Add initial dataset

README.md

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 ---
 license: mit
 ---
+This repo gives preprocessed dataset that contains front camera videos and groundtruth trajectories created based on our SLAM framework.

interpolated_analysis.csv

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output_final_frame.py

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+import pandas as pd
+from pathlib import Path
+from tqdm import tqdm
+
+def find_last_true_index(interpolated_series):
+    
+    true_indices = interpolated_series[interpolated_series == True].index
+    if len(true_indices) > 0:
+        return true_indices[-1]
+    return None
+
+def analyze_all_samples(data_dir):
+    
+    data_path = Path(data_dir)
+    parquet_files = sorted(data_path.glob("*.parquet"))
+    
+    results = []
+    
+    for parquet_file in tqdm(parquet_files, desc="analyzing samples"):
+        sample_name = parquet_file.stem
+        
+        df = pd.read_parquet(parquet_file)
+        
+        if 'interpolated' not in df.columns:
+            print(f"warning: {sample_name} has no interpolated column")
+            continue
+        
+        last_true_idx = find_last_true_index(df['interpolated'])
+        
+        results.append({
+            'sample': sample_name,
+            'last_true_index': last_true_idx
+        })
+    
+    # create results DataFrame
+    results_df = pd.DataFrame(results)
+    
+    # save to CSV
+    output_csv = Path(data_dir).parent / 'interpolated_analysis.csv'
+    results_df.to_csv(output_csv, index=False)
+    print(f"\nresults saved to: {output_csv}")
+    
+    return results_df
+
+# example
+if __name__ == "__main__":
+    data_dir = "./trajectories"
+    results = analyze_all_samples(data_dir)
+    
+    print("\nanalysis results:")
+    print(results)
+    print(f"\nstatistics:")
+    print(results.describe())

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