the instructions in this notebook: https://github.com/gustavofuhr/ios_object_detection/blob/main/rtmdet_mmdetection_to_coreml/export_mmdetection_coreml.ipynb to build and install mmdeploy v1.3.1 (commit hash: bc75c9d) and mmdet v3.3.0 (commit hash: 44ebd17b145c2372c4b700bfb9cb20dbd28ab64a).
Run mmdeploy
python mmdeploy/tools/deploy.py mmdeploy/configs/mmdet/_base_/base_instance-seg_coreml.py mmdetection/configs/rtmdet/rtmdet-ins_tiny_8xb32-300e_coco.py rtmdet-ins_tiny_8xb32-300e_coco_20221130_151727-ec670f7e.pth mmdetection/demo/demo.jpg --work-dir rtmdet-ins-tiny --device cpu --dump-info
Environment
Error traceback
No response
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