Upload app.py

app.py

@@ -11,35 +11,37 @@ fs = project.get_feature_store()
 
 
 mr = project.get_model_registry()
-model = mr.get_model("iris_modal", version=1)
+model = mr.get_model("titan_modal", version=50)
 model_dir = model.download()
-model = joblib.load(model_dir + "/iris_model.pkl")
+model = joblib.load(model_dir + "/titan_model.pkl")
 
 
-def iris(sepal_length, sepal_width, petal_length, petal_width):
+def titan(pclass, sex, age, fare, famliy):
     input_list = []
-    input_list.append(sepal_length)
-    input_list.append(sepal_width)
-    input_list.append(petal_length)
-    input_list.append(petal_width)
+    input_list.append(pclass)
+    input_list.append(sex)
+    input_list.append(age)
+    input_list.append(fare)
+    input_list.append(famliy)
     # 'res' is a list of predictions returned as the label.
     res = model.predict(np.asarray(input_list).reshape(1, -1)) 
     # We add '[0]' to the result of the transformed 'res', because 'res' is a list, and we only want 
     # the first element.
-    flower_url = "https://raw.githubusercontent.com/featurestoreorg/serverless-ml-course/main/src/01-module/assets/" + res[0] + ".png"
-    img = Image.open(requests.get(flower_url, stream=True).raw)            
+    survivor_url = "https://raw.githubusercontent.com/Chaouo/Titanic_serverless_ML/main/image/"+ str(res[0]) + ".png"
+    img = Image.open(requests.get(survivor_url, stream=True).raw)                        
     return img
         
 demo = gr.Interface(
-    fn=iris,
-    title="Iris Flower Predictive Analytics",
-    description="Experiment with sepal/petal lengths/widths to predict which flower it is.",
+    fn=titan,
+    title="Titanic Survival Predictive Analytics",
+    description="Experiment with pclass, sex, age, fare, famliy to predict which flower it is.",
     allow_flagging="never",
     inputs=[
-        gr.inputs.Number(default=1.0, label="sepal length (cm)"),
-        gr.inputs.Number(default=1.0, label="sepal width (cm)"),
-        gr.inputs.Number(default=1.0, label="petal length (cm)"),
-        gr.inputs.Number(default=1.0, label="petal width (cm)"),
+        gr.inputs.Number(default=1.0, label="pclass (1-3)"),
+        gr.inputs.Number(default=1.0, label="sex (0 indecates male and 1 indecates female)"),
+        gr.inputs.Number(default=1.0, label="age"),
+        gr.inputs.Number(default=1.0, label="fare (0-512)"),
+        gr.inputs.Number(default=1.0, label="famliy (numbers)"),
         ],
     outputs=gr.Image(type="pil"))