crosstyan/RapidPoseTriangulation
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Optional batched pose processing.

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This commit is contained in:
Daniel
2024-12-18 16:22:08 +01:00
parent 7b8d209601
commit 07426fac2f
8 changed files with 151 additions and 75 deletions
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7
scripts/test_skelda_dataset.py
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@ -53,6 +53,9 @@ default_min_match_score = 0.94
# If the number of cameras is high, and the views are not occluded, use a higher value
default_min_group_size = 1
# Batch poses per image for faster processing
# If most of the time only one person is in a image, disable it, because it is slightly slower then
default_batch_poses = True
datasets = {
"human36m": {
@ -62,6 +65,7 @@ datasets = {
"min_group_size": 1,
"min_bbox_score": 0.4,
"min_bbox_area": 0.1 * 0.1,
"batch_poses": False,
},
"panoptic": {
"path": "/datasets/panoptic/skelda/test.json",
@ -310,13 +314,14 @@ def main():
min_group_size = datasets[dataset_use].get("min_group_size", default_min_group_size)
min_bbox_score = datasets[dataset_use].get("min_bbox_score", default_min_bbox_score)
min_bbox_area = datasets[dataset_use].get("min_bbox_area", default_min_bbox_area)
batch_poses = datasets[dataset_use].get("batch_poses", default_batch_poses)
# Load 2D pose model
whole_body = test_triangulate.whole_body
if any((whole_body[k] for k in whole_body)):
kpt_model = utils_2d_pose.load_wb_model()
else:
kpt_model = utils_2d_pose.load_model(min_bbox_score, min_bbox_area)
kpt_model = utils_2d_pose.load_model(min_bbox_score, min_bbox_area, batch_poses)
# Manually set matplotlib backend
try: