Convert PyTorch* F3Net to the Intermediate Representation

F3Net: Fusion, Feedback and Focus for Salient Object Detection

Download and Convert the Model to ONNX*

To download the pretrained model or train the model yourself, refer to the instruction in the F3Net model repository. Firstly, convert the model to ONNX* format. Create and run the script with the following content in the src directory of the model repository:

import torch

from dataset import Config
from net import F3Net

cfg = Config(mode='test', snapshot=<path_to_checkpoint_dir>)
net = F3Net(cfg)
image = torch.zeros([1, 3, 352, 352])
torch.onnx.export(net, image, 'f3net.onnx', export_params=True, do_constant_folding=True, opset_version=11)

The script generates the ONNX* model file f3net.onnx. The model conversion was tested with the repository hash commit eecace3adf1e8946b571a4f4397681252f9dc1b8.

Convert ONNX* F3Net Model to IR

./mo.py --input_model <MODEL_DIR>/f3net.onnx