The normal estimation checkpoints are available at,
Model | Checkpoint Path |
---|---|
Sapiens-0.3B | $SAPIENS_LITE_CHECKPOINT_ROOT/normal/checkpoints/sapiens_0.3b/sapiens_0.3b_normal_render_people_epoch_66_$MODE.pt2 |
Sapiens-0.6B | $SAPIENS_LITE_CHECKPOINT_ROOT/normal/checkpoints/sapiens_0.6b/sapiens_0.6b_normal_render_people_epoch_200_$MODE.pt2 |
Sapiens-1B | $SAPIENS_LITE_CHECKPOINT_ROOT/normal/checkpoints/sapiens_1b/sapiens_1b_normal_render_people_epoch_115_$MODE.pt2 |
Sapiens-2B | $SAPIENS_LITE_CHECKPOINT_ROOT/normal/checkpoints/sapiens_2b/sapiens_2b_normal_render_people_epoch_70_$MODE.pt2 |
- Navigate to your script directory:
cd $SAPIENS_LITE_ROOT/scripts/demo/[torchscript,bfloat16]
- For normal estimation (uncomment your model config line):
./normal.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, surface normal]
Adjust BATCH_SIZE
, JOBS_PER_GPU
, TOTAL_GPUS
and VALID_GPU_IDS
for multi-GPU configurations.