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Runtime error
File size: 1,877 Bytes
25c6c7f 62238cb 25c6c7f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | import streamlit as st
import pandas as pd
import joblib
import os
from huggingface_hub import hf_hub_download
# -------------------------------
# UI
# -------------------------------
st.set_page_config(page_title="Engine Condition Monitoring", layout="centered")
st.title("🚗 Engine Condition Monitoring System")
st.write("Enter engine parameters below to predict condition.")
# -------------------------------
# Load Model
# -------------------------------
@st.cache_resource
def load_model():
try:
# Download model from Hugging Face
model_path = hf_hub_download(
repo_id="Satyanjay/engine-condition-monitoring-model",
filename="best_model.joblib"
)
except:
# fallback if running locally
model_path = "best_model.joblib"
model = joblib.load(model_path)
return model
model = load_model()
# Input fields
engine_rpm = st.number_input("Engine RPM", min_value=0.0)
lub_oil_pressure = st.number_input("Lub Oil Pressure", min_value=0.0)
fuel_pressure = st.number_input("Fuel Pressure", min_value=0.0)
coolant_pressure = st.number_input("Coolant Pressure", min_value=0.0)
lub_oil_temp = st.number_input("Lub Oil Temperature", min_value=0.0)
coolant_temp = st.number_input("Coolant Temperature", min_value=0.0)
# -------------------------------
# Prediction
# -------------------------------
if st.button("Predict"):
input_data = pd.DataFrame([{
'Engine rpm': engine_rpm,
'Lub oil pressure': lub_oil_pressure,
'Fuel pressure': fuel_pressure,
'Coolant pressure': coolant_pressure,
'Lub oil temp': lub_oil_temp,
'Coolant temp': coolant_temp
}])
prediction = model.predict(input_data)[0]
if prediction == 1:
st.error("⚠️ Engine Condition: FAULT DETECTED")
else:
st.success("✅ Engine Condition: NORMAL")
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