Update README.md

README.md

@@ -30,29 +30,27 @@ The dataset supports research in **driver monitoring, gaze estimation, takeover
 
 ## 📂 Dataset Structure
 
-Tester2/
+Tester1/
 ├── Gaze_object_output/
-│ ├── Stare_obj_0.csv # Gaze target data for subject 0
+│ ├── Stare_obj_0.csv # Gaze target data for scene 1
 │ ├── Stare_obj_1.csv
 │ └── ...
 │
-├── Tester2_feature_csv/
-│ ├── feature_0.csv # Feature vectors for subject 0
+├── Tester1_feature_csv/
+│ ├── feature_0.csv # Feature vectors for scene 1
 │ ├── feature_1.csv
 │ └── ...
 │
-├── Tester2_IS/
-│ ├── Tester2_0_IS/
+├── Tester1_IS/
+│ ├── Tester1_0_IS/
 │ │ ├── frame_output/ # Instance segmentation images (PNG frames)
-│ │ │ ├── frame_0001.png
+│ │ │ ├── frame_1.png
 │ │ │ └── ...
 │ │ └── obj_pixel_table.csv # Pixel-level statistics for each segmented vehicle
-│ ├── Tester2_1_IS/
+│ ├── Tester1_1_IS/
 │ └── ...
 
-markdown
-复制
-编辑
+
 
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@@ -83,35 +81,3 @@ markdown
     - `class_label`
 
 ---
-
-## 🧪 Usage Example
-
-```python
-import pandas as pd
-from PIL import Image
-
-# Load gaze data
-gaze_df = pd.read_csv("Tester2/Gaze_object_output/Stare_obj_0.csv")
-print("Gaze sample:", gaze_df.head())
-
-# Load feature CSV
-feat_df = pd.read_csv("Tester2/Tester2_feature_csv/feature_0.csv")
-print("Feature sample:", feat_df.describe())
-
-# Load segmentation image
-img = Image.open("Tester2/Tester2_IS/Tester2_0_IS/frame_output/frame_0001.png")
-img.show()
-
-# Load pixel statistics
-obj_stats = pd.read_csv("Tester2/Tester2_IS/Tester2_0_IS/obj_pixel_table.csv")
-print("Segmentation stats:", obj_stats.head())
-🎯 Potential Research Tasks
-Driver gaze estimation
-
-Driver attention prediction
-
-Takeover performance analysis
-
-Semantic segmentation of driving scenes
-
-Multimodal learning (gaze + features + segmentation)