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README.md

@@ -1,10 +1,10 @@
 ---
-title: Titanic
-emoji: 🦀
-colorFrom: blue
-colorTo: red
+title: Iris
+emoji: 🐨
+colorFrom: yellow
+colorTo: yellow
 sdk: gradio
-sdk_version: 3.10.1
+sdk_version: 3.9.1
 app_file: app.py
 pinned: false
 ---

app.py

@@ -0,0 +1,52 @@
+import gradio as gr
+import numpy as np
+from PIL import Image
+import requests
+
+import hopsworks
+import joblib
+
+project = hopsworks.login(api_key_value="CDqcnm3gyfxjyCO8.TZwOClLOwCqDp33vX0P5Q2nsvNNyEhfBMArwNoPjnb9tUSSKq6I8X35HQ5D2tlJ7")
+fs = project.get_feature_store()
+
+
+mr = project.get_model_registry()
+model = mr.get_model("titanic_modal", version=1)
+model_dir = model.download()
+model = joblib.load(model_dir + "/titanic_model.pkl")
+
+
+def titanic(pclass, sex, age, sibs, par_ch, fare):
+    input_list = []
+    input_list.append(pclass)
+    input_list.append(sex)
+    input_list.append(age)
+    input_list.append(sibs)
+    input_list.append(par_ch)
+    input_list.append(fare)
+    input_list.append(np.random.choice([0,1], 9))
+    # '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.
+    man_url = "https://raw.githubusercontent.com/Tilosmsh/IL2223_lab1/main/images/" + ("survived.jpg" if res[0] else "dead.jpg")
+    img = Image.open(requests.get(man_url, stream=True).raw)            
+    return img
+        
+demo = gr.Interface(
+    fn=titanic,
+    title="Titanic Predictive Analytics",
+    description="Experiment with passenger class, sex, age, number of siblings, number of parents & children and fare, to predict whether the passenger survived.",
+    allow_flagging="never",
+    inputs=[
+        gr.inputs.Number(default=1, label="Passenger Class (0, 1 or 2)"),
+        gr.inputs.Number(default=1, label="Sex (0 or 1)"),
+        gr.inputs.Number(default=30.0, label="Age (0 to 80)"),
+        gr.inputs.Number(default=1, label="Number of Siblings (0 to 8)"),
+        gr.inputs.Number(default=1, label="Number of Parents and children (0 to 6)"),
+        gr.inputs.Number(default=35.0, label="Fare (0 to 513)"),
+        ],
+    outputs=gr.Image(type="pil"))
+
+demo.launch()
+