Codename;0's improved RVC Onnx models Inference.

THE PROJECT IS CURRENTLY PAUSED - NOT ABANDONED.

Currently, the basics work; you can infer just fine however there's a length limit ( despite the internal slicing ) of around 50 seconds - at least on my machine.
I have to find a better and more efficient segmentation mechanism, til then yea.

Ready to be used with RVC V2 onnx models. ( CPU, Cuda and DML support )

Todo:

• Adding index/faiss support
• Automating stuff / making i/o handling easier.
• Adding rmvpe f0 method
• Better automation and easier input/output managment + stuff picker.
• Possibly even a gui or web-ui ~ one day huh.
• Quite possibly a tflite model exporting for future Mobile-RVC-infer-port-project ( Not 100% sure yet, concept stage. )
  

Usage guide:

1. First, prior to any inferencing, you gotta obtain the: 'vec-768-layer-12.onnx' file from:

https://huggingface.co/NaruseMioShirakana/MoeSS-SUBModel/tree/main

Place it here: RVC_Onnx_Infer/assets/vec

reference: 'RVC_Onnx_Infer/assets/vec/vec-768-layer-12.onnx'

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2. Your .onnx models land into 'onnx_models' folder

( You set which one to use in the 30th line of 'RVC_Onnx_Infer.py' script )

model_path = os.path.join("onnx_models", "Your_Model.onnx") # Your .ONNX model

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3. Your vocals for inference / acapella .wav goes into 'input' folder.

( Script will pick only the first found .wav in there, so, always have just 1 in there to avoid issues. )

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4. Your inference outputs will appear in the 'outpit' folder.

( One at a time. Any consecutive inferences will overwrite the previous file so, copy / move it somewhere else.

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5. To switch the device to Cuda or DML, change "cpu" to any of the mentioned.

The 27th line of 'RVC_Onnx_Infer.py' script;

device = "cpu" # options: dml, cuda, cpu

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6. To change hop_size, replace the '64' value with any desired.

The 22nd line of 'RVC_Onnx_Infer.py' script;

hop_size = 64 # hop size for inference. ( Currently, applies only to dio F0 )
Try: 32, 64, 128, 256, 512 or custom of your choice.

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| v0.2a | 10.12.2023 - CHANGELOG:

Changes:

• Inference max length limit off - No more '50 seconds max' per infer / file length.
  ( Now it's internally slicing, inferencing the segments 1 by 1 to avoid memory issues and merging it all into 1 final output. )
• DML x CPU is set as default for the main device.
  
• PM F0 Pitch estimation: Yea, I sorta fixed it but it's not perfect ( Doesn't support custom hop length too ) - Dio is better.

That is, until a workaround for pitch offset / hop length related(?) is found.

• Cosmetics changes - Made the console a lil bit more fancy lol + logging of segmenting process and so on. ⠀
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INITIAL RELEASE: v0.1a

Notes:

• Project is in an early alpha-dev / test / debug state.
• Currently only Dio F0 Pitch estimation until I figure out the rest.
• It is supporting RVC V2 onnx models only.
  (V1 models do not work unless you get 256-layer-9 vec onnx and modify the code appropriately.) ⠀
  
• CPU is set by default as the main device for the sake of compatibility, need more testing.