@version 1

# Panoptic segmentation models (modules/Segment). Each file named here is in the models folder: made
# by tools/export_mask2former.py, which also checks the .onnx against PyTorch.

[model mask2former-swin-base-coco-panoptic]
title:             "Mask2Former Swin-B, COCO panoptic (133 classes)"
model:             "mask2former-swin-base-coco-panoptic.onnx"
model_coreml:      "mask2former-swin-base-coco-panoptic.mlpackage"   # macOS: on the GPU (tools/export_mask2former_coreml.py makes it)
classes:           "mask2former-swin-base-coco-panoptic.classes.txt"
image_size:        384             # squashed to 384 x 384, not keeping its shape, as the checkpoint's processor does
mean:              0.485 0.456 0.406
std:               0.229 0.224 0.225
batch_gpu:         4
batch_cpu:         2               # the fastest per image on the CPU (tools/export_mask2former.py's check)
score_threshold:   0.5             # transformers 5.19's post_process_panoptic_segmentation defaults, which the check compares with
mask_threshold:    0.5
overlap_threshold: 0.8
map_max_side:      1024            # the stored segment map's longest side