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import streamlit as st
from PIL import Image
from modules.thermal_fault_detection import detect_faults
st.set_page_config(page_title="Solar Panel Thermal Fault Detector", layout="centered")
st.title("π Solar Panel Thermal Fault Detection Dashboard")
st.markdown("""
This AI-powered app analyzes thermal images from drones to detect:
- π₯ Overheating
- π«οΈ Dust Accumulation
- π§ Physical Breakage
""")
uploaded_image = st.file_uploader("Upload a thermal image of a solar panel", type=["jpg", "png", "jpeg", "webp"])
if uploaded_image:
image = Image.open(uploaded_image).convert("RGB")
st.image(image, caption="Uploaded Thermal Image", use_column_width=True)
with st.spinner("Analyzing for thermal faults..."):
results, annotated_image = detect_faults(image)
if results:
st.error("β Faults Detected:")
for fault in results:
st.write(f"- π΄ **Fault Type:** {fault[0]} | **Confidence:** {fault[1]:.2f}")
st.image(annotated_image, caption="Detected Faults", use_column_width=True)
else:
st.success("β
No faults detected.")
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