def setup_detectron2_predictors(silhouettes_from='densepose'):
# Keypoint-RCNN
kprcnn_config_file = "COCO-Keypoints/keypoint_rcnn_R_50_FPN_3x.yaml"
kprcnn_cfg = get_cfg()
kprcnn_cfg.merge_from_file(model_zoo.get_config_file(kprcnn_config_file))
kprcnn_cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.7 # set threshold for this model
kprcnn_cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url(kprcnn_config_file)
kprcnn_cfg.freeze()
joints2D_predictor = DefaultPredictor(kprcnn_cfg)
if silhouettes_from == 'pointrend':
# PointRend-RCNN-R50-FPN
pointrend_config_file = "PointRend/configs/InstanceSegmentation/pointrend_rcnn_R_50_FPN_3x_coco.yaml"
pointrend_cfg = get_cfg()
add_pointrend_config(pointrend_cfg)
pointrend_cfg.merge_from_file(pointrend_config_file)
pointrend_cfg.MODEL.WEIGHTS = "checkpoints/pointrend_rcnn_R_50_fpn.pkl"
pointrend_cfg.freeze()
silhouette_predictor = DefaultPredictor(pointrend_cfg)
elif silhouettes_from == 'densepose':
# DensePose-RCNN-R101-FPN
densepose_config_file = "DensePose/configs/densepose_rcnn_R_101_FPN_s1x.yaml"
densepose_cfg = get_cfg()
add_densepose_config(densepose_cfg)
densepose_cfg.merge_from_file(densepose_config_file)
densepose_cfg.MODEL.WEIGHTS = "checkpoints/densepose_rcnn_R_101_fpn_s1x.pkl"
densepose_cfg.freeze()
silhouette_predictor = DefaultPredictor(densepose_cfg)
return joints2D_predictor, silhouette_predictor
def setup_cfg(args):
# load config from file and command-line arguments
cfg = get_cfg()
add_pointrend_config(cfg)
cfg.merge_from_file(args.config_file)
cfg.merge_from_list(args.opts)
# Set score_threshold for builtin models
cfg.MODEL.RETINANET.SCORE_THRESH_TEST = args.confidence_threshold
cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = args.confidence_threshold
cfg.MODEL.PANOPTIC_FPN.COMBINE.INSTANCES_CONFIDENCE_THRESH = args.confidence_threshold
cfg.freeze()
return cfg