Spaces:
Sleeping
Sleeping
File size: 4,524 Bytes
03289af | 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 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | import joblib
import pandas as pd
import gradio as gr
# ---------------- Load model bundle ----------------
bundle = joblib.load("best_model_v2_calibrated.joblib")
model = bundle["model"]
threshold = float(bundle["threshold"])
# ---------------- Output formatting ----------------
def format_output(lang, label, proba):
if lang == "বাংলা":
risk_text = "উচ্চ ঝুঁকি" if label == "High Risk" else "কম ঝুঁকি"
return (
f"### ফলাফল: **{risk_text}**\n"
f"- ঝুঁকির সম্ভাবনা (Probability): **{proba:.3f}**\n"
f"- Threshold: **{threshold:.2f}**\n\n"
"⚠️ এটি একটি **স্ক্রিনিং টুল**, চিকিৎসা নির্ণয় নয়। সমস্যা থাকলে ডাক্তারের পরামর্শ নিন।"
)
else:
return (
f"### Result: **{label}**\n"
f"- Risk probability: **{proba:.3f}**\n"
f"- Threshold: **{threshold:.2f}**\n\n"
"⚠️ This is a **screening tool**, not a medical diagnosis. If you have symptoms, consult a clinician."
)
def web_speak_html(text, lang):
voice_lang = "bn-BD" if lang == "বাংলা" else "en-US"
safe = text.replace("`", "").replace("\\", "\\\\").replace("'", "\\'")
return f"""
<div style="display:flex;gap:10px;align-items:center;">
<button onclick="(function(){{
const msg = new SpeechSynthesisUtterance('{safe}');
msg.lang = '{voice_lang}';
window.speechSynthesis.cancel();
window.speechSynthesis.speak(msg);
}})()" style="padding:10px 14px;border-radius:10px;border:1px solid #ccc;cursor:pointer;">
🔊 Speak / শোনান
</button>
<span style="opacity:0.7;">(Voice depends on browser installed voices)</span>
</div>
"""
# ---------------- Prediction ----------------
def predict(lang, age, gender, bmi, bp_sys, bp_dia, phys_days, dpq, smoking, alcohol, diabetes, cycle):
sample = pd.DataFrame([{
"Age": float(age),
"Gender": gender,
"BMI": float(bmi),
"BP_SYS": float(bp_sys),
"BP_DIA": float(bp_dia),
"Phys_Activity_Days": float(phys_days),
"DPQ_Score": float(dpq),
"Smoking_Indicator": float(smoking),
"Alcohol_Feature": float(alcohol),
"Diabetes_Indicator": float(diabetes),
"Cycle": cycle
}])
proba = float(model.predict_proba(sample)[:, 1][0])
pred = int(proba >= threshold)
label = "High Risk" if pred == 1 else "Low Risk"
md = format_output(lang, label, proba)
speak = web_speak_html(md, lang)
return md, speak
# ---------------- UI ----------------
with gr.Blocks(title="SleepGuardAI – Sleep Risk Screening") as demo:
gr.Markdown("# SleepGuardAI – Sleep Risk Screening (NHANES-based)")
gr.Markdown("Fill the form → get risk score. Bilingual output + Speak button included.")
lang = gr.Radio(["English", "বাংলা"], value="English", label="Language / ভাষা")
with gr.Row():
age = gr.Slider(10, 90, value=30, label="Age / বয়স")
gender = gr.Dropdown(["Male", "Female"], value="Male", label="Gender")
with gr.Row():
bmi = gr.Slider(10, 50, value=25, label="BMI")
bp_sys = gr.Slider(80, 220, value=120, label="Systolic BP")
bp_dia = gr.Slider(40, 140, value=80, label="Diastolic BP")
phys = gr.Slider(0, 7, value=3, step=1, label="Physical Activity Days/Week")
gr.Markdown("### Optional (improves accuracy if known)")
with gr.Row():
dpq = gr.Slider(0, 27, value=0, step=1, label="DPQ Depression Score (0–27)")
smoking = gr.Dropdown([1, 2], value=2, label="Smoking (1=Yes, 2=No)")
diabetes = gr.Dropdown([1, 2], value=2, label="Diabetes (1=Yes, 2=No)")
alcohol = gr.Slider(0, 30, value=0, step=1, label="Alcohol feature (proxy)")
cycle = gr.Dropdown(["G", "H", "I", "J"], value="J", label="NHANES Cycle")
btn = gr.Button("Predict / ফলাফল দেখুন")
out_md = gr.Markdown()
out_speak = gr.HTML()
btn.click(
predict,
inputs=[lang, age, gender, bmi, bp_sys, bp_dia, phys, dpq, smoking, alcohol, diabetes, cycle],
outputs=[out_md, out_speak]
)
demo.launch()
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