Semantic Segmentation using DeepLabv3+
Dataset
The benchmark implementation run command will automatically download the validation and calibration datasets and do the necessary preprocessing. In case you want to download only the datasets, you can use the below commands.
DeepLabv3+ validation run uses the Cognata dataset. The preprocessed data is located under mlc_cognata_dataset/preprocessed_seg.
Get Validation Dataset
mlcr get,preprocessed,dataset,cognata,_mlc,_segmentation,_validation --outdirname=<path_to_download>
Get Calibration Dataset
mlcr get,preprocessed,dataset,cognata,_mlc,_segmentation,_calibration --outdirname=<path_to_download>
For preprocessing the dataset yourself, you can download the raw dataset.
Get Raw Dataset
mlcr get,raw,dataset,cognata,_mlc,_rclone --outdirname=<path_to_download>
Model
The benchmark implementation run command will automatically download the required model and do the necessary conversions. In case you want to only download the official model, you can use the below commands.
Get the Official MLPerf DeepLabv3+ Model
ONNX
Two variants are available:
# 8MP optimized version
mlcr get,ml-model,deeplabv3-plus,_mlc,_rclone,_onnx --outdirname=<path_to_download>
# Dynamic resolution version
mlcr get,ml-model,deeplabv3-plus,_mlc,_rclone,_onnx,_dynamic --outdirname=<path_to_download>
PyTorch
mlcr get,ml-model,deeplabv3-plus,_mlc,_rclone,_pytorch --outdirname=<path_to_download>