Spaces:
Sleeping
Sleeping
vitorcalvi
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Commit
·
ffc9ee0
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Parent(s):
99e7048
first commit
Browse files- app.py +157 -0
- conda_create.sh +12 -0
app.py
ADDED
@@ -0,0 +1,157 @@
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1 |
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import gradio as gr
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import numpy as np
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from scipy import signal
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import soundfile as sf
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import matplotlib.pyplot as plt
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import io
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def generate_test_tone(frequency, duration=1.0, sample_rate=44100):
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t = np.linspace(0, duration, int(sample_rate * duration))
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tone = np.sin(2 * np.pi * frequency * t)
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return tone * np.hanning(len(tone))
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def create_audiogram(left_ear_results, right_ear_results):
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frequencies = [250, 500, 1000, 2000, 4000, 8000]
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plt.figure(figsize=(10, 8))
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plt.fill_between([125, 8000], -10, 25, color='#e6f3ff', alpha=0.3, label='Normal Hearing')
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plt.fill_between([125, 8000], 25, 40, color='#b3d9ff', alpha=0.3, label='Mild Loss')
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plt.fill_between([125, 8000], 40, 55, color='#80bfff', alpha=0.3, label='Moderate Loss')
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plt.fill_between([125, 8000], 55, 70, color='#4da6ff', alpha=0.3, label='Moderate-Severe Loss')
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plt.plot(frequencies, left_ear_results, 'x-', color='blue', label='Left Ear')
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plt.plot(frequencies, right_ear_results, 'o-', color='red', label='Right Ear')
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plt.xscale('log')
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plt.xlim(125, 8000)
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plt.ylim(70, -10)
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plt.grid(True)
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plt.xlabel('Frequency (Hz)')
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plt.ylabel('Hearing Level (dB)')
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plt.title('Audiogram Results')
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plt.legend()
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buf = io.BytesIO()
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plt.savefig(buf, format='png')
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plt.close()
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return buf
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def hearing_test(frequency, volume, ear_selection):
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sample_rate = 44100
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tone = generate_test_tone(float(frequency), 1.0, sample_rate)
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volume_adjusted = tone * (10 ** (volume / 20))
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stereo_tone = np.zeros((2, len(tone)))
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if ear_selection == "Left":
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stereo_tone[0] = volume_adjusted
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elif ear_selection == "Right":
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stereo_tone[1] = volume_adjusted
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else:
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stereo_tone[0] = stereo_tone[1] = volume_adjusted
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output_path = f"test_tone_{frequency}Hz.wav"
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sf.write(output_path, stereo_tone.T, sample_rate)
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return output_path
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def generate_audio(duration, selected_frequencies):
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sample_rate = 44100
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num_samples = int(float(duration) * sample_rate)
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noise = np.random.normal(0, 1, num_samples)
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if selected_frequencies:
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frequencies = [int(f) for f in selected_frequencies]
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for freq in frequencies:
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depth = -40 if freq == 4000 else -30
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width = freq / 10
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nyquist = sample_rate / 2
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freq_normalized = freq / nyquist
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quality_factor = freq / width
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b, a = signal.iirnotch(freq_normalized, quality_factor)
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noise = signal.filtfilt(b, a, noise)
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noise *= 10 ** (depth / 20)
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noise = noise / np.max(np.abs(noise))
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output_path = "notched_noise.wav"
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sf.write(output_path, noise, sample_rate)
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return output_path
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def create_interface():
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with gr.Blocks(title="Hearing Test & White Noise Generator") as app:
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with gr.Tabs():
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with gr.Tab("Hearing Test"):
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gr.Markdown("## Hearing Test")
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with gr.Row():
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with gr.Column():
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frequency = gr.Dropdown(
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choices=["250", "500", "1000", "2000", "4000", "8000"],
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value="1000",
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label="Test Frequency (Hz)"
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)
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volume = gr.Slider(
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minimum=-60,
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maximum=0,
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value=-20,
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step=5,
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label="Volume (dB)"
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)
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ear_select = gr.Radio(
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choices=["Both", "Left", "Right"],
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value="Both",
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label="Ear Selection"
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)
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test_btn = gr.Button("Play Test Tone")
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with gr.Column():
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audio_output = gr.Audio(label="Test Tone")
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with gr.Row():
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with gr.Column():
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left_thresholds = [gr.Number(value=0, label=f"{freq}Hz Left") for freq in [250, 500, 1000, 2000, 4000, 8000]]
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with gr.Column():
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right_thresholds = [gr.Number(value=0, label=f"{freq}Hz Right") for freq in [250, 500, 1000, 2000, 4000, 8000]]
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generate_audiogram_btn = gr.Button("Generate Audiogram")
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audiogram_output = gr.Image(label="Audiogram")
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with gr.Tab("White Noise Generator"):
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gr.Markdown("## Notched White Noise Generator")
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with gr.Row():
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with gr.Column():
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duration = gr.Slider(
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minimum=1,
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maximum=30,
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value=5,
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step=1,
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label="Duration (seconds)"
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)
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frequencies = gr.CheckboxGroup(
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choices=["250", "500", "1000", "2000", "4000", "8000"],
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label="Frequencies to Notch (Hz)",
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value=["4000", "2000"]
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)
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generate_noise_btn = gr.Button("Generate Noise")
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with gr.Column():
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noise_output = gr.Audio(label="Generated Noise")
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test_btn.click(
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fn=hearing_test,
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inputs=[frequency, volume, ear_select],
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outputs=audio_output
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)
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generate_audiogram_btn.click(
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fn=lambda *args: create_audiogram(args[:6], args[6:]).getvalue(),
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inputs=left_thresholds + right_thresholds,
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outputs=audiogram_output
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)
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generate_noise_btn.click(
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fn=generate_audio,
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inputs=[duration, frequencies],
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outputs=noise_output
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)
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return app
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if __name__ == "__main__":
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app = create_interface()
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app.launch(share=False)
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conda_create.sh
ADDED
@@ -0,0 +1,12 @@
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1 |
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# Create a new conda environment named 'noise-gen'
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2 |
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conda create -n noise-gen python=3.10
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# Activate the environment
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conda activate noise-gen
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# Install required packages
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conda install numpy scipy pip
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pip install gradio soundfile
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# Verify installation
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python -c "import gradio; import numpy; import scipy; import soundfile"
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