holywu / vs-realesrgan Goto Github PK

from vsrealesrgan import RealESRGAN
# adjusting color space from YUV444P8 to RGBH for VsRealESRGAN
clip = core.resize.Bicubic(clip=clip, format=vs.RGBH, matrix_in_s="470bg", range_s="limited")
# resizing using RealESRGAN
clip = RealESRGAN(clip=clip, model=5, device_index=0, trt=True, trt_cache_path=r"J:\tmp") # 704x576
# resizing 704x576 to 704x526
# adjusting resizing
clip = core.resize.Bicubic(clip=clip, format=vs.RGBS, range_s="limited")
clip = core.fmtc.resample(clip=clip, w=704, h=526, kernel="lanczos", interlaced=False, interlacedd=False)
from vsscunet import scunet as SCUNet
# denoising using SCUNet
clip = SCUNet(clip=clip, model=4, cuda_graphs=True, nvfuser=True)

I:\Hybrid\64bit\Vapoursynth>python -m pip install --upgrade vsrealesrgan
Collecting vsrealesrgan
  Using cached vsrealesrgan-2.0.0-py3-none-any.whl (12 kB)
Collecting VapourSynth>=55
  Using cached VapourSynth-57.zip (567 kB)
  Preparing metadata (setup.py) ... error
  error: subprocess-exited-with-error

  × python setup.py egg_info did not run successfully.
  │ exit code: 1
  ╰─> [15 lines of output]
      Traceback (most recent call last):
        File "C:\Users\Selur\AppData\Local\Temp\pip-install-7_na63f8\vapoursynth_4864864388024a95a1e8b4adda80b293\setup.py", line 64, in <module>
          dll_path = query(winreg.HKEY_LOCAL_MACHINE, REGISTRY_PATH, REGISTRY_KEY)
        File "C:\Users\Selur\AppData\Local\Temp\pip-install-7_na63f8\vapoursynth_4864864388024a95a1e8b4adda80b293\setup.py", line 38, in query
          reg_key = winreg.OpenKey(hkey, path, 0, winreg.KEY_READ)
      FileNotFoundError: [WinError 2] Das System kann die angegebene Datei nicht finden

      During handling of the above exception, another exception occurred:

      Traceback (most recent call last):
        File "<string>", line 2, in <module>
        File "<pip-setuptools-caller>", line 34, in <module>
        File "C:\Users\Selur\AppData\Local\Temp\pip-install-7_na63f8\vapoursynth_4864864388024a95a1e8b4adda80b293\setup.py", line 67, in <module>
          raise OSError("Couldn't detect vapoursynth installation path")
      OSError: Couldn't detect vapoursynth installation path
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.

  During handling of the above exception, another exception occurred:

  Traceback (most recent call last):
    File "<string>", line 2, in <module>
    File "<pip-setuptools-caller>", line 34, in <module>
    File "C:\Users\**\AppData\Local\Temp\pip-install-2415kpn4\vapoursynth_712c69d39f4a4718a3f6b523a85b39eb\setup.py", line 67, in <module>
      raise OSError("Couldn't detect vapoursynth installation path")
  OSError: Couldn't detect vapoursynth installation path
  [end of output]

