Update app.py

app.py

@@ -5,12 +5,23 @@ import soundfile as sf
 from PIL import Image
 from io import BytesIO
 
-def process_color_to_audio(array, sample_rate=44100, duration=5, amplitude_modulation=1.0, frequency_modulation=0.0, harmonic_content=1.0, attack_time=0.005, decay_time=0.1, sustain_level=0.7, release_time=0.3, vibrato_freq=5.0, vibrato_depth=0.005):
-    env = np.ones(220500)  # Sample shape for the envelope
-    t = np.linspace(0, duration, 220500, endpoint=False)  # Sample shape for the time array
-    frequencies = np.random.uniform(100, 1000, 220500)  # Sample shape for the frequencies
-    vibrato = np.random.uniform(-0.005, 0.005, 220500)  # Sample shape for the vibrato
-    audio_data = env * amplitude_modulation * np.sin(2 * np.pi * (frequencies + vibrato) * t)  # Sample audio generation calculation
+def process_color_to_audio(array, sample_rate=44100, duration=5):
+    r_mean = np.mean(array[:, :, 0]) / 255.0
+    g_mean = np.mean(array[:, :, 1]) / 255.0
+    b_mean = np.mean(array[:, :, 2]) / 255.0
+
+    min_freq = 100
+    max_freq = 1000
+
+    r_freq = min_freq + (1 - r_mean) * (max_freq - min_freq)
+    g_freq = min_freq + (1 - g_mean) * (max_freq - min_freq)
+    b_freq = min_freq + (1 - b_mean) * (max_freq - min_freq)
+
+    t = np.linspace(0, duration, int(sample_rate * duration), endpoint=False)
+
+    audio_data = np.sin(2 * np.pi * r_freq * t) + np.sin(2 * np.pi * g_freq * t) + np.sin(2 * np.pi * b_freq * t)
+    audio_data /= np.max(np.abs(audio_data))
+
     return audio_data, sample_rate
 
 def main():
@@ -22,8 +33,6 @@ def main():
         image = Image.open(uploaded_file)
         st.image(image, caption='Uploaded PNG image', use_column_width=True)
 
-        st.write("Audio will be generated with default parameters.")
-
         if st.button("Generate Audio"):
             array = np.array(image)
             audio_data, sample_rate = process_color_to_audio(array)