Add initial examples

app.py

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+import gradio as gr
+import matplotlib.pyplot as plt
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy.io.wavfile import write
+
+audios = [
+    ["Book Example", "speaker"],
+    ["Swoosh", "swoosh"],
+    ["Knocking", "knocking"],
+    ["Forest", "forest"],
+    ["Evil Laugh", "evil-laugh"],
+    ["Morning", "morning"],
+    ["Cinematic", "cinematic"],
+]
+
+
+
+with gr.Blocks() as demo:
+    with gr.Tab("Waveforms"):
+        gr.Markdown("""## Waveforms
+                    
+In this section, we'll look into the waveforms of multiple audios.
+
+""")
+        for title, path in audios:
+            with gr.Row():
+                with gr.Column(scale=1):
+                    gr.Markdown(f"### {title}")
+                with gr.Column(scale=5):
+                    waveform = gr.Image(value=f"{path}/waveform.png")
+                with gr.Column(scale=5):
+                    video = gr.Video(value=f"{path}/waveform_video.mp4")
+
+    with gr.Tab("Understanding Frequencies"):
+        gr.Markdown("""## Understanding Frequencies
+                    """)
+        freq = gr.Slider(0, 300, step=20, value=40, label="Frequency")
+        freq2 = gr.Slider(0, 30, step=5, value=0, label="Second Frequency")
+        amplitude = gr.Slider(0.05, 1, step=0.05, value=1, label="Amplitude")
+
+        audio = gr.Audio()
+        with gr.Row():
+            plots = gr.Plot(label="Results")
+        with gr.Row():
+            button = gr.Button(label="Create")
+        
+        # https://github.com/gradio-app/gradio/issues/5469
+        @gr.on(inputs=[freq, freq2, amplitude], outputs=[audio, plots])
+        def plot_sine(freq, freq2, a):
+            sr = 1000   # samples per second
+            ts = 1.0/sr # sampling interval
+            t = np.arange(0, 1, ts) # time vector
+            data = a * np.sin(2 * np.pi * freq * t) + a * np.sin(2 * np.pi * freq2 * t)
+            write("test.wav", sr, data)
+
+            fig, axes = plt.subplots(nrows=2, ncols=1, sharex=False)
+            ax_waveform = axes[0]
+            ax_spectrum = axes[1]
+
+            ax_waveform.plot(t, data)
+            ax_waveform.set_title(f'Sine wave with frequency {freq} and amplitude {a}')
+            ax_waveform.set_xlabel('Time )s)')
+            ax_waveform.set_ylabel('Amplitude')
+            ax_waveform.set_title("Time domain of the signal")
+
+            X = np.fft.fft(data)
+            N = len(X)
+            n = np.arange(N)
+            T = N/sr
+            freq = n/T
+            ax_spectrum.set_xlim((0,300))
+            ax_spectrum.stem(freq, np.abs(X), 'r', \
+                markerfmt=" ", basefmt="-b")
+            ax_spectrum.set_xlabel("Frequency (Hz)")
+            ax_spectrum.set_title("Frequency domain of the signal")
+
+            fig.tight_layout()
+            fig.savefig('foo.png')
+            return "test.wav", fig
+        button.click(plot_sine, inputs=[freq, freq2, amplitude], outputs=[audio, plots])
+
+  
+if __name__ == '__main__':
+    demo.launch(debug=True)

requirements.txt

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+scipy