Using Stable Diffision models for Colorization

[Dan64]

... here's what I did:

• opened a terminal inside 'Hybrid\64bit\Vapoursynth'
  
• put the content of the repository into DiTServerRPC-main using:
  
• changed into 'DiTServerRPC-main' folder
  
• installed venv (portable Python usually isn't build with venv
  
• created the venv
  
• activated the venv:
  
• Installed the dependencies into the venv:
  
• started the server with the preload:
  
• ran the test script
  Opened another terminal where I navigated to  'Hybrid\64bit\Vapoursynth' and called
  
  python DiTServerRPC-main\dit_client_example.py --pipeline-config DiTServerRPC-main\qwen_config_fp4.json --use-shm

that ended with:

[INFO] Connecting to http://127.0.0.1:8765/ ...
[INFO] Server is reachable.
[INFO] Transport: shared memory
[INFO] Pipeline already loaded on server.
[INFO] Reading input image: F:\Hybrid\64bit\Vapoursynth\DiTServerRPC-main\assets\santa_bw.png
[INFO] Colorizing (1184x880 px) ...
[INFO] Inference time : 11.89s
[INFO] Round-trip time: 11.93s
[INFO] Saved: F:\Hybrid\64bit\Vapoursynth\DiTServerRPC-main\assets\santa_colorized.png

So far so good.

Hello Selur,

   your results are good using the pair() trick I expect that you could obtain an inference speed of about 5/6secs per image.
   The RTX4080 should have 16GB of VRAM size, how many RAM do you have on your PC (just the understand better the HW requirements) ?
   The comments that I wrote to didris in the previous post will apply also to you.
   
    Please let me know what you think.

Dan