Spaces:
Runtime error
Runtime error
| 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=2) | |
| model_dir = model.download() | |
| model = joblib.load(model_dir + "/titanic_model.pkl") | |
| def titanic(pclass, sex, age_bin, fare_bin): | |
| input_list = [] | |
| input_list.append(pclass) | |
| input_list.append(sex) | |
| input_list.append(age_bin) | |
| input_list.append(fare_bin) | |
| # 'res' is a list of predictions returned as the label. | |
| res = model.predict(np.asarray(input_list).reshape(1, -1)) | |
| res_0 = str(res[0]) | |
| # We add '[0]' to the result of the transformed 'res', because 'res' is a list, and we only want | |
| # the first element. | |
| prediction_url = "https://raw.githubusercontent.com/torileatherman/serverless_ml_titanic/main/src/assets/"+res_0+".png" | |
| img = Image.open(requests.get(prediction_url, stream=True).raw) | |
| return img | |
| demo = gr.Interface( | |
| fn=titanic, | |
| title="Titanic Survival Predictive Analytics", | |
| description="Experiment with class, sex, age, and fare type to predict if the passenger survived", | |
| allow_flagging="never", | |
| inputs=[ | |
| gr.inputs.Number(default=1, label="Class (1 is highest, 3 is lowest"), | |
| gr.inputs.Number(default=1, label="Gender (0 is male, 1 is female)"), | |
| gr.inputs.Number(default=20, label="Age (years)"), | |
| gr.inputs.Number(default=1, label="Fare Type (1 is lowest, 4 is highest)"), | |
| ], | |
| outputs=gr.Image(type="pil")) | |
| demo.launch(share=True) |