update pedalboard and librosa and use recent interfaces, plus require matplotlib in packages.txt (#1)

- update pedalboard and librosa and use recent interfaces, plus require matplotlib in packages.txt (5e59257490af86f42718ab664ee721b1bf09f309)


Co-authored-by: Cumhur Erkut <cerkut@users.noreply.huggingface.co>

app.py

@@ -0,0 +1,157 @@
+import streamlit as st
+import soundfile as sf
+from pedalboard import (
+    Pedalboard,
+    Chorus,
+    Compressor,
+    Convolution,
+    Distortion,
+    Gain,
+    HighpassFilter,
+    LadderFilter,
+    Limiter,
+    LowpassFilter,
+    NoiseGate,
+    Phaser,
+    Reverb,
+)
+
+
+objects_and_init_kwargs = [
+    (
+        Chorus,
+        {
+            "rate_hz": 1.0,
+            "depth": 0.25,
+            "centre_delay_ms": 7.0,
+            "feedback": 0.0,
+            "mix": 0.5,
+        },
+    ),
+    (Compressor, {"threshold_db": 0, "ratio": 1, "attack_ms": 1.0, "release_ms": 100}),
+    # TODO - maybe add a few impulse responses to a folder + let folks cycle through them.
+    # (Convolution, {'impulse_response_filename': None, 'mix': 1.0}),
+    (Distortion, {"drive_db": 25}),
+    (Gain, {"gain_db": 1.0}),
+    (HighpassFilter, {"cutoff_frequency_hz": 50}),
+    (LadderFilter, {"mode": LadderFilter.LPF12, "cutoff_hz": 200, "drive": 1.0}),
+    (Limiter, {"threshold_db": -10.0, "release_ms": 100.0}),
+    (LowpassFilter, {"cutoff_frequency_hz": 50}),
+    (
+        NoiseGate,
+        {"threshold_db": -100.0, "ratio": 10, "attack_ms": 1.0, "release_ms": 100.0},
+    ),
+    (
+        Phaser,
+        {
+            "rate_hz": 1.0,
+            "depth": 0.5,
+            "centre_frequency_hz": 1300.0,
+            "feedback": 0.0,
+            "mix": 0.5,
+        },
+    ),
+    (
+        Reverb,
+        {
+            "room_size": 0.5,
+            "damping": 0.5,
+            "wet_level": 0.33,
+            "dry_level": 0.4,
+            "width": 1.0,
+            "freeze_mode": 0.0,
+        },
+    ),
+]
+
+name_to_object_init_kwargs = {
+    obj.__name__: (obj, kwargs) for obj, kwargs in objects_and_init_kwargs
+}
+
+
+def get_transform_names(augmentations):
+    transform_names = [st.sidebar.selectbox("Select transformation №1:", augmentations)]
+    while transform_names[-1] != "None":
+        transform_names.append(
+            st.sidebar.selectbox(
+                f"Select transformation №{len(transform_names) + 1}:",
+                ["None"] + augmentations,
+            )
+        )
+    transform_names = transform_names[:-1]
+    return transform_names
+
+
+def get_transforms():
+    transform_names = get_transform_names(sorted(name_to_object_init_kwargs.keys()))
+
+    transforms = []
+    for i, name in enumerate(transform_names):
+        st.sidebar.markdown("---")
+        st.sidebar.markdown(f"#### transformation №{i + 1}: {name}")
+        obj, kwargs = name_to_object_init_kwargs[name]
+
+        # 🚨 OMG pls no 🤮. It doesn't have to be this way. Do anything but this. 🚨
+        inputs = {}
+        for k, v in kwargs.items():
+            if k in ["mix", "room_size", "damping", "wet_level", "dry_level", "width", "freeze_mode", 'feedback']:
+                x = st.sidebar.slider(k, 0.0, 1.0, 0.1, key=f"{k}_{i}")
+            elif k in ['threshold_db', 'gain_db']:
+                x = st.sidebar.slider(k, -20., 20., 0., key=f"{k}_{i}")
+            elif k in ['rate_hz', 'centre_delay_ms', 'depth']:
+                x = st.sidebar.slider(k, 0., 10., 0.5, key=f"{k}_{i}")
+            elif k in ['drive_db']:
+                x = st.sidebar.slider(k, 0., 20., 0., key=f"{k}_{i}")
+            elif k in ['release']:
+                x = st.sidebar.slider(k, 0.01, 5000., 100., key=f"{k}_{i}")
+            elif k in ['ratio', 'drive']:
+                x = st.sidebar.slider(k, 1.0, 20., 4., key=f"{k}_{i}")
+            elif k in ['attack_ms', 'release_ms']:
+                x = st.sidebar.slider(k, 0.1, 2000., key=f"{k}_{i}")
+            elif k in ['cutoff_frequency_hz', 'cutoff_hz', 'centre_frequency_hz']:
+                x = st.sidebar.slider(k, 20, 20000, key=f"{k}_{i}")
+            elif k in ['mode']:
+                choices = [LadderFilter.LPF12, LadderFilter.HPF12, LadderFilter.BPF12, LadderFilter.LPF24, LadderFilter.HPF24, LadderFilter.BPF24]
+                x = st.sidebar.selectbox(k, choices)
+            else:
+                x = type(v)(st.sidebar.text_input(k, value=v))
+            inputs[k] = x
+        
+        # st.json(inputs)
+        transforms.append(obj(**inputs))
+    return transforms
+
+
+# 🚨 TODO - messy. clean me pls.
+
+audio_file = open('./example.wav', 'rb')
+audio_bytes = audio_file.read()
+
+st.markdown("## Input Audio")
+st.audio(audio_bytes, format='audio/ogg')
+
+# Run the audio through this pedalboard!
+audio, sample_rate = sf.read('./example.wav')
+# board = Pedalboard(get_transforms(), sample_rate=sample_rate)
+board = Pedalboard(get_transforms())
+effected = board(audio,sample_rate)
+
+# Write the audio back as a wav file:
+with sf.SoundFile('./outputs.wav', 'w', samplerate=sample_rate, channels=len(effected.shape)) as f:
+    f.write(effected)
+
+
+audio_file = open('./outputs.wav', 'rb')
+audio_bytes = audio_file.read()
+
+st.markdown("## Effected Audio")
+st.audio(audio_bytes, format='audio/wav')
+
+
+from matplotlib import pyplot as plt
+import librosa
+import librosa.display
+
+fig = plt.figure(figsize=(14, 5))
+librosa.display.waveshow(effected, sr=sample_rate)
+st.pyplot(fig)

requirements.txt

@@ -1,4 +1,5 @@
-streamlit==0.80.0
+streamlit
 pysoundfile
 pedalboard
-librosa
+librosa
+matplotlib