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README.md

@@ -19,7 +19,7 @@ configs:
     default: true
     description: "Temporal segment labels for all videos. Load splits to get train/val/test paths."
 
-  - config_name: default
+  - config_name: random
     data_files:
       - split: train
         path: "splits/train.csv"
@@ -27,7 +27,7 @@ configs:
         path: "splits/val.csv"
       - split: test
         path: "splits/test.csv"
-    description: "Default random 80/10/10 train/val/test split (seed 42)"
+    description: "Random 80/10/10 train/val/test split (seed 42)"
 ---
 [![License: CC BY-NC 4.0](https://img.shields.io/badge/License-CC%20BY--NC%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by-nc/4.0/)
 
@@ -136,11 +136,11 @@ import pandas as pd
 # Load the datasets
 print("Loading WanFall dataset...")
 
-# Labels are always in 'train' split by default in HuggingFace
-labels = load_dataset("simplexsigil2/wanfall", "labels")["train"]
+# Load labels (all temporal segments) - default config
+labels = load_dataset("YOUR_USERNAME/wanfall")["train"]
 
-# Load default train/val/test splits
-default_split = load_dataset("simplexsigil2/wanfall", "default")
+# Load random train/val/test splits
+random_split = load_dataset("YOUR_USERNAME/wanfall", "random")
 
 # Convert to pandas DataFrames
 labels_df = pd.DataFrame(labels)
@@ -148,7 +148,7 @@ print(f"Labels dataframe shape: {labels_df.shape}")
 print(f"Total temporal segments: {len(labels_df)}")
 
 # Process each split
-for split_name, split_data in default_split.items():
+for split_name, split_data in random_split.items():
     # Convert to DataFrame
     split_df = pd.DataFrame(split_data)
 
@@ -168,8 +168,8 @@ for split_name, split_data in default_split.items():
 from datasets import load_dataset
 import pandas as pd
 
-# Load labels
-labels = load_dataset("YOUR_USERNAME/wanfall", "labels")["train"]
+# Load labels (default config)
+labels = load_dataset("YOUR_USERNAME/wanfall")["train"]
 labels_df = pd.DataFrame(labels)
 
 # Load label names
@@ -204,10 +204,10 @@ from datasets import load_dataset
 import pandas as pd
 
 # Load data
-labels = load_dataset("YOUR_USERNAME/wanfall", "labels")["train"]
+labels = load_dataset("YOUR_USERNAME/wanfall")["train"]  # default config
 labels_df = pd.DataFrame(labels)
 
-splits = load_dataset("YOUR_USERNAME/wanfall", "default")
+splits = load_dataset("YOUR_USERNAME/wanfall", "random")
 train_df = pd.DataFrame(splits["train"])
 
 # Merge to get train labels