Download and install the latest version of Filestar.
Right click on one or more Vda file(s) on your desktop and select Convert with Filestar.
Type convert to viff in the search box.
Press Convert.
Or let an AI agent do it: filestarcli -i photo.vda -c "convert to viff" (how).
Documents - File Explorer─☐✕
This PC › Documents
Home
Desktop
Downloads
Documents
Pictures
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.vdaContract.vda
.xlsxBudget.xlsx
.pdfReport.pdf
.pngLogo.png
Filestar*Help✕
Drop files here to get started
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Let your AI agent convert VDA to VIFF
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 VDA files in my Downloads folder to VIFF”
Or run it yourself:
filestarcli -i photo.vda -c "convert to viff"
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 VDA to VIFF?
Yes. Install the Filestar CLI with npm install -g filestar and your agent can run filestarcli -i photo.vda -c "convert to viff" on your computer, so your files stay on it.
The VDA file format, short for Targa Bitmap Image File, is a variant of the TGA file format (Truevision Advanced Raster Graphics Adapter) used for storing digital images. Developed by Truevision Inc., VDA files are raster graphics files that support various color depths, ranging from 1 to 32 bits per pixel, which includes support for alpha channels and compression. This format is designed to be highly flexible and is capable of storing high-quality images used in video editing and animations.
The Visualization Image File Format (VIFF) is a specialized file format designed for storing image data. It is primarily used in scientific and technical applications where complex visualization of multi-dimensional data is required. VIFF files can store various types of data including grayscale, color, and multi-spectral images, making them suitable for tasks such as image processing, medical imaging, and remote sensing. This format supports a range of metadata, allowing for the inclusion of information about the image data, such as dimensions and color.
