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PRETRAIN_README.md

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Sapiens-Lite: Image Encoder

Model Zoo

Our 1024 x 1024 resolution vision transformers.

Model Checkpoint Path
Sapiens-0.3B $SAPIENS_LITE_CHECKPOINT_ROOT/pretrain/checkpoints/sapiens_0.3b/sapiens_0.3b_epoch_1600_$MODE.pt2
Sapiens-0.6B $SAPIENS_LITE_CHECKPOINT_ROOT/pretrain/checkpoints/sapiens_0.6b/sapiens_0.6b_epoch_1600_$MODE.pt2
Sapiens-1B $SAPIENS_LITE_CHECKPOINT_ROOT/pretrain/checkpoints/sapiens_1b/sapiens_1b_epoch_173_$MODE.pt2
Sapiens-2B $SAPIENS_LITE_CHECKPOINT_ROOT/pretrain/checkpoints/sapiens_2b/sapiens_2b_epoch_660_$MODE.pt2

Inference Guide

  • Navigate to your script directory: 
    cd $SAPIENS_LITE_ROOT/scripts/demo/[torchscript,bfloat16,float16]
  • For image feature extraction (uncomment your model config line): 
    ./extract_feature.sh

Define INPUT for your image directory and OUTPUT for results. The features are C x H x W dimensional and saved as .npy files to the OUTPUT folder.
Adjust BATCH_SIZE, JOBS_PER_GPU, TOTAL_GPUS and VALID_GPU_IDS for multi-GPU configurations.