def create_context(cls: type, args: argparse.Namespace,
cfg: CfgNode) -> Dict[str, Any]:
vis_specs = args.visualizations.split(",")
visualizers = []
extractors = []
for vis_spec in vis_specs:
texture_atlas = get_texture_atlas(args.texture_atlas)
texture_atlases_dict = get_texture_atlases(
args.texture_atlases_map)
vis = cls.VISUALIZERS[vis_spec](
cfg=cfg,
texture_atlas=texture_atlas,
texture_atlases_dict=texture_atlases_dict,
)
visualizers.append(vis)
extractor = create_extractor(vis)
extractors.append(extractor)
visualizer = CompoundVisualizer(visualizers)
extractor = CompoundExtractor(extractors)
context = {
"extractor": extractor,
"visualizer": visualizer,
"out_fname": args.output,
"entry_idx": 0,
}
return context
viz_class=DensePoseOutputsVertexVisualizer,
viz_class_kwargs=dict(),
),
chimps=dict(
config=str(
Path(__file__).parent / "assets" /
"densepose_rcnn_R_50_FPN_soft_chimps_finetune_4k.yaml"),
densepose_weights_url=
"https://dl.fbaipublicfiles.com/densepose/cse/densepose_rcnn_R_50_FPN_soft_chimps_finetune_4k/253146869/model_final_52f649.pkl",
weights="zamba_densepose_model_final_52f649.pkl",
viz_class=DensePoseOutputsTextureVisualizer,
viz_class_kwargs=dict(
texture_atlases_dict={
"chimp_5029":
get_texture_atlas(
str(
Path(__file__).parent / "assets" /
"chimp_texture_colors_flipped.tif"))
}),
anatomy_color_mapping=str(
Path(__file__).parent / "assets" / "chimp_5029_parts.csv"),
),
)
class DensePoseManager:
def __init__(
self,
model=MODELS["chimps"],
model_cache_dir: Path = Path(".zamba_cache"),
download_region=RegionEnum("us"),
):