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Runtime error
SamuelHarner
commited on
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48ccf8f
1
Parent(s):
f4d7fc2
Upload app.py
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app.py
CHANGED
@@ -15,11 +15,14 @@ model = joblib.load(model_dir + "/wine_model.pkl")
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print("Model downloaded")
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def wine(fixed_acidity, citric_acid,
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print("Calling function")
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# df = pd.DataFrame([[sepal_length],[sepal_width],[petal_length],[petal_width]],
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df = pd.DataFrame([[fixed_acidity, citric_acid,
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print("Predicting")
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print(df)
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# 'res' is a list of predictions returned as the label.
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@@ -28,6 +31,7 @@ def wine(fixed_acidity, citric_acid, type_white, chlorides, volatile_acidity, de
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# the first element.
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# print("Res: {0}").format(res)
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print(res)
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star_url = "https://raw.githubusercontent.com/SamuelHarner/review-images/main/images/" + str(res[0]) + "_stars.png"
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img = Image.open(requests.get(star_url, stream=True).raw)
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return img
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@@ -39,13 +43,17 @@ demo = gr.Interface(
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"to predict of which quality the wine is.",
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allow_flagging="never",
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inputs=[
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gr.inputs.Number(default=7.2, label="fixed acidity"),
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gr.inputs.Number(default=0.34, label="volatile acidity"),
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gr.inputs.Number(default=0.32, label="citric acid"),
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gr.inputs.
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gr.inputs.Number(default=10.5, label="alcohol"),
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gr.inputs.Number(default=0.99, label="density"),
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gr.inputs.Number(default=0.06, label="chlorides"),
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],
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outputs=gr.Image(type="pil"))
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print("Model downloaded")
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def wine(fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides,
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free_sulfur_dioxide, density, pH, sulphates, alcohol, type_red):
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print("Calling function")
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# df = pd.DataFrame([[sepal_length],[sepal_width],[petal_length],[petal_width]],
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df = pd.DataFrame([[fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides,
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free_sulfur_dioxide, density, pH, sulphates, alcohol, type_red]],
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columns=['fixed_acidity', 'volatile_acidity', 'citric_acid', 'residual_sugar', 'chlorides',
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'free_sulfur_dioxide', 'density', 'pH', 'sulphates', 'alcohol', 'type_red'])
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print("Predicting")
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print(df)
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# 'res' is a list of predictions returned as the label.
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# the first element.
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# print("Res: {0}").format(res)
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print(res)
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+
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star_url = "https://raw.githubusercontent.com/SamuelHarner/review-images/main/images/" + str(res[0]) + "_stars.png"
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img = Image.open(requests.get(star_url, stream=True).raw)
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return img
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"to predict of which quality the wine is.",
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allow_flagging="never",
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inputs=[
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gr.inputs.Number(default=7.2, label="fixed acidity (3.8 ... 15.9)"),
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gr.inputs.Number(default=0.34, label="volatile acidity (0.00 ... 1.58)"),
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gr.inputs.Number(default=0.32, label="citric acid (0.00 ... 1.66)"),
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gr.inputs.Number(default=0, label="type (0...red, 1...white)"),
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gr.inputs.Number(default=10.5, label="alcohol (8.0 ... 14.9"),
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gr.inputs.Number(default=0.99, label="density (0.99 ... 1.04)"),
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gr.inputs.Number(default=0.06, label="chlorides (0.00 ...0.61)"),
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gr.inputs.Number(default=5.07, label="residual sugar (0.60 ...65.80)"),
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gr.inputs.Number(default=30.06, label="free sulfur dioxide (1.0 ...289.0)"),
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gr.inputs.Number(default=3.22, label="pH (2.72 ...4.01)"),
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gr.inputs.Number(default=0.53, label="sulphates (0.00 ...2.00)"),
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],
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outputs=gr.Image(type="pil"))
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