Below is a quick attempt to make V7 look a bit younger. To me default V7 looks around 25ish, but I agree that this is a matter of opinion. I find that the G3F bunch look a bit too old to me for some reason. Old? She looks like a young woman to me : ) I'll be blowing the dust off the old wallet and making some extra purchases next month then. Thats good news if they do then because I really like some of the Belle 6 characters and textures. Really? I thought it sounded a bit crazy, but I didn't question it because I thought "Hey, its Daz! It could easily be true.". I mean I can't show you screenshots to prove it, being that this forum isn't rated for that, but.yeah, they do, both Belle 6 and Teen Josie 6. I.what? Heh someone was seriously pulling your leg if they told you that. I never used the Josie textures, probably didn't even realize she didn't have areolas.never had any need for belle. Though I can understand not wanting to fork over the funds for that. You can still use your other textures and dial in a bit of teen to soften the older gals looks. I think I only used Josie on 2 characters, but it was small amounts at that. Just keep in mind you don't have to use Josie or Belle textures or their complete shape. Its basically the same reason why I wouldn't buy a model that lacked fingernail textures, or ear textures etc. I don't see the point in buying a human figure that lacks nipples. Yeah I heard that Teen Josie 7 might be coming out soon, but I tend to avoid the teen models like Josie and Belle because I heard that they don't have nipples and although I don't intend to try to render any naked teens I do like the models I buy to be complete in all senses regardless, in case I want to use their textures for something else in the future. Thats true, I hadn't thought about the youth morphs. You can always dial in the young facial morph to soften their features I think, and if you´d really like a younger figure, Teen Josie 7 seems to be coming out soon.
#MORPH AGE SAVING IMAGE CODE#
KerasĪ Keras port of this code was recently developed and made available at. Also see the the file-diff comparing CORAL with regular CNN. We provide a recipe for porting the code is provided at coral-implementation-recipe.ipynb. Our models were originally implemented in PyTorch 1.5. Implementations for Other Deep Learning Frameworks Porting Guide
Single-image-prediction_w-pretrained-models subdirectory for details. We share the pre-trained models from the paper that can be used to make predictions on AFAD, MORPH-2, or CACD images.
Here is an overview of the differences between a regular CNN and a CORAL-CNN: outpath : Path for saving the training log ( training.log)Īnd the parameters of the trained model ( model.pt). cuda : The CUDA device number of the GPU to be used for training The model weight initialization (note that CUDA convolutions are not fully deterministic). seed : Integer for the random seed used for training set shuffling and Python afad-coral.py -seed 1 -cuda 0 -outpath afad-model1 The model code can be found in the (./model-code) subdirectory, and the code files are labeled using the scheme In the scripts depending on where you save the image datasets and label filesĪll code was run on PyTorch 1.5 and Python 3.7,Īnd we do not guarantee upward and downward compatibility The file paths to the datasets at the top of the file and using dataloaders specific to Is identical for the different datasets, however, we hard coded If you are primarily interested in using CORAL, a PyTorch library with Tutorials can be found here:
This GitHub repository contains the code files and training logs used in the paper.
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