BasicVSR++ is more suited to deal with compression and resizing artifacts, one of its strengthens is to repair chroma.
Spotless, DeDot and similar are more suited to remove such dirt
Don't like what DeepEnhancer does with the contrast.
For old clips, I usually prefer non-machine learning based solutions.
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Dev versions are in the 'experimental'-folder of my GoogleDrive, which is linked on the download page.
Selur, that was incredible work. Thank you for the script, led me to discover why KillerSpots wasn't working for me previously, I renamed RemoveDirt.dll to RemoveDirtVS.dll to fix it
Thanks for your feedback—totally understandable regarding DeepEnhancer’s contrast handling. It does tend to be a bit aggressive and might not be the best default choice for all clips, especially if a more subtle restoration is desired.
Still, I’ve found it surprisingly effective on very old footage, particularly from the 1920s–40s, where it manages to remove large blotches and stains that even Spotless and DeDot sometimes struggle with. I agree that BasicVSR++ is great for chroma repair and compression artifacts, but DeepEnhancer seems to go further in cleaning up physical damage, even if a bit heavy-handed.
In the end, it's great to have multiple tools available depending on the situation. The flexibility Hybrid and HAVC offer makes it possible to test and choose the best one for each clip—which is a huge strength!
Thanks again for your thoughts and for keeping everything so customizable.
If you open the script attached in the previous post and run the preview are shown the following message.
Quote:Unable to import quantization op. Please install modelopt library (https://github.com/NVIDIA/TensorRT-Model...stallation) to add support for compiling quantized models TensorRT-LLM is not installed. Please install TensorRT-LLM or set TRTLLM_PLUGINS_PATH to the directory containing libnvinfer_plugin_tensorrt_llm.so to use converters for torch.distributed ops D:\Programs\Hybrid\64bit\Vapoursynth\Lib\site-packages\timm\models\layers\__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers
warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning)
these message are not filteret-out by vspipe.
The problem is on vspipe. The pipe in output should provide only the video stream.
It is a design bug and need to be fixed on vspipe side.