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| import gradio as gr | |
| import numpy as np | |
| from PIL import Image | |
| import requests | |
| import hopsworks | |
| import joblib | |
| project = hopsworks.login() | |
| 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, sibsp, parch, fare, embarked): | |
| input_list = [] | |
| if sex == 'female': | |
| input_list.append(1.0) | |
| input_list.append(0.0) | |
| elif sex == 'male': | |
| input_list.append(0.0) | |
| input_list.append(1.0) | |
| else: | |
| print("ERROR!") | |
| exit() | |
| if embarked == "C": | |
| input_list.append(1.0) | |
| input_list.append(0.0) | |
| input_list.append(0.0) | |
| elif embarked == "Q": | |
| input_list.append(0.0) | |
| input_list.append(1.0) | |
| input_list.append(0.0) | |
| elif embarked == "S": | |
| input_list.append(0.0) | |
| input_list.append(0.0) | |
| input_list.append(1.0) | |
| else: | |
| print("ERROR!") | |
| exit() | |
| if age < 18: | |
| input_list.append(1.0) | |
| elif age < 55: | |
| input_list.append(2.0) | |
| else: | |
| input_list.append(3.0) | |
| input_list.append(sibsp) | |
| input_list.append(parch) | |
| input_list.append(fare) | |
| input_list.append(pclass) | |
| # '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. | |
| if res[0] == 1.0: | |
| survive_url = "https://raw.githubusercontent.com/Hope-Liang/ID2223Lab1/main/serverless-ml-titanic/images/survived.png" | |
| else: | |
| survive_url = "https://raw.githubusercontent.com/Hope-Liang/ID2223Lab1/main/serverless-ml-titanic/images/died.png" | |
| img = Image.open(requests.get(survive_url, stream=True).raw) | |
| return img | |
| demo = gr.Interface( | |
| fn=titanic, | |
| title="Titanic Survival Predictive Analytics", | |
| description="Experiment with titanic passenger features to predict whether survived or not.", | |
| allow_flagging="never", | |
| inputs=[ | |
| gr.inputs.Number(default=1, label="Pclass (1,2,3)"), | |
| gr.inputs.Textbox(default="female", label="Sex (female/male)"), | |
| gr.inputs.Number(default=30.0, label="age (years)"), | |
| gr.inputs.Number(default=1.0, label="SibSp"), | |
| gr.inputs.Number(default=1.0, label="Parch"), | |
| gr.inputs.Number(default=10.0, label="Fare (GBP)"), | |
| gr.inputs.Textbox(default="S", label="Embarked (S,C,Q)") | |
| ], | |
| outputs=gr.Image(type="pil")) | |
| demo.launch() | |