From 807164276cd51143c9f072994afa1513f145c587 Mon Sep 17 00:00:00 2001 From: polyaxon-team Date: Fri, 4 Sep 2020 00:02:40 +0200 Subject: [PATCH] Update --- in_cluster/sklearn/iris/app.py | 57 ++++++++++++++++++ .../sklearn/iris/hyper-polyaxonfile.yml | 19 ++++++ .../sklearn/iris/images/iris-setosa.png | Bin 0 -> 61976 bytes .../sklearn/iris/images/iris-versicolor.png | Bin 0 -> 67908 bytes .../sklearn/iris/images/iris-virginica.png | Bin 0 -> 65423 bytes .../sklearn/iris/streamlit-polyaxonfile.yml | 22 +++++++ 6 files changed, 98 insertions(+) create mode 100644 in_cluster/sklearn/iris/app.py create mode 100644 in_cluster/sklearn/iris/hyper-polyaxonfile.yml create mode 100644 in_cluster/sklearn/iris/images/iris-setosa.png create mode 100644 in_cluster/sklearn/iris/images/iris-versicolor.png create mode 100644 in_cluster/sklearn/iris/images/iris-virginica.png create mode 100644 in_cluster/sklearn/iris/streamlit-polyaxonfile.yml diff --git a/in_cluster/sklearn/iris/app.py b/in_cluster/sklearn/iris/app.py new file mode 100644 index 0000000..56beb5b --- /dev/null +++ b/in_cluster/sklearn/iris/app.py @@ -0,0 +1,57 @@ +import streamlit as st +import pandas as pd +import joblib +import argparse + +from PIL import Image + + +def load_model(model_path: str): + model = open(model_path, "rb") + return joblib.load(model) + + +if __name__ == '__main__': + parser = argparse.ArgumentParser() + parser.add_argument( + '--model-path', + type=str, + ) + args = parser.parse_args() + + setosa = Image.open("images/iris-setosa.png") + versicolor = Image.open("images/iris-versicolor.png") + virginica = Image.open("images/iris-virginica.png") + classifier = load_model(args.model_path) + print(classifier) + + st.title("Iris flower species Classification") + st.sidebar.title("Features") + parameter_list = [ + "Sepal length (cm)", + "Sepal Width (cm)", + "Petal length (cm)", + "Petal Width (cm)" + ] + sliders = [] + for parameter, parameter_df in zip(parameter_list, ['5.2', '3.2', '4.2', '1.2']): + values = st.sidebar.slider( + label=parameter, + key=parameter, + value=float(parameter_df), + min_value=0.0, + max_value=8.0, + step=0.1 + ) + sliders.append(values) + + input_variables = pd.DataFrame([sliders], columns=parameter_list) + + prediction = classifier.predict(input_variables) + if prediction == 0: + st.image(setosa) + elif prediction == 1: + st.image(versicolor) + else: + st.image(virginica) + diff --git a/in_cluster/sklearn/iris/hyper-polyaxonfile.yml b/in_cluster/sklearn/iris/hyper-polyaxonfile.yml new file mode 100644 index 0000000..69b353b --- /dev/null +++ b/in_cluster/sklearn/iris/hyper-polyaxonfile.yml @@ -0,0 +1,19 @@ +version: 1.1 +kind: operation +matrix: + kind: random + numRuns: 15 + params: + n_neighbors: + kind: range + value: "3:50:5" + leaf_size: + kind: choice + value: [5, 10, 20, 30] + metric: + kind: pchoice + value: [[minkowski, 0.8], [euclidean, 0.2]] + test_size: + kind: choice + value: [0.2, 0.3, 0.4] +urlRef: 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