trained the model based on dark art sketches. got such bizarre forms of life

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  • dataset-tools

    Tools for quickly normalizing image datasets

  • I am very glad that my work aroused interest. Thank you all! I will try to answer the questions. How did i create this? I collected a dataset of about 600 images of dark art sketches, processed them so that they would be suitable for training in the StyleGAN2-ada (resized to 1024x1024, edited something a little, made sure that all images have 3 channels). Mainly used photoshop, also Duplicate Photos Fixer Pro to find duplicates, and also I highly recommend Derek's dataset-tools for preparing datasets. Then the dataset was archived, uploaded to GoogleDrive and added to Google Colab for training. I had to subscribe to the Colab Pro because the free version could not start training due to lack of memory. A pro subscription costs $10 per month and provides advantages in capacity and uptime. More about working with Google Colab can be found here. I'm a beginner myself, so no secret techniques have been applied. In fact, everything is as in the video tutorial. Training took place about 30 hours, partly at Tesla P100 and partly on a more powerful Tesla V100. I have not written anywhere an article about this project because I do not speak English very well. And there is not much to write about, everything is simple. In the future I will probably post the .pkl file to the public.

  • pix2pix

    Image-to-image translation with conditional adversarial nets

  • It seems like this even would make for a cool website, like pix2pix

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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