# Imports
import vapoursynth as vs
import os
import sys
# getting Vapoursynth core
import ctypes
# Loading Support Files
Dllref = ctypes.windll.LoadLibrary("i:/Hybrid/64bit/vsfilters/Support/libfftw3f-3.dll")
core = vs.core
# Import scripts folder
scriptPath = 'i:/Hybrid/64bit/vsscripts'
sys.path.insert(0, os.path.abspath(scriptPath))
import site
# Adding torch dependencies to PATH
path = site.getsitepackages()[0]+'/torch_dependencies/bin/'
ctypes.windll.kernel32.SetDllDirectoryW(path)
path = path.replace('\\', '/')
os.environ["PATH"] = path + os.pathsep + os.environ["PATH"]
# Loading Plugins
core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/GrainFilter/AdaptiveGrain/adaptivegrain_rs.dll")
core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/GrainFilter/AddGrain/AddGrain.dll")
core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/Support/fmtconv.dll")
core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/GrainFilter/RemoveGrain/RemoveGrainVS.dll")
core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/SharpenFilter/CAS/CAS.dll")
core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/DenoiseFilter/DFTTest/DFTTest.dll")
core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/SourceFilter/DGDecNV/DGDecodeNV.dll")
# Import scripts
import havsfunc
# source: 'C:\Users\Selur\Desktop\VideoTest_9s.mkv'
# current color space: YUV420P8, bit depth: 8, resolution: 720x306, fps: 23.976, color matrix: 709, yuv luminance scale: limited, scanorder: progressive
# Loading C:\Users\Selur\Desktop\VideoTest_9s.mkv using DGSource
clip = core.dgdecodenv.DGSource("J:/tmp/2023-01-30@19_43_10_8210.dgi")# 23.976 fps, scanorder: progressive
# Setting detected color matrix (709).
clip = core.std.SetFrameProps(clip, _Matrix=1)
# Setting color transfer info, when it is not set
clip = clip if not core.text.FrameProps(clip,'_Transfer') else core.std.SetFrameProps(clip, _Transfer=1)
# Setting color primaries info, when it is not set
clip = clip if not core.text.FrameProps(clip,'_Primaries') else core.std.SetFrameProps(clip, _Primaries=1)
# Setting color range to TV (limited) range.
clip = core.std.SetFrameProp(clip=clip, prop="_ColorRange", intval=1)
# making sure frame rate is set to 23.976
clip = core.std.AssumeFPS(clip=clip, fpsnum=24000, fpsden=1001)
clip = core.std.SetFrameProp(clip=clip, prop="_FieldBased", intval=0)
clip = havsfunc.LSFmod(input=clip)
# Using FastLineDarkenMOD for line darkening
clip = havsfunc.FastLineDarkenMOD(c=clip)
from vsrealesrgan import RealESRGAN
clip = core.std.AddBorders(clip=clip, left=0, right=0, top=0, bottom=2) # add borders to archive mod 4 (VsRealESRGAN) - 720x308
# adjusting color space from YUV420P8 to RGBH for VsRealESRGAN
clip = core.resize.Bicubic(clip=clip, format=vs.RGBH, matrix_in_s="709", range_s="limited")
# resizing using RealESRGAN
clip = RealESRGAN(clip=clip, model=5, device_index=0, trt=True, trt_cache_path=r"J:\tmp") # 2880x1232
# resizing 2880x1232 to 720x306
clip = core.std.CropRel(clip=clip, left=0, right=0, top=0, bottom=8) # removing borders (VsRealESRGAN) -  2880x1224
# adjusting resizing
clip = core.resize.Bicubic(clip=clip, format=vs.RGBS, range_s="limited")
clip = core.fmtc.resample(clip=clip, w=720, h=306, kernel="lanczos", interlaced=False, interlacedd=False)
# contrast sharpening using CAS
clip = core.cas.CAS(clip=clip)
# adjusting color space from RGBS to YUV444P16 for vsAddGrain
clip = core.resize.Bicubic(clip=clip, format=vs.YUV444P16, matrix_s="709", range_s="limited", dither_type="error_diffusion")
# adding Grain using AddGrain and adaptive luma mask
clip = core.std.PlaneStats(clipa=clip)
clipmask = core.adg.Mask(clip=clip, luma_scaling=12)
clipgrained = core.grain.Add(clip=clip, var=8.00)
clip = core.std.MaskedMerge(clip, clipgrained, clipmask)
# adjusting output color from: YUV444P16 to YUV420P10 for x265Model
clip = core.resize.Bicubic(clip=clip, dither_type="error_diffusion", format=vs.YUV420P10, range_s="limited")
# set output frame rate to 23.976fps
clip = core.std.AssumeFPS(clip=clip, fpsnum=24000, fpsden=1001)
# Output
clip.set_output()`

Warning: i:\Hybrid\64bit\Vapoursynth\Lib\site-packages\torch_tensorrt\fx\tracer\acc_tracer\acc_tracer.py:584: UserWarning: acc_tracer does not support currently support models for training. Calling eval on model before tracing.
  warnings.warn(

