Convert PyTorch* F3Net Model¶
F3Net : Fusion, Feedback and Focus for Salient Object Detection
Clone the F3Net Repository¶
To clone the repository, run the following command:
git clone http://github.com/weijun88/F3Net.git
Download and Convert the Model to ONNX*¶
To download the pre-trained model or train the model yourself, refer to the instruction in the F3Net model repository. First, convert the model to ONNX* format. Create and run the following Python script 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. This model conversion was tested with the repository hash commit eecace3adf1e8946b571a4f4397681252f9dc1b8
.
Convert ONNX* F3Net Model to IR¶
mo --input_model <MODEL_DIR>/f3net.onnx