:sparkles: more hackathon messing about

app.py

@@ -1,51 +1,75 @@
 import numpy as np
 import io
+import pydub
 import soundfile as sf
 import streamlit as st
 from audio_recorder_streamlit import audio_recorder
 
 import pedalboard as pb
 
-@st.cache
-def remove_leading_silence(wave, threshold=0.001):
-    clean = np.array([])
-    for i, samples in enumerate(wave):
-        if abs(samples[0]) > threshold or abs(samples[1]) > threshold:
-            clean = wave[i:]
-            break
-    if clean.any():
-        return clean
-    else:
-        return wave
-
-st.title("👹 Voice Refuckulator")
-
-audio_bytes = audio_recorder()
-board = pb.Pedalboard([pb.Reverb(room_size=0.100), pb.Gain(-10)])
-
-if audio_bytes:
-    # data must be transposed, maybe before processing?
-    wave, sr = sf.read(io.BytesIO(audio_bytes))
-    wave = remove_leading_silence(wave)
-    try:
-        effected = board(wave, sr, reset=False)
-    except:
-        effected = wave
+
+def stretch(audio, factor, buffer=[]):
+    for s in audio:
+        for _ in range(factor):
+            buffer.append(s)
+    return buffer
+
+
+def destretcher(audio, buffer=[]):
+    for i, s in enumerate(audio):
+        if i % 100 == 0:
+            for _ in range(10):
+                buffer.append([0, 0])
+    return buffer
+
+st.title("👹 Sound Refuckulator")
+
+audio = np.array([])
+
+source = st.radio("Choose source", ["Microphone", "File upload"])
+if source == "Microphone":
+    audio_bytes = audio_recorder()
+    if audio_bytes:
+        audio, sr = sf.read(io.BytesIO(audio_bytes))
+else:
+    audio_bytes = st.file_uploader("Upload file")
+    if audio_bytes:
+        if audio_bytes.name.endswith("mp3"):
+            audio = pydub.AudioSegment.from_mp3(audio_bytes)
+            sr = audio.frame_rate
+            audio = np.float32(audio.get_array_of_samples()) / 2**15
+        else:
+            audio, sr = sf.read(audio_bytes)
+
+
+if audio.any():
     cols = st.columns(5)
-    stretch_factor = cols[0].slider("🧌 Trollizer", 1, 32, 1)
-    chunk_factor = cols[1].slider("🕋 Chunkinator", 1, 16, 1)
-    chunk_dividend = cols[2].slider("🫀 Dechunkizer", 1, 32, 1)
-    shuffle = cols[3].slider("🤡 Impredictidiblize", 1, 32, 1)
-    sr_factor = cols[4].slider("🏃‍♀️ Chirpidize", 1, 16, 1)
-    stretched = []
-    for chunk in np.array_split(effected, chunk_dividend):
-        for i in range(chunk_factor):
-            if i % shuffle == 0:
-                for c in chunk:
-                    for _ in range(stretch_factor):
-                        stretched.append(c)                
-            else:
-                for c in chunk:
-                    stretched.append(c)
-    stretched = np.array(stretched)
-    st.audio(stretched.T, sample_rate=sr*sr_factor)
+    chunk_dividend = cols[0].slider("🫀 Chunkizer", 16, 128, step=16)
+    stretch_factor = cols[1].slider("🧌 Trollizer", 1, 10, 1)
+    prob = cols[2].slider("🤡 Impredictidiblize", 0, 100, 0)
+    sr_factor = cols[3].slider("🏃‍♀️ Chirpidize", 1, 16, 1)
+    rev_size = cols[4].slider("🚛 Hugermaker", 0.0, 0.99, 0.0)
+    delay = pb.Pedalboard([pb.Delay(delay_seconds=0.01, feedback=0.6)])
+    reverb = pb.Pedalboard([pb.Reverb(room_size=rev_size)])
+    chorus = pb.Pedalboard([pb.Chorus()])
+    pshifter = pb.Pedalboard([pb.PitchShift(-12)])
+    processed = []
+    chunk_dividend = sorted(np.random.randint(audio.shape[0], size=chunk_dividend))
+    for i, chunk in enumerate(np.array_split(audio, chunk_dividend)):
+        if np.random.randint(100) < prob*2:
+            chunk = reverb(chunk, sample_rate=sr, reset=False) if np.random.randint(100) < prob else chunk
+            chunk = delay(chunk, sample_rate=sr, reset=False) if np.random.randint(100) < prob else chunk
+            chunk = chorus(chunk, sample_rate=sr, reset=False) if np.random.randint(100) < prob else chunk
+            chunk = pshifter(chunk, sample_rate=sr, reset=False) if np.random.randint(100) < prob else chunk
+            chunk = chunk + chunk if np.random.randint(100) < prob/2 else chunk
+            chunk = stretch(chunk, stretch_factor) if np.random.randint(100) < prob else chunk
+            chunk = destretcher(chunk) if np.random.randint(100) < prob else chunk
+        processed += [s for s in chunk]
+
+    processed = np.array(processed)
+    reverb = pb.Pedalboard([pb.Reverb(room_size=0.3)])
+    reverbered = reverb(processed, sr, reset=False)
+    compressor = pb.Pedalboard([pb.Limiter(threshold_db=-1)])
+    compressed = compressor(processed, sr, reset=False)
+
+    st.audio(compressed.T, sample_rate=sr * sr_factor)