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import os
import tempfile
import streamlit as st
from aira.core import AmbisonicsImpulseResponseAnalyzer
from aira.engine.input import InputMode
def save_temp_file(file):
temp_dir = tempfile.gettempdir()
temp_file_path = os.path.join(temp_dir, file.name)
with open(temp_file_path, "wb") as temp_file:
temp_file.write(file.getvalue())
return temp_file_path
def run_streamlit_app():
st.set_page_config(
page_title="AIRA", page_icon="docs/images/aira-icon.png", layout="wide"
)
# Logo
logo_path = "docs/images/aira-banner.png"
personal_logo_path = "docs/images/nahue-passano.png"
st.columns(11)[10].image(personal_logo_path, use_column_width=True)
# Audio loading and settings
settings, audio_files = st.columns(2)
with settings:
st.image(logo_path, use_column_width=True)
st.subheader("⚙️ Settings")
col1, col2, col3 = st.columns(3)
with col1:
integration_time = st.selectbox("Integration time [ms]", [1, 5, 10])
with col2:
analysis_length = st.text_input("Analysis length [ms]", value="500")
with col3:
intensity_threshold = st.text_input("Intensity threshold [dB]", value=-60)
with audio_files:
st.subheader("🔉 LSS room responses in A-Format")
up_files, down_files = st.columns(2)
with up_files:
audio_file_flu = st.file_uploader("Front-Left-Up", type=["mp3", "wav"])
audio_file_bru = st.file_uploader("Back-Right-Up", type=["mp3", "wav"])
with down_files:
audio_file_frd = st.file_uploader("Front-Right-Down", type=["mp3", "wav"])
audio_file_bld = st.file_uploader("Back-Left-Down", type=["mp3", "wav"])
audio_file_inverse_filter = st.file_uploader(
"Inverse filter", type=["mp3", "wav"]
)
# "Analyze" button
if st.button("Analyze", use_container_width=True):
data = {
"front_left_up": save_temp_file(audio_file_flu),
"front_right_down": save_temp_file(audio_file_frd),
"back_right_up": save_temp_file(audio_file_bru),
"back_left_down": save_temp_file(audio_file_bld),
"inverse_filter": save_temp_file(audio_file_inverse_filter),
"input_mode": InputMode.LSS,
"channels_per_file": 1,
"frequency_correction": True,
}
analyzer = AmbisonicsImpulseResponseAnalyzer()
fig = analyzer.analyze(
input_dict=data,
integration_time=float(integration_time) / 1000,
intensity_threshold=float(intensity_threshold),
analysis_length=float(analysis_length) / 1000,
show=False,
)
fig.update_layout(
height=1080,
paper_bgcolor="rgb(14,17,23)",
plot_bgcolor="rgb(14,17,23)",
)
st.plotly_chart(fig, use_container_width=True, height=1080)
if __name__ == "__main__":
run_streamlit_app()
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