Since my temporary departure from developments 2-3 months ago, a variety of bugs have sprung up, likely as a result of ever-changing dependencies. This thread will track the status of bringing AnKit back to its previous functioning state.

Some programs output as 1.jpg, 2.jpg, 3.jpg etc. whereas others output as 001.jpg, 002.jpg. etc.

Right now, the non-botched build does the former.

I need to make it auto-recognize the flow of a directory and have it sort accordingly.

a16434f41a8998b6efd9f64b813269ffd8aa5a81 hides the following options:

"'RealESRGANv2-anime-xsx2','RealESRGANv2-animevideo-xsx2-nousm','RealESRGANv2-animevideo-xsx2','RealESRGANv2-anime-xsx4','RealESRGANv2-animevideo-xsx4-nousm','RealESRGANv2-animevideo-xsx4"

Originally posted by @sadnow in https://github.com/sadnow/AnimationKit-AI/issues/5#issuecomment-1000061506

These newer Real-ESRGAN's functions will be tested and integrated. Prior functions will be preserved and left as a toggle for users.

• [x] differentiate AnKit chained process into 2 methods, recognized by vars method_a and method_b
• [x] #14
• [ ] Outscale option for Method B (possibly mixed w/ with rife_scale) - intended for lower-power gpu's
• [x] #11
• [x] RIFE sound support in method B
• [ ] Compare current splitframes, frames2video methods to the examples listed in https://github.com/xinntao/Real-ESRGAN/blob/master/docs/anime_video_model.md#step-1-use-ffmpeg-to-extract-frames-from-video
• [ ] #17
• [ ] c:v hevc_nvenc support for new_method inference_py file
• [ ] fps detection occurs before RIFE
• [ ] source_fps option for individual_frames (with a default being "default" (24fps)

For documentation, I guess I could refer to this as Method-A & Method-B AnKit Chaining. Sounds fancy.

Reference links: https://github.com/xinntao/Real-ESRGAN/blob/master/docs/anime_video_model.md https://stackoverflow.com/questions/678236/how-to-get-the-filename-without-the-extension-from-a-path-in-python?rq=1

--- Code overhaul

• [ ] #20

Hurdle: "error: unrecognized arguments: --netscale 4"

Originally posted by @sadnow in https://github.com/sadnow/AnimationKit-AI/issues/2#issuecomment-1000048704

"inference_realesrgan.py: error: unrecognized arguments: --model_path /content/Real-ESRGAN/experiments/pretrained_models/RealESRGAN_x4plus.pth --netscale 4 /content/Real-ESRGAN/results"

Re-evaluating available params

Originally posted by @sadnow in https://github.com/sadnow/AnimationKit-AI/issues/2#issuecomment-1000042722

hmm, getting the following error since this afternoon:

Creating /content/frames_storage/upscaled_frame_storage ...
/content/Real-ESRGAN
Traceback (most recent call last):
  File "inference_realesrgan.py", line 128, in <module>
    main()
  File "inference_realesrgan.py", line 84, in main
    from gfpgan import GFPGANer
  File "/usr/local/lib/python3.7/dist-packages/gfpgan/__init__.py", line 2, in <module>
    from .archs import *
  File "/usr/local/lib/python3.7/dist-packages/gfpgan/archs/__init__.py", line 10, in <module>
    _arch_modules = [importlib.import_module(f'gfpgan.archs.{file_name}') for file_name in arch_filenames]
  File "/usr/local/lib/python3.7/dist-packages/gfpgan/archs/__init__.py", line 10, in <listcomp>
    _arch_modules = [importlib.import_module(f'gfpgan.archs.{file_name}') for file_name in arch_filenames]
  File "/usr/lib/python3.7/importlib/__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "/usr/local/lib/python3.7/dist-packages/gfpgan/archs/gfpganv1_cleanonnx_arch.py", line 8, in <module>
    from .stylegan2_cleanonnx_arch import StyleGAN2GeneratorCleanONNX
ModuleNotFoundError: No module named 'gfpgan.archs.stylegan2_cleanonnx_arch'

Investigating.

I LOVE THIS NOTEBOOK! Major props. One question, the first few videos came out H265 and perfect, but after a few times running the notebook with different videos/input frame folders, the video fails to compress properly? Example, the video will save to my drive and will be available for download, but once I download and attempt to play the video, it won't open on any media player, yet will play while still loaded in my drive? I'm thinking that it could be a compression issue, but any help will be appreciated as I LOVE this notebook, if I haven't said it again. Thanks in advance, and amazing work!

