Delete prediction.py

prediction.py

@@ -1,27 +0,0 @@
-import numpy as np
-import pandas as pd
-from preprocessing import preprocess_eeg_file
-from preprocessing_2dcnn import convert_epoch_to_spectrogram
-
-def aggregate_predictions(spectrogram_list, model, threshold=0.5):
-    X = np.array([np.transpose(s, (1, 2, 0)) for s in spectrogram_list])  # (n, H, W, C)
-    preds = model.predict(X, verbose=0)
-    segment_probs = preds[:, 1]  # probas pour la classe "épilepsie"
-    mean_prob = np.mean(segment_probs)
-    final_label = 1 if mean_prob >= threshold else 0
-    return final_label, mean_prob, segment_probs
-
-def predict_eeg_recording(edf_path, model, threshold=0.5):
-    preprocessed_df = preprocess_eeg_file(edf_path, fmin=1.0, fmax=45.0, segment_lenght=5, overlap=2)
-
-    if preprocessed_df is None or preprocessed_df.empty:
-        raise ValueError("EEG file could not be preprocessed or no valid segments found.")
-    
-    channels = ["EEG FP1-REF", "EEG FP2-REF", "EEG F3-REF", "EEG F4-REF", "EEG C3-REF"]
-    
-    spectrogram_list = preprocessed_df.apply(
-        lambda row: convert_epoch_to_spectrogram(row, channels, fs=250, nperseg=128, noverlap=64),
-        axis=1
-    ).tolist()
-
-    return aggregate_predictions(spectrogram_list, model, threshold)