Download and install the latest version of Filestar.
Right click on one or more Psp file(s) on your desktop and select Convert with Filestar.
Type convert to face in the search box.
Press Convert.
Or let an AI agent do it: filestarcli -i photo.psp -c "convert to face" (how).
Documents - File Explorer─☐✕
This PC › Documents
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Desktop
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.pspContract.psp
.xlsxBudget.xlsx
.pdfReport.pdf
.pngLogo.png
Filestar*Help✕
Drop files here to get started
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Let your AI agent convert PSP to FACE
Claude Code, Codex, Cursor and other agents can do this on your computer with Filestar. Your files stay on your machine.
Install Filestar and add it to your agents:
npm install -g filestar
filestarcli agent install
Then ask your agent:
“Convert the PSP files in my Downloads folder to FACE”
Or run it yourself:
filestarcli -i photo.psp -c "convert to face"
Runs on your computer, so your files stay on it. Works on Windows, macOS and Linux. 50 free conversions with the npm install, no account needed.
Can my AI agent convert PSP to FACE?
Yes. Install the Filestar CLI with npm install -g filestar and your agent can run filestarcli -i photo.psp -c "convert to face" on your computer, so your files stay on it.
PSP file format is associated with PaintShop Pro, an image editing software developed by Corel. It is a proprietary format used for storing raster graphics created and manipulated within PaintShop Pro. PSP files support layers, channels, and various other advanced graphics elements, allowing for detailed and complex image editing. This format is primarily used for saving intermediate edits, enabling users to continue working on their projects with all elements intact.
The face file type is associated with the Usenix FaceServer, a software tool designed for the management and distribution of digital images of faces. Originally developed for use in UNIX systems, it serves as a database for storing and retrieving facial images, often used in academic and research settings. The face file typically contains the digital image data of a person's face, along with metadata such as identification and attributes. This format is specifically tailored for applications requiring facial recognition and categorization, playing a crucial role in studies related to computer vision and human-computer interaction.
