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| import gradio as gr | |
| from PIL import Image, ImageDraw, ImageFont | |
| import requests | |
| import hopsworks | |
| import joblib | |
| import pandas as pd | |
| project = hopsworks.login() | |
| fs = project.get_feature_store() | |
| mr = project.get_model_registry() | |
| model = mr.get_model("wine_model", version=2) | |
| model_dir = model.download() | |
| model = joblib.load(model_dir + "/wine_model.pkl") | |
| print("Model downloaded") | |
| def wine(fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, | |
| free_sulfur_dioxide, density, pH, sulphates, alcohol, type_red): | |
| print("Calling function") | |
| # df = pd.DataFrame([[sepal_length],[sepal_width],[petal_length],[petal_width]], | |
| df = pd.DataFrame([[fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, | |
| free_sulfur_dioxide, density, pH, sulphates, alcohol, type_red]], | |
| columns=['fixed_acidity', 'volatile_acidity', 'citric_acid', 'residual_sugar', 'chlorides', | |
| 'free_sulfur_dioxide', 'density', 'pH', 'sulphates', 'alcohol', 'type_red']) | |
| print("Predicting") | |
| print(df) | |
| # 'res' is a list of predictions returned as the label. | |
| res = model.predict(df) | |
| # We add '[0]' to the result of the transformed 'res', because 'res' is a list, and we only want | |
| # the first element. | |
| # print("Res: {0}").format(res) | |
| print(res) | |
| star_url = "https://raw.githubusercontent.com/SamuelHarner/review-images/main/images/" + str(res[0]) + "_stars.png" | |
| img = Image.open(requests.get(star_url, stream=True).raw) | |
| return img | |
| demo = gr.Interface( | |
| fn=wine, | |
| title="Wine Quality Predictive Analytics", | |
| description="Experiment with fixed_acidity, citric_acid, type, chlorides, volatile_acidity, density, alcohol" | |
| "to predict of which quality the wine is.", | |
| allow_flagging="never", | |
| inputs=[ | |
| gr.inputs.Number(default=7.2, label="fixed acidity (3.8 ... 15.9)"), | |
| gr.inputs.Number(default=0.34, label="volatile acidity (0.00 ... 1.58)"), | |
| gr.inputs.Number(default=0.32, label="citric acid (0.00 ... 1.66)"), | |
| gr.inputs.Number(default=0, label="type (0...red, 1...white)"), | |
| gr.inputs.Number(default=10.5, label="alcohol (8.0 ... 14.9"), | |
| gr.inputs.Number(default=0.99, label="density (0.99 ... 1.04)"), | |
| gr.inputs.Number(default=0.06, label="chlorides (0.00 ...0.61)"), | |
| gr.inputs.Number(default=5.07, label="residual sugar (0.60 ...65.80)"), | |
| gr.inputs.Number(default=30.06, label="free sulfur dioxide (1.0 ...289.0)"), | |
| gr.inputs.Number(default=3.22, label="pH (2.72 ...4.01)"), | |
| gr.inputs.Number(default=0.53, label="sulphates (0.00 ...2.00)"), | |
| ], | |
| outputs=gr.Image(type="pil")) | |
| demo.launch(debug=True) | |