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Image logging is supported on the platform that are in the format of: To log an image, instantiate the pluto.Image class. 
img = pluto.Image(
    data: Union[str, PILImage.Image, matplotlib.figure.Figure, torch.Tensor, np.ndarray],
    caption: str | None = None,
)
pluto.log({"image/file/0-0": img}, step=step)
ParameterTypeDescription
dataUnion[str, PILImage.Image, matplotlib.figure.Figure, torch.Tensor, np.ndarray]The image data to log. Can be a path to an image file, a PIL image, a Matplotlib figure, a PyTorch tensor, or a NumPy array.
captionstrA caption for the image.

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Viewing Images in the Dashboard

Logged images appear as gallery cards in the dashboard, grouped by their metric label prefix. When comparing multiple runs, images from each run are shown side-by-side. Images in the Pluto dashboard

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Step Navigation

Use the step navigator below the image gallery to browse images logged at different training steps. You can click the forward/back arrows or type a specific step number to jump directly to it. The navigator shows the current step and total available steps (e.g., “Step 0/25”).

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Multi-Run Comparison

When multiple runs are selected in the Compare view, images logged with the same metric label are displayed together, with each run’s image labeled with the run name and ID. This makes it easy to visually compare outputs across experiments.