Topaz Labs have recently released an update the Gigapixel AI utility (V5.0.0) and to celebrate are offering a discount on the package. If you are already a current Gigapixel owner you can simply download the update at no cost.
From 25th June 2020 to 7th July 2020 Gigapixel AI is available for $79.99 USD instead of the regular $99.99 USD, furthermore the Utility Bundle which also includes JPEG to RAW AI, DeNoise AI, Sharpen AI and Gigapixel AI is on sale for the same period, and is discounted to $195 USD instead of the regular $249.99 USD.
In addition to the above discounts, if you use the discount code TravisHale during checkout you can get an additional discount on any purchases.
In terms of Gigapixel AI, the change log is as follows;
- New previewing mode: Single Image View
- New zoom features: zoom to fit, a zoom slider, text field input, and scroll wheel to zoom
- Updated AI models
- “Image Type” selection on the right panel: choose between two different AI models, one for natural images (portraits, nature) and man-made images (cityscapes, typography)
- Preview panning responsiveness has been drastically improved
- Images that have not been successfully loaded or could cause a crash when processing now pop up a warning that gives more in-depth information for better troubleshooting. Unsupported images include images in the CMYK color space and images with more than four channels (alpha masking channels that have been turned off in Photoshop, for example)
- New auto-updater: new version installer will now download from within the application
- Updated back-end CPU processing library
- Added ability to right-click to select preset zoom amounts
- Able to now pan on both the original image and the preview image
- Preview window has been made bigger
- Certain images should no longer successfully process then fail to save out the image – this was due to corrupted image metadata that was silently failing when exporting the image. Default metadata will now be used.
- Preview should no longer double process (spinner reaches 100%, then starts over) in most situations. If it does occur please post here with steps on how to replicate.