app.py

heart predictor.py

@@ -0,0 +1,42 @@
+import numpy as np
+import gradio as gr
+import pickle
+from sklearn.preprocessing import normalize
+
+model = pickle.load(open("C:/Users/Admin/Downloads/model.pkl", 'rb'))
+
+def predict(Age, CigsPerDay, Cholestrol, SysBP, DIaBP, BMI, HeartRate, GlucoseLevel, Gender, BpMedication, PrevalentStroke, Smoker):
+    '''
+    For making predictions
+    '''
+    list_to_be_normalised = np.array([Age, CigsPerDay, Cholestrol, SysBP, DIaBP, BMI, HeartRate, GlucoseLevel]).reshape(1, -1)
+    normalized = normalize(list_to_be_normalised)
+    boolean = [Gender, BpMedication, PrevalentStroke, Smoker]
+    final_features = np.append(normalized, boolean).reshape(1, -1)
+    prediction = model.predict(final_features)
+
+    if prediction == 1:
+        return "problem"
+    else:
+        return "healthy"
+    
+iface = gr.Interface(
+    fn=predict,
+    inputs=[
+        gr.inputs.Number(label="Age (Enter Age)", default=40),
+        gr.inputs.Number(label="CigsPerDay (Enter Cigarettes Per Day)", default=10),
+        gr.inputs.Number(label="Cholesterol (Enter Cholesterol Level)", default=200),
+        gr.inputs.Number(label="SysBP (Enter Systolic Blood Pressure)", default=120),
+        gr.inputs.Number(label="DIaBP (Enter Diastolic Blood Pressure)", default=80),
+        gr.inputs.Number(label="BMI (Enter Body Mass Index)", default=25),
+        gr.inputs.Number(label="HeartRate (Enter Heart Rate)", default=70),
+        gr.inputs.Number(label="GlucoseLevel (Enter Glucose Level)", default=100),
+        gr.inputs.Checkbox(label="Gender (Select Gender)"),
+        gr.inputs.Checkbox(label="BpMedication (Select Blood Pressure Medication)"),
+        gr.inputs.Checkbox(label="PrevalentStroke (Select Prevalent Stroke)"),
+        gr.inputs.Checkbox(label="Smoker (Select Smoker)"),
+    ],
+    outputs=gr.outputs.Textbox(label="Prediction"),
+)
+
+iface.launch()