Update README.md

README.md

@@ -78,9 +78,9 @@ ChingMu 1000H is an optical motion capture dataset designed for training and val
 
 | Component | Format | Details |
 |---|---|---|
-| Raw motion | `.bvh` | Y-up, 120 fps, YXZ rotation, cm, 22 joints |
-| Retargeted trajectories | `.csv` | Root position (m), quaternion, joint angles (rad) |
-| Object 6D pose | `.csv` | Position (m) + quaternion, 120 Hz |
+| Raw motion | `.bvh` | Y-up, 120 fps, YXZ rotation, mm, 22 joints |
+| Retargeted trajectories | `.csv` | Root position (mm), quaternion, joint angles (rad) |
+| Object 6D pose | `.csv` | Position (mm) + quaternion, 120 Hz |
 | Multi-view video | `.mp4` | 2-3 cameras, co-registered |
 | Semantic labels | `.csv` | Task, scenario, action, object |
 
@@ -156,7 +156,7 @@ file_path = hf_hub_download(
     repo_id=repo_id,
     filename="samples/1.1.Basic_Movement_Category/1.1.1.High_Dynamic_Movement/1.1.1.1.Standing_High_Jump/BM_Standing_High_Jump_00001.csv",
     repo_type="dataset",
-    local_dir="./robot_samples"
+    local_dir="./samples"
 )
 print(f"Downloaded: {file_path}")
 ```
@@ -169,7 +169,7 @@ print(f"Downloaded: {file_path}")
 
 **Accuracy:** joint error <1mm, object pose ±2mm / ±0.5°, temporal sync <1 frame.  
 
-**Limitations:** performer age skew (20–35), object accuracy varies with marker cluster size.  
+**Limitations:** performer age skew (20–40), object accuracy varies with marker cluster size.  
 
 ---