I'm using the animation kit-AI on google colab and cuda is running out of memory, I want to specify the tile size, please tell me where to insert the code! -I want to specify the tile size, but I need to know where to insert the code! What code do I put it in? ↓URL https://colab.research.google.com/github/sadnow/AnimationKit-AI_Upscaling-Interpolation_RIFE-RealESRGAN/blob/main/AnimationKit_Rife_RealESRGAN_Upscaling_Interpolation.ipynb#scrollTo=MhMORNgduDyt

Error message " Error CUDA out of memory.Tried to allocate 7.91 GiB (GPU 0; 14.76 GiB total capacity; 2.51 GiB already allocated; 2.81 GiB free; 10.90 GiB reserved in total by PyTorch) If reserved memory is more than allocated memory, try setting max_split_size_mb to prevent fragmentation. See the documentation on memory management and PYTORCH_CUDA_ALLOC_CONF. If CUDA runs out of memory, try setting -tile to a smaller number. Test 428 A00429 "

The google drive version of the RIFE model can no longer be downloaded programatically, so the notebook fails to run. This PR mirrors the RIFE model here and uses the mirrored version instead.

This is an evolution of the previous classes and functions AnKit utilized pre-2.5.

Rough draft:

class SadKit:
  def __init__(self):
    ## instantiating the 'Inner' class
    #self.debug = self.Debug()
    self.path = self.Path()
    self.image_tools = self.Image_tools()
    #Ank = self.AnimationKit_colab
    # self.dprint = self.dprint
    #dprint = self.debug_print
    import os.path
    from os import path
  def debug_print(self, msg): #debug print
    print(msg)  #make this colored eventually
    #code to clear screen
  class Image_tools:
    def frames2video(self, input):
      #!ffmpeg -framerate $_target_fps -pattern_type glob -i '*.png' -y '/content/frames2video.mp4' #old method
      print("RUNNING THE EXPERIMENTAL")
      !ffmpeg -r 24 -pattern_type glob -i '*.png' -c:v libx264 -r 23.98 -pix_fmt yuv420p '/content/frames_storage/init_frame_storage/frames2video.mp4'  #documented example realsrgan-video.md
        #note: detect_fps might be wonky

  class Path:
    #intent(s): detect, create, insert, type_id, remove_extension, append_prefix, append_suffix
    #  
    def detect_dir(self, input):  #/content/example.mp4 would become /content/
      dir = os.path.dirname(input)
      return dir
    def make(self, input):
      !mkdir -p $input
    def type_id(self, input): #determine whether file or directory
      #types: file,dir
      import os.path
      from os import path
      input = self.sanitize(input)
      if os.path.isdir(input):  type = 'dir'
      elif os.path.isfile(input): type = 'file'
      else: type = 'error'
      #print(type)
      return type
      #else: print("ERROR: Your input file is neither an mp4 nor a frame directory.")
    def sanitize(self, input):
      import os.path
      input = os.path.normpath(input)
      return input
    def filter_by_extension(self, input_dir, output_dir, file_ext): #sorts a dir's files by extension and copies matching files to new dir
      #print("\n Beginning sortFrames... ")
      if not self.query(output_dir):
        self.make(output_dir)
      #print("\n Copying frames to "+'/content/frames_storage/init_frame_storage'+" for processing...\n")
      %cd $input
      #!find -maxdepth 1 -name '*.png' -print0 | xargs -0 cp -t '/content/frames_storage/init_frame_storage'
      !find -maxdepth 1 -name '*.'$file_ext -print0 | xargs -0 cp -t $output
      %cd $output
      !find . -type f -name "*."$file_ext -execdir bash -c 'mv "$0" "${0##*_}"' {} \;  #removes anything not numbered (junk files) from new dir
      self.dir_file_suffix_padding(output_dir)
      print("\n Finished copying frames to "+'/content/frames_storage/init_frame_storage'+".\n")
      print("Completed sortFrames... \n")
    def dir_file_suffix_padding(input_dir): #pads all filenames within a dir
      %cd $input_dir
      !rename 's/\d+/sprintf("%05d",$&)/e' *  #adds padding to numbers
      return
    def query(self, input):
      if self.type_id(input) == 'file' or self.type_id(input) == 'dir': 
        #print(self.type_id(input))
        return True
      else: return False
    def upload(self, input):
      import os
      from google.colab import files
      import shutil
      # upload images
      upload_folder = 'upload'
      result_folder = 'results'
      if os.path.isdir(upload_folder):
        shutil.rmtree(upload_folder)
      if os.path.isdir(result_folder):
        shutil.rmtree(result_folder)
      os.mkdir(upload_folder)
      os.mkdir(result_folder)
      #
      uploaded = files.upload()
      for filename in uploaded.keys():
        dst_path = os.path.join(upload_folder, filename)
        print(f'move {filename} to {dst_path}')
        shutil.move(filename, dst_path)
######################