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import gradio as gr |
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from PIL import Image, ImageDraw, ImageFont |
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import requests |
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import hopsworks |
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import joblib |
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import pandas as pd |
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project = hopsworks.login() |
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fs = project.get_feature_store() |
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mr = project.get_model_registry() |
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model = mr.get_model("wine_model", version=1) |
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model_dir = model.download() |
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model = joblib.load(model_dir + "/wine_model.pkl") |
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print("Model downloaded") |
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columns = ['type_white','fixed_acidity','volatile_acidity','citric_acid','residual_sugar','chlorides','free_sulfur_dioxide','total_sulfur_dioxide','density','alcohol'] |
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def get_image_with_text(text): |
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img = Image.new(size=(200,200),mode="RGBA", color='white') |
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draw = ImageDraw.Draw(img) |
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font = ImageFont.load_default(size=150) |
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draw.text((50,0), text, font=font, fill=(0, 0, 0, 0)) |
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return img |
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def wine(type_white,fixed_acidity,volatile_acidity,citric_acid,residual_sugar,chlorides,free_sulfur_dioxide,total_sulfur_dioxide,density,alcohol): |
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print("Calling function") |
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df = pd.DataFrame([[type_white,fixed_acidity,volatile_acidity,citric_acid,residual_sugar,chlorides,free_sulfur_dioxide,total_sulfur_dioxide,density,alcohol]], |
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columns=columns) |
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print("Predicting") |
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print(df) |
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res = model.predict(df) |
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res_text = f'the predicted quality of your wine was {res[0]}' |
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print(res) |
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img = get_image_with_text(f'{res[0]}') |
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return img,res_text |
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demo = gr.Interface( |
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fn=wine, |
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title="Wine Quality Predictive Analytics", |
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description="Experiment with the features to predict which quality the wine is.", |
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allow_flagging="never", |
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inputs=[ |
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gr.Number(value=1.0, label='is_white_wine (1/0)'), |
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gr.Number(value=7.0, label=columns[1]), |
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gr.Number(value=0.20, label=columns[2]), |
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gr.Number(value=0.25, label=columns[3]), |
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gr.Number(value=9.0, label=columns[4]), |
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gr.Number(value=0.05, label=columns[5]), |
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gr.Number(value=40.0, label=columns[6]), |
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gr.Number(value=150.0, label=columns[7]), |
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gr.Number(value=0.9950, label=columns[8]), |
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gr.Number(value=10.0, label=columns[9]), |
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], |
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outputs=[ |
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gr.Image(type="pil"), |
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gr.Text(), |
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] |
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) |
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demo.launch(debug=True) |
