regular update 230803

open-mmlab · Aug 3, 2023 · 0a4a5ac · 0a4a5ac
1 parent 21ef023
commit 0a4a5ac
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Showing 3 changed files with 8 additions and 4 deletions.
diff --git a/mmhuman3d/data/data_converters/cimi4d.py b/mmhuman3d/data/data_converters/cimi4d.py
@@ -94,10 +94,12 @@ def convert_by_mode(self, dataset_path: str, out_path: str,
             betas = np.repeat(betas, transl.shape[0], axis=0) 
 
             # image paths
-            image_paths = sorted(glob.glob(os.path.join(seq, 'img*', '*.jpg')))
+            image_paths = sorted(glob.glob(os.path.join(seq, '**', '*.jpg'), recursive=True))
 
             # translation need for official vis tools
 
+
+
 
 
 

diff --git a/mmhuman3d/data/data_converters/hsc4d.py b/mmhuman3d/data/data_converters/hsc4d.py
@@ -35,7 +35,7 @@ def __init__(self, modes=[], *args, **kwargs):
         self.misc_config = dict(
             bbox_source='by_dataset',
             smpl_source='original',
-            cam_param_type='prespective',
+            cam_param_type='perspective',
             kps3d_root_aligned=False,
         )
 

diff --git a/mmhuman3d/data/data_converters/ssp3d.py b/mmhuman3d/data/data_converters/ssp3d.py
@@ -40,9 +40,10 @@ def __init__(self):
             bbox_body_scale=1.2,
             bbox_facehand_scale=1.0,
             bbox_source='keypoints2d_smpl',
+            cam_param_type='prespective',
             cam_param_source='estimated',
             smpl_source='original',
-            focal_length=5000,
+            focal_length=(5000, 5000),
             principal_point=(256, 256),
             image_size=512,
         )
@@ -54,6 +55,7 @@ def __init__(self):
         }
 
         super(Ssp3dConverter, self).__init__()
+
 
     def _keypoints_to_scaled_bbox_bfh(self,
                                       keypoints,
@@ -136,7 +138,7 @@ def convert(self, dataset_path: str, out_path: str) -> dict:
         # initialize
         image_path_, keypoints2d_, bbox_xywh_ = [], [], []
 
-        seed, size = '230525', '999'
+        seed, size = '230803', '999'
         random.seed(int(seed))
 
         anno = dict(np.load(os.path.join(dataset_path, 'labels.npz')))