simplