I have an up-scaling program that breaks down videos to images then up-scales using waifu2x-caffe, issue is i cant seem to figure out what the optimal settings for speed without losing quality would be. Already on GitHub? I do have to note that since I have no idea how to do any of this my estimations are based on generic models.

Offhand do you know of any big differences quality wise ? For more information, see our Privacy Statement. Physical memory use seems to adhere to the memory limit, though, even if there's about 6gb of extra "available" physical memory and 3gb free VRAM. Have a question about this project? Especially since CUDA consumes more memory than cuDNN, be careful, Japanese Lang ID: 0x11 (LANG_JAPANESE), SubLangID: 0x01 (SUBLANG_JAPANESE_JAPAN), English (US) LangID: 0x09 (LANG_ENGLISH), SubLangID: 0x01 (SUBLANG_ENGLISH_US), English (UK) LangID: 0x09 (LANG_ENGLISH), SubLangID: 0x02 (SUBLANG_ENGLISH_UK), Fixed that the enlargement of vertical width or horizontal width specification may cause deviation of about 1px from specified size due to calculation error, Correct that output of CUI may be garbled in non-Japanese environment, Fixed a bug that sometimes caused errors when selecting output folder, Fixed a bug recognized as horizontal width specification even if vertical width size is specified in GUI, The output depth bit number can not be changed by input, Added size specification by width and width after conversion in GUI, CUI allows you to simultaneously specify width and width after conversion, Updated CUDA Toolkit to 8.0.44 (dll included is also updated), If the alpha channel is monochromatic, speed up by expanding with cv :: INTER_NEAREST, Fixed a bug that output was wrong when using TTA mode when crop_w and crop_h are different values, Change the model used by the standard to upconv_7_anime_style_art_rgb, The upconv model is displayed on the GUI version, Fixed a bug that the output file name does not change even when changing the noise removal level to 0 in the GUI version, Fixed a bug that denoising level 0 could not be specified with command line option, Fixed a bug that output file name suffix does not change when noise removal level 0 radio button is pressed in GUI version, Fixed bug that Chinese (simplified) translation was not displayed correctly, Change the default value of noise removal level from 1 to 0, Fixed a bug where vertical width specification enlargement behavior was the same as horizontal width specification, Fixed that the use amount of VRAM exceeding the maximum value was forcibly terminated in algorithm search using cuDNN, Fixed a bug that forcibly terminates when selecting a large number of files in GUI input input reference dialog, Fixed a bug that command line option crop size specification was not working in GUI version, Correct that strange images appear when converting 32 bit Bitmap, Faster processing speed when using cuDNN (we made cu DNN usage algorithm fastest and cached the result), Added crop_w, crop_h option in CUI version, Update contents of "About cuDNN" of README according to the current situation, Messages are issued on forced termination in the GUI version (Although only message that split size may be the cause is issued, but in fact it may be another cause to note), Fixed a bug that forcibly terminates if batch_size is 2 or more, Fixed a bug that forcibly terminates if the used processor is CPU, Fixed cuBLAS and cuRAND initialization failure message issued in an environment where CUDA is not available, correspond to upconv model (illustration), Enabled to specify the GPU device used for conversion, The rule of automatic generation of output file name of CUI version is aligned with GUI version, Memory shortage countermeasure became ineffective due to the relationship which rewrote considerably contents (In environments where 16 GB of memory is loaded, it may become to forcibly terminate if the image of 1500 x 1500 magnified is enlarged more than 8 times. ...but I'm still getting this error :( Please throw some money my way either directly VIA PayPal or with my Ko-Fi maybe don’t do my Patreon until I fully set it up. privacy statement. Press question mark to learn the rest of the keyboard shortcuts. I have an up-scaling program that breaks down videos to images then up-scales using waifu2x-caffe, issue is i cant seem to figure out what the optimal settings for speed without losing quality would be. GUI supports English, Japanese, Simplified Chinese, Traditional Chinese, Korean, Turkish, Spanish, Russian, and French. We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products.

I have an GeForce GTX 1060 with 4 gigs of vram, an Intel Intel Core i5-7300HQ, and 8 gigs of ram. You'll need: A 64-bit Windows 10, 8.1, 8, or 7.

You can check the performance of model with models/my_model/noise1_scale2.0x_best.png. すいません、要求環境には書かれていませんでしたがCUDAで計算するにはCompute Capability 2.0以上のGPUが必要です。 Okay, so I uninstalled the previous stuff and downloaded cuDNN. The whole entire DirectML and DXR framework are a thing that isn’t really locked to hardware.