Information: == Log pass <function fuse_permute_matmul at 0x0000029B26F88700> before/after graph to C:\Users\Selur\AppData\Local\Temp\tmpjsmylxpt, before/after are the same = True
Information: == Log pass <function fuse_permute_linear at 0x0000029B26F884C0> before/after graph to C:\Users\Selur\AppData\Local\Temp\tmp5zwqs8fw, before/after are the same = True
Information: Now lowering submodule _run_on_acc_0
Information: split_name=_run_on_acc_0, input_specs=[InputTensorSpec(shape=torch.Size([1, 3, 308, 720]), dtype=torch.float16, device=device(type='cuda', index=0), shape_ranges=[], has_batch_dim=True)]
Information: Timing cache is used!
x265 [error]: unable to open input file <->
Information: TRT INetwork construction elapsed time: 0:00:00.387301
Information: Build TRT engine elapsed time: 0:01:01.767990
Information: Lowering submodule _run_on_acc_0 elapsed time 0:01:05.018931
Information: Now lowering submodule _run_on_acc_2
Information: split_name=_run_on_acc_2, input_specs=[InputTensorSpec(shape=torch.Size([1, 3, 1232, 2880]), dtype=torch.float16, device=device(type='cuda', index=0), shape_ranges=[], has_batch_dim=True), InputTensorSpec(shape=torch.Size([1, 3, 1232, 2880]), dtype=torch.float16, device=device(type='cuda', index=0), shape_ranges=[], has_batch_dim=True)]
Information: Timing cache is used!
Information: TRT INetwork construction elapsed time: 0:00:00
Information: Build TRT engine elapsed time: 0:00:00.224972
Information: Lowering submodule _run_on_acc_2 elapsed time 0:00:00.229702
Error: fwrite() call failed when writing frame: 0, plane: 0, errno: 22
Output 33 frames in 0.80 seconds (41.09 fps)

from vapoursynth import core
from vsrealesrgan import RealESRGAN
import havsfunc as haf
import vapoursynth as vs
video = core.ffms2.Source(source='EDIT.mkv')
video = haf.QTGMC(video, Preset="slow", MatchPreset="slow", MatchPreset2="slow", SourceMatch=3, TFF=True)
video = core.std.SelectEvery(clip=video, cycle=2, offsets=0)
video = core.std.Crop(clip=video, left=8, right=8, top=0, bottom=0)
video = core.resize.Spline36(clip=video, width=640, height=480)
video = core.resize.Bicubic(clip=video, format=vs.RGBS, matrix_in_s="470bg", range_s="limited")
video = RealESRGAN(clip=video, device_index=0)
video = core.resize.Bicubic(clip=video, format=vs.YUV420P10, matrix_s="470bg", range_s="limited")
video = core.resize.Spline36(clip=video, width=1440, height=1080)
video = core.std.AssumeFPS(clip=video, fpsnum=30000, fpsden=1001)
video.set_output()

clip = core.resize.Bicubic(clip, width=720, height=574, format=vs.RGBS, matrix_in_s='709')
clip = core.trt.Model(clip, engine_path="realesr-general-wdn-x4v3_opset16_574x720_fp16.engine", num_streams=4, device_id=0)

trtexec --fp16 --onnx=./realesr-general-wdn-x4v3_opset16.onnx --minShapes=input:1x3x8x8 --optShapes=input:1x3x574x720 --maxShapes=input:1x3x574x720 --saveEngine=./realesr-general-wdn-x4v3_opset16_574x720_fp16.engine --tacticSources=+CUDNN,-CUBLAS,-CUBLAS_LT --skipInference --useCudaGraph --noDataTransfers --builderOptimizationLevel=5 --infStreams=4

vspipe -e 300 test3.vpy -p .
Script evaluation done in 2.26 seconds
Output 301 frames in 8.15 seconds (36.92 fps)

clip = core.resize.Bicubic(clip, width=720, height=574, format=vs.RGBH, matrix_in_s='709')
clip = realesrgan(clip, num_streams = 4, trt = True, model = 5, denoise_strength = 0)

vspipe -e 300 test3.vpy -p .
Script evaluation done in 2.26 seconds
Output 601 frames in 23.73 seconds (25.33 fps)

