Batch Processing
How a high-volume photo lab enhances thousands of customer images per day with the VIESUS CLI — and which interface and settings fit the workflow.
The scenario: A photo lab receives thousands of customer images per day across many orders. Images vary in size and quality, and every order must come back enhanced with consistent settings — without anyone editing images by hand.
Recommended interface
The CLI reads a list of images (or a folder), applies one shared configuration to every image, and writes the enhanced files out. For interactive workloads behind a web service instead, see the Node.js module; for PDFs, see PDF Processing.
How it works
You define one enhancement configuration (
viesusini.json) and reuse it across the whole lab, so results stay consistent regardless of who runs the job.The CLI processes a batch — a folder or an image list — in one run, writing each enhanced image to a destination folder.
A per-image result file records the status of every image, which your monitoring can scan to confirm an order completed cleanly.
Throughput scales by running more CLI instances in parallel — for example one per order, or one per GPU on a multi-GPU machine.
What to consider
Hardware
A compatible NVIDIA GPU is recommended for AI features (AI upscaling, Artifact Removal) and speed. Standard enhancement also runs on CPU. See System Requirements.
Consistency
Keep a single configuration per product type so every order is enhanced identically.
Throughput
Plan capacity against your daily volume — see Benchmarks and Performance Tuning.
Scaling
Parallelism comes from running multiple instances, not from one giant job.
Storage
Enhanced output can be larger than compressed input — size your output storage accordingly.
Licensing
A GUID suits servers that scale; an Activation Key suits a fixed machine. See Licensing.
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