I try to replicate an exception posted to the staxrip issue tracker, the user is getting E_ACCESSDENIED after staxrip calls TaskDialog to show an error returned from VapourSynth, I get following error: Python exception: Waifu2x-caffe: failed open model file at initialization. According to the source of Waifu2x’s documentation it is possible to train your own models for use in this.

Thanks Are_ for testing.

to your account, Shit, i just realized I downloaded the wrong file. they're used to gather information about the pages you visit and how many clicks you need to accomplish a task. Last Updated: Millions of developers and companies build, ship, and maintain their software on GitHub — the largest and most advanced development platform in the world. Idk where I'd be without you.

In my case, waifu2x is trained with 6000 high-resolution-noise-free-PNG images. There is also the issue where the program I’m using saves to a file and doesn’t just process everything internally to the graphics pipeline nor does it do any edge detection which could speed things up considerably. Although it … Note2: The command that was used to train for waifu2x’s pretraind models is available at appendix/train_upconv_7_art.sh, appendix/train_upconv_7_photo.sh.

GIMP is the GNU Image Manipulation Program. Note1: If you have cuDNN library, you can use cudnn kernel with -backend cudnn option. or would there be any reason NOT to switch to using the caffe version if you had a compatible GPU ? You signed in with another tab or window. https://developer.nvidia.com/cudnn. Anime (UpPhoto model), anime_style_art_rgb: 2D illustration (RGB model), anime_style_art_y: 2-dimensional illustration (Y model), The higher the number is, the more it will not become faster. Change the default model to upconv_7_anime_style_art_rgb. The major difference is that caffe version has upconv_7 models and cuDNN support while w2xc version doesn't. I have an GeForce GTX 1060 with 4 gigs of vram, an Intel Intel Core i5-7300HQ, and 8 gigs of ram. Waifu2x Caffe rewrites only the conversion function of the image conversion software "waifu2x" using Caffe and is software developed for Windows. Estimated reading time: ~4 minutes. The cpu takes about 2-4 minutes to convert a single image, was hoping to speed that up somehow :(. Waifu2x Caffe rewrites only the conversion function of the image conversion software "waifu2x" using Caffe and is software developed for Windows.

Sign in Train Your Own Model. Waifu2x-Caffe is a deep learning system for upscaling images. And it supports photos. According to 4gamer Radeon is working with the DirectML framework to bring exciting new technologies to their GPUs.

I guess lansing was asking whether he should divide the image of the original size or the upscaled size. You should use noise free images. Found a bad link? Upscales from what to what? I’m just a geek with ADHD and motivational issues , Train a 2x and noise reduction fusion model, https://blogs.msdn.microsoft.com/directx/2018/03/19/gaming-with-windows-ml/, https://blogs.msdn.microsoft.com/directx/2018/03/19/announcing-microsoft-directx-raytracing/, Creative Commons Attribution-ShareAlike 4.0 International License. May 14, 2019 they're used to log you in. Conversely speaking, there is no effect unless it is expanded to a considerable size), Fixed a bug that input path might not be recognized when launching by passing command line option in GUI, Update Caffe (corresponds to cuDNN v5 RC), Corresponds to command line options with GUI, Separate option settings in separate windows with GUI, Added behavior setting when file is specified as argument in GUI, Add output file overwrite prohibition setting by GUI, Added initial directory setting when pressing reference button in GUI, Improved so that you can select files and folders at the same time in the window when input reference button is pressed in GUI, Fixed a bug that forced termination occurred with 16 bit output, Added check on whether GUI is Compute Capability 2.0 or higher device, If the size of the enlarged image exceeds 3 GB, data is written to a temporary file so as to take measures against memory shortage, Update model of anime_style_art (Y direction), Added ability to change the size of the dialog displayed by GUI reference button, Fixed a bug that CUI did not start (change the shortcut option for help display to "-? Out of curiosity, why does Waifu2x caffe support non-integer scaling when this version doesn't? GUI supports English, Japanese, Simplified Chinese, Traditional Chinese, Korean, Turkish, Spanish, Russian, and French. Waifu2x-Caffe is a deep learning system for upscaling images. I dropped 'cudnn64_4.dll' into the waifu2x directory... :) So people who want to use cuDNN download binary for Windows (v 5.1 RC or later) on this page Please put "cudnn64_7.dll" in the folder of waifu2x-caffe. The program will run on most modern PCs, although it will perform better if you have a speedy processor and/or video card (also called a GPU).

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