Create app.py

app.py

@@ -0,0 +1,65 @@
+import gradio as gr
+import pandas as pd
+from joblib import load
+
+
+
+def cardio(age,is_male,ap_hi,ap_lo,cholesterol,gluc,smoke,alco,active,height,weight,BMI):
+    model = load('cardiosight.joblib')
+    df = pd.DataFrame.from_dict(
+        {
+            "age": [age*365],
+            "gender":[0 if is_male else 1],
+            "ap_hi": [ap_hi],
+            "ap_lo": [ap_lo],
+            "cholesterol": [cholesterol + 1],
+            "gluc": [gluc + 1],
+            "smoke":[1 if smoke else 0],
+            "alco": [1 if alco else 0],
+            "active": [1 if active else 0],
+            "newvalues_height": [height],
+            "newvalues_weight": [weight],
+            "New_values_BMI": [BMI],
+            
+        }
+    )
+       
+    pred = model.predict(df)[0]
+    if pred==1:
+      predicted="Tiene un riesgo alto de sufrir problemas cardiovasculares"
+    else:
+      predicted="Su riesgo de sufrir problemas cardiovasculares es muy bajo. Siga así."
+    return predicted
+    
+iface = gr.Interface(
+    cardio,
+    [
+        gr.inputs.Slider(1,99,label="Age"),
+        "checkbox",
+        gr.inputs.Slider(10,250,label="Diastolic Preassure"),
+        gr.inputs.Slider(10,250,label="Sistolic Preassure"),
+        gr.inputs.Radio(["Normal","High","Very High"],type="index",label="Cholesterol"),
+        gr.inputs.Radio(["Normal","High","Very High"],type="index",label="Glucosa Level"),
+        "checkbox",
+        "checkbox",
+        "checkbox",
+        gr.inputs.Slider(30,220,label="Height in cm"),
+        gr.inputs.Slider(10,300,label="Weight in Kg"),
+        gr.inputs.Slider(1,50,label="BMI"),
+    ],
+
+    "text",
+    examples=[
+        [40,True,120,80,"High","Normal",0,0,1,168,62,21],
+        [35,False,150,60,"Very High","Normal",0,0,1,143,52,31],
+        [60,True,160,70,"High","High",1,1,0,185,90,23],
+    ],
+    interpretation="default",
+    title = 'Calculadora de Riesgo Cardiovascular mediante Inteligencia Artificial',
+    description = 'El proyecto de CARDIOSIGHT nace debido a la presente necesidad en nuestro país de crear métodos y herramientas de identificación temprana para los individuos con alto riesgo de sufrir enfermedades cardiovasculares. Con el fin de prevenir eventos cardíacos primarios y ayudar a disminuir la incidencia de nuevos casos, por medio de hábitos de prevención. Mas información: https://saturdays.ai/2022/03/16/cardiosight-machine-learning-para-calcular-riesgo-cardiovascular/',
+    theme = 'grass'
+)
+
+
+   
+iface.launch()