SC-FEGAN

GitHub describes it as SC-FEGAN : Face Editing Generative Adversarial Network with User's Sketch and Color (ICCV2019). The repository metadata lists Python as its primary language. The metadata lists the NOASSERTION license. This article stays within the project description and details documented in the GitHub repository README.

GitHub describes it as SC-FEGAN : Face Editing Generative Adversarial Network with User's Sketch and Color (ICCV2019). The repository metadata lists Python as its primary language. The metadata lists the NOASSERTION license. The README describes the project this way: SC-FEGAN : Face Editing Generative Adversarial Network with User's Sketch and Color (ICCV 2019)

The README section "Overview" states: Edit face images using a a deep neural network. Users can edit face images using intuitive inputs such as sketching and coloring, from which our network SC-FEGAN generates high quality synthetic images. We used SN-patchGAN discriminator and Unet-like generator with gated convolutional layers.

The README section "Setup" states: Select the number of GPUs you want to use by editing demo.yaml file (multi-GPUs are not supported).

The README section "How to Use" states: Edit face images using a simple GUI. Only erased regions of the image are filled in by the network.

The repository README is the source for this review. It does not replace a local installation or an independent test.

• Source 1 · Project repository
• Source 2 · README