Hello Team,
I develop the MaskRCNN Resnet50 model using Pytorch.
model = torchvision.models.detection.maskrcnn_resnet50_fpn(weights=MaskRCNN_ResNet50_FPN_Weights.DEFAULT)
Model training reference link: https://haochen23.github.io/2020/06/fine-tune-mask-rcnn-pytorch.html#.ZCRDd3ZBy5d
Convert the Pytorch model to ONNX using the below code (convert_pth_to_onnx.py).
Converted ONNX model to Openvino using the below command.
Model optimization command: mo --framework=onnx --data_type=FP16 --output_dir=./weights/Openvino/FP16/ --model_name=mask_rcnn_resnet50 --input_model=./weights/ONNX/MaskRCNN_resnet-50.onnx --input_shape=[1,3,536,559]
Inference the openvino model using CPU is working fine. Change the device name to GPU in
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Hi Vishnu T,
Thanks for reaching out.
Your shared folder is not including your model files. The weight folder is empty. Please reshare the model for us to validate on our end.
Meanwhile, for conversion of Mask R-CNN model, use the same parameter as shown in Converting an ONNX Mask R-CNN Model documentation.
On another note, please also try to compile your model with compiled_model=core.compile_model(model,"GPU"); instead of (model,"GPU.0")
Regards,
Aznie
