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Clusterfun is an open-source python plotting library to explore images in your plots.
After installing clusterfun with
After installing clusterfun with
pip install clusterfun, you can create the above plot locally, without any additional setup:import pandas as pd
import clusterfun as clt
df = pd.read_csv("https://raw.githubusercontent.com/gietema/clusterfun-data/main/mnist.csv")
clt.scatter(df, x="x", y="y", media="img_path", color="label")import pandas as pd
import clusterfun as clt
df = pd.read_csv("https://raw.githubusercontent.com/gietema/clusterfun-data/main/mnist.csv")
clt.confusion_matrix(df, y_true="label", y_pred="pred", media="img_path")import pandas as pd
import clusterfun as clt
df = pd.read_csv("https://raw.githubusercontent.com/gietema/clusterfun-data/main/mnist.csv")
clt.violin(df, y="mean_value", color="label", media="img_path")Why clusterfun?
- Lightweight
As opposed to big data analysis platforms (Scale, Encord), clusterfun allows you to review data within a minute. All you need is apandasdataframe with an image location per row. Data can be hosted locally or on AWS S3. No sign up, integration, or data transfer is needed. - Flexible
Clusterfun is a plotting library, which means that you determine what the x- and y-axis represent. This gives you the freedom to plot what you want. The additional benefit of a plot is that it allows you to see how close a data point is to another data point, which is more difficult in an image grid visualisation. - Interactive
As opposed to static plots, clusterfun allows you to hover, select, and zoom in on data slices.