WIP animate mouth scale based on precalculated voiceline amplitude timelines

3d-generation-pipeline/generate_voiceline_amplitude_curves.py

@@ -0,0 +1,52 @@
+import os
+import librosa
+import numpy as np
+
+# === CONFIG ===
+FRAME_DURATION = 0.02  # 20 ms windows
+GAIN = 1.0             # multiply RMS values (set to e.g. 30.0 if you want larger values)
+EXTENSION = ".txt"     # output file extension
+
+
+def process_wav(filepath):
+    print(f"Processing: {filepath}")
+
+    # Load audio
+    audio, sr = librosa.load(filepath, mono=True)
+
+    # Frame size in samples
+    frame_len = int(FRAME_DURATION * sr)
+    hop_len = frame_len
+
+    # Compute RMS
+    rms = librosa.feature.rms(
+        y=audio,
+        frame_length=frame_len,
+        hop_length=hop_len
+    )[0]
+
+    # Apply optional gain
+    rms = rms * GAIN
+
+    # Save to .txt
+    out_path = os.path.splitext(filepath)[0] + EXTENSION
+    np.savetxt(out_path, rms, fmt="%.8f")
+
+    print(f"Saved RMS → {out_path}")
+
+
+def process_folder(folder_path):
+    print(f"Scanning folder: {folder_path}")
+
+    for filename in os.listdir(folder_path):
+        if filename.lower().endswith(".wav"):
+            filepath = os.path.join(folder_path, filename)
+            process_wav(filepath)
+
+    print("Done!")
+
+
+# === Run script ===
+if __name__ == "__main__":
+    folder = input("Enter folder path: ").strip()
+    process_folder(folder)

3d-generation-pipeline/line_rms.txt

@@ -0,0 +1,49 @@
+3.170447962475009263e-05
+2.923115389421582222e-04
+2.510738931596279144e-02
+1.111792679876089096e-02
+6.692767888307571411e-02
+1.006313711404800415e-01
+7.780694961547851562e-02
+5.686730891466140747e-02
+5.614304915070533752e-02
+4.554714635014533997e-02
+4.514135792851448059e-02
+5.479728057980537415e-02
+4.272024706006050110e-02
+3.989587724208831787e-02
+4.298635944724082947e-02
+4.074911773204803467e-02
+2.244980260729789734e-02
+1.105279754847288132e-02
+1.347438804805278778e-02
+1.654553040862083435e-02
+1.846965588629245758e-02
+2.045047841966152191e-02
+1.407719496637582779e-02
+6.578906439244747162e-03
+1.353173051029443741e-02
+1.625132374465465546e-02
+5.863697826862335205e-02
+1.110599413514137268e-01
+9.950184077024459839e-02
+1.184522062540054321e-01
+1.000181213021278381e-01
+6.772108376026153564e-02
+7.621638476848602295e-02
+3.018615581095218658e-02
+9.624224901199340820e-02
+1.259753555059432983e-01
+1.276500672101974487e-01
+1.206035763025283813e-01
+1.011835709214210510e-01
+6.155343726277351379e-02
+3.734333068132400513e-02
+2.485111355781555176e-02
+2.122259326279163361e-02
+1.139380130916833878e-02
+7.472451310604810715e-03
+5.807624198496341705e-03
+1.960268709808588028e-03
+8.761089411564171314e-04
+3.071058890782296658e-04