This adds up to a total of 7% of Imagenet data trained once (3 hours of direct GAN training). This model was trained with 3 critic pretrain/GAN cycle repeats via NoGAN, in addition to the initial generator/critic pretrain/GAN NoGAN training, at 192px. This model uses a resnet101 backbone on a UNet with an emphasis on width of layers on the decoder side. It generally has less weird miscolorations than artistic, but it's also less colorful in general. Notably, it produces less "zombies"- where faces or limbs stay gray rather than being colored in properly. Stable: This model achieves the best results with landscapes and portraits. This adds up to a total of 32% of Imagenet data trained once (12.5 hours of direct GAN training).
Fortunately, DeepAI allows the submission of jobs with an API. This model was trained with 5 critic pretrain/GAN cycle repeats via NoGAN, in addition to the initial generator/critic pretrain/GAN NoGAN training, at 192px. As far as I know, the paid version of deepAI also doesn’t support larger images, if they do please let me know. The model uses a resnet34 backbone on a UNet with an emphasis on depth of layers on the decoder side. Additionally, the model does not do as well as stable in a few key common scenarios- nature scenes and portraits. The most notable drawback however is that it's a bit of a pain to fiddle around with to get the best results (you have to adjust the rendering resolution or render_factor to achieve this). Something to keep in mind- historical accuracy remains a huge challenge! About the demoĪrtistic: This model achieves the highest quality results in image coloration, in terms of interesting details and vibrance. We'll get into the details in a bit, but first let's see some
Simply put, the mission of this project is to colorize and restore old images andįilm footage. Try a few images for free! MyHeritage In Color
The most advanced version of DeOldify image colorization is available here,Įxclusively.
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