Hugging Face's logo

Spaces:
geniusut
/
engine-predictive-maintenance
Runtime error

App Files Community
engine-predictive-maintenance
File size: 1,880 Bytes
e011941
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92

import streamlit as st
import pandas as pd
import joblib

from huggingface_hub import hf_hub_download

# =========================================
# Load Model from Hugging Face Hub
# =========================================

model_path = hf_hub_download(
    repo_id="geniusut/engine-predictive-maintenance-model",
    filename="best_model.pkl"
)

model = joblib.load(model_path)

# =========================================
# Streamlit UI
# =========================================

st.title("Engine Predictive Maintenance")

st.write(
    "Enter engine operational parameters "
    "to predict maintenance requirements."
)

# =========================================
# User Inputs
# =========================================

engine_rpm = st.number_input(
    "Engine RPM",
    value=800.0
)

lub_oil_pressure = st.number_input(
    "Lub Oil Pressure",
    value=3.5
)

fuel_pressure = st.number_input(
    "Fuel Pressure",
    value=6.5
)

coolant_pressure = st.number_input(
    "Coolant Pressure",
    value=2.5
)

lub_oil_temp = st.number_input(
    "Lub Oil Temperature",
    value=75.0
)

coolant_temp = st.number_input(
    "Coolant Temperature",
    value=80.0
)

# =========================================
# Prepare Input Data
# =========================================

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
}])

# =========================================
# Predict
# =========================================

if st.button("Predict"):

    prediction = model.predict(input_data)[0]

    result = (
        "Maintenance Required"
        if prediction == 1
        else "Engine Operating Normally"
    )

    st.success(f"Prediction Result: {result}")