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DEPTH_README.md

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Sapiens-Lite: Depth Estimation

Model Zoo

The depth estimation model checkpoints are available at,

Model Checkpoint Path
Sapiens-0.3B $SAPIENS_LITE_CHECKPOINT_ROOT/depth/checkpoints/sapiens_0.3b/sapiens_0.3b_render_people_epoch_100_$MODE.pt2
Sapiens-0.6B $SAPIENS_LITE_CHECKPOINT_ROOT/depth/checkpoints/sapiens_0.6b/sapiens_0.6b_render_people_epoch_70_$MODE.pt2
Sapiens-1B $SAPIENS_LITE_CHECKPOINT_ROOT/depth/checkpoints/sapiens_1b/sapiens_1b_render_people_epoch_88_$MODE.pt2
Sapiens-2B $SAPIENS_LITE_CHECKPOINT_ROOT/depth/checkpoints/sapiens_2b/sapiens_2b_render_people_epoch_25_$MODE.pt2

Inference Guide

  • Navigate to your script directory: 
      cd $SAPIENS_LITE_ROOT/scripts/demo/[torchscript,bfloat16]
  • For depth estimation (uncomment your model config line): 
    ./depth.sh

Define INPUT for your image directory, SEG_DIR for the .npy foreground segmentation directory (obtained from body-part segmentation) and OUTPUT for results.
The predictions will be visualized as (.jpg or .png) files to the OUTPUT directory as [image, depth as heatmap, surface normal from depth].
Adjust BATCH_SIZE, JOBS_PER_GPU, TOTAL_GPUS and VALID_GPU_IDS for multi-GPU configurations.

Depth Prediction