kurzti88066/Fahrsimulator_MSY2526_AI
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

added clean eye df call to combined feature creation

Browse Source 
bug fix, was missing in combined feature creation script
This commit is contained in:
Michael Weig 2026-01-26 17:53:54 +01:00
parent 38e9354c42
commit eee173dc0b
1 changed files with 9 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
dataset_creation/combined_feature_creation.py
View File

@ -11,7 +11,7 @@ from pygazeanalyser.detectors import fixation_detection, saccade_detection
# KONFIGURATION
##############################################################################
INPUT_DIR = Path(r"/home/jovyan/data-paulusjafahrsimulator-gpu/both_mod_parquet_files")
OUTPUT_FILE = Path(r"/home/jovyan/data-paulusjafahrsimulator-gpu/new_datasets/blink_fix_dataset.parquet")
OUTPUT_FILE = Path(r"/home/jovyan/data-paulusjafahrsimulator-gpu/new_datasets/50s_25Hz_dataset.parquet")
WINDOW_SIZE_SAMPLES = 25*50 # 50s bei 25Hz
STEP_SIZE_SAMPLES = 125 # 5s bei 25Hz
@ -26,6 +26,7 @@ MIN_DUR_BLINKS = 2 # x * 40ms
def clean_eye_df(df):
"""Extrahiert nur Eye-Tracking Spalten und entfernt leere Zeilen."""
eye_cols = [c for c in df.columns if c.startswith("EYE_")]
if not eye_cols:
return pd.DataFrame()
@ -56,13 +57,14 @@ def extract_gaze_signal(df):
gx_R[~val_R] = np.nan
gy_R[~val_R] = np.nan
# Mittelwert beider Augen
gx = np.mean(np.column_stack([gx_L, gx_R]), axis=1)
gy = np.mean(np.column_stack([gy_L, gy_R]), axis=1)
# Interpolation
gx = pd.Series(gx).interpolate(limit=50, limit_direction="both").bfill().ffill()
gy = pd.Series(gy).interpolate(limit=50, limit_direction="both").bfill().ffill()
gx = pd.Series(gx).interpolate(limit=None, limit_direction="both").bfill().ffill()
gy = pd.Series(gy).interpolate(limit=None, limit_direction="both").bfill().ffill()
# MinMax Skalierung
xscaler = MinMaxScaler()
@ -227,6 +229,7 @@ def process_combined_features(input_dir, output_file, window_size, step_size, fs
df = pd.read_parquet(parquet_file)
print(f" Einträge: {len(df)}")
# Identifiziere Spalten
au_columns = [col for col in df.columns if col.startswith('FACE_AU')]
eye_columns = [col for col in df.columns if col.startswith('EYE_')]
@ -286,6 +289,9 @@ def process_combined_features(input_dir, output_file, window_size, step_size, fs
# Eye-Tracking Features
if has_eye:
try:
# clean dataframe from all nan rows
window_df= clean_eye_df(window_df)
eye_features = extract_eye_features_window(window_df[eye_columns], fs=fs,min_dur_blinks=min_duration_blinks)
result.update(eye_features)
except Exception as e: