update code

fit/configs/UTD_MHAD.json

@@ -4,7 +4,7 @@
     },
     "TRAIN": {
         "LEARNING_RATE": 2e-2,
-        "MAX_EPOCH": 500,
+        "MAX_EPOCH": 10,
         "WRITE": 1
     },
     "USE_GPU": 1,

fit/tools/map.py

@@ -1,14 +0,0 @@
-import numpy as np
-
-def mapping(Jtr,cfg):
-    name=cfg.DATASET.NAME
-    if not name=='HumanAct12':
-        mapped_joint=cfg.DATASET.DATA_MAP.UTD_MHAD
-        Jtr_mapped=np.zeros([Jtr.shape[0],len(mapped_joint),Jtr.shape[2]])
-        for i in range(Jtr.shape[0]):
-            for j in range(len(mapped_joint)):
-                for k in range(Jtr.shape[2]):
-                    Jtr_mapped[i][j][k]=Jtr[i][mapped_joint[j]][k]
-        return Jtr_mapped
-    return Jtr
-

fit/tools/save.py

@@ -41,14 +41,10 @@ def save_params(res, file, logger, dataset_name):
     fit_path = "fit/output/{}/params/".format(dataset_name)
     create_dir_not_exist(fit_path)
     logger.info('Saving params at {}'.format(fit_path))
-    pose_params = pose_params.cpu().detach()
+    pose_params = (pose_params.cpu().detach()).numpy().tolist()
-    pose_params = pose_params.numpy().tolist()
+    shape_params = (shape_params.cpu().detach()).numpy().tolist()
-    shape_params = shape_params.cpu().detach()
+    Jtr = (Jtr.cpu().detach()).numpy().tolist()
-    shape_params = shape_params.numpy().tolist()
+    verts = (verts.cpu().detach()).numpy().tolist()
-    Jtr = Jtr.cpu().detach()
-    Jtr = Jtr.numpy().tolist()
-    verts = verts.cpu().detach()
-    verts = verts.numpy().tolist()
     params = {}
     params["pose_params"] = pose_params
     params["shape_params"] = shape_params