Image Upscaling

DeepImage takes a low-resolution image and generates a larger version with the missing detail filled in by a model. A Beam agent reads new images added to a folder or queue, applies the account's rule for which images qualify, such as a minimum starting resolution or a specific product category, and starts the upscale before updating the record with the finished file. Results that come back visibly distorted, or images the rule doesn't clearly cover, like a scanned document instead of a photo, are set aside for a person to check by eye. This keeps the automatic step limited to images it actually handles well.

Background Removal

DeepImage can strip the background out of a photo, leaving just the subject on a transparent layer. A Beam agent reads images tagged for background removal, applies the account's rule for what should happen next, for example dropping the cut-out subject onto a standard product template, and updates the listing or file once the result comes back. Cut-outs with rough edges around hair, fur or fine detail, or a background the model can't cleanly separate from the subject, are routed to a person to finish by hand. This keeps automatic cut-outs limited to images clean enough for the model to handle well.

Noise and Blur Correction

DeepImage can reduce noise in a grainy photo and sharpen a slightly blurred one without a full upscale. A Beam agent reads which correction a batch of images calls for under the account's rule, for example a set of low-light photos flagged for denoising, and applies the correction before updating the file. Images that stay noisy or blurred after correction, or ones where the source damage is severe enough that the rule marks it for manual work, are left for a person to look at directly. This keeps the automatic pass limited to fixable images instead of forcing a result that still looks poor.