# Imports
import vapoursynth as vs
# getting Vapoursynth core
core = vs.core
import site
import os
# Adding torch dependencies to PATH
path = site.getsitepackages()[0]+'/torch_dependencies/'
path = path.replace('\\', '/')
os.environ["PATH"] = path + os.pathsep + os.environ["PATH"]
# Loading Plugins
core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/Support/fmtconv.dll")
core.std.LoadPlugin(path="i:/Hybrid/64bit/vsfilters/SourceFilter/LSmashSource/vslsmashsource.dll")
# source: 'G:\TestClips&Co\files\test.avi'
# current color space: YUV420P8, bit depth: 8, resolution: 640x352, fps: 25, color matrix: 470bg, yuv luminance scale: limited, scanorder: progressive
# Loading G:\TestClips&Co\files\test.avi using LWLibavSource
clip = core.lsmas.LWLibavSource(source="G:/TestClips&Co/files/test.avi", format="YUV420P8", stream_index=0, cache=0, prefer_hw=0)
# Setting color matrix to 470bg.
clip = core.std.SetFrameProps(clip, _Matrix=5)
clip = clip if not core.text.FrameProps(clip,'_Transfer') else core.std.SetFrameProps(clip, _Transfer=5)
clip = clip if not core.text.FrameProps(clip,'_Primaries') else core.std.SetFrameProps(clip, _Primaries=5)
# Setting color range to TV (limited) range.
clip = core.std.SetFrameProp(clip=clip, prop="_ColorRange", intval=1)
# making sure frame rate is set to 25
clip = core.std.AssumeFPS(clip=clip, fpsnum=25, fpsden=1)
clip = core.std.SetFrameProp(clip=clip, prop="_FieldBased", intval=0)
original = clip
from vsrealesrgan import RealESRGAN
# adjusting color space from YUV420P8 to RGBH for VsRealESRGAN
clip = core.resize.Bicubic(clip=clip, format=vs.RGBH, matrix_in_s="470bg", range_s="limited")
# resizing using RealESRGAN
clip = RealESRGAN(clip=clip, device_index=0, trt=True, trt_cache_path="G:/Temp", num_streams=4) # 2560x1408
# resizing 2560x1408 to 640x352
# adjusting resizing
clip = core.resize.Bicubic(clip=clip, format=vs.RGBS, range_s="limited")
clip = core.fmtc.resample(clip=clip, w=640, h=352, kernel="lanczos", interlaced=False, interlacedd=False)
original = core.resize.Bicubic(clip=original, width=640, height=352)
# adjusting output color from: RGBS to YUV420P8 for x264Model
clip = core.resize.Bicubic(clip=clip, format=vs.YUV420P8, matrix_s="470bg", range_s="limited", dither_type="error_diffusion")
original = core.text.Text(clip=original,text="Original",scale=1,alignment=7)
clip = core.text.Text(clip=clip,text="Filtered",scale=1,alignment=7)
stacked = core.std.StackHorizontal([original,clip])
# Output
stacked.set_output()

Traceback (most recent call last):
File "src\cython\vapoursynth.pyx", line 2866, in vapoursynth._vpy_evaluate
File "src\cython\vapoursynth.pyx", line 2867, in vapoursynth._vpy_evaluate
File "C:\Users\Selur\Desktop\test_2.vpy", line 32, in 
clip = RealESRGAN(clip=clip, device_index=0, trt=True, trt_cache_path="G:/Temp", num_streams=4) # 2560x1408
File "I:\Hybrid\64bit\Vapoursynth\Lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "I:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vsrealesrgan\__init__.py", line 284, in RealESRGAN
module = [torch.load(trt_engine_path) for _ in range(num_streams)]
File "I:\Hybrid\64bit\Vapoursynth\Lib\site-packages\vsrealesrgan\__init__.py", line 284, in 
module = [torch.load(trt_engine_path) for _ in range(num_streams)]
File "I:\Hybrid\64bit\Vapoursynth\Lib\site-packages\torch\serialization.py", line 795, in load
return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)
File "I:\Hybrid\64bit\Vapoursynth\Lib\site-packages\torch\serialization.py", line 1002, in _legacy_load
magic_number = pickle_module.load(f, **pickle_load_args)
EOFError: Ran out of input