  We introduce an interactive image segmentation and visualization framework
for identifying, inspecting, and editing tiny objects (just a few pixels wide)
in large multi-megapixel high-dynamic-range (HDR) images. Detecting cosmic rays
(CRs) in astronomical observations is a cumbersome workflow that requires
multiple tools, so we developed an interactive toolkit that unifies model
inference, HDR image visualization, segmentation mask inspection and editing
into a single graphical user interface. The feature set, initially designed for
astronomical data, makes this work a useful research-supporting tool for
human-in-the-loop tiny-object segmentation in scientific areas like
biomedicine, materials science, remote sensing, etc., as well as computer
vision. Our interface features mouse-controlled, synchronized, dual-window
visualization of the image and the segmentation mask, a critical feature for
locating tiny objects in multi-megapixel images. The browser-based tool can be
readily hosted on the web to provide multi-user access and GPU acceleration for
any device. The toolkit can also be used as a high-precision annotation tool,
or adapted as the frontend for an interactive machine learning framework. Our
open-source dataset, CR detection model, and visualization toolkit are
available at https://github.com/cy-xu/cosmic-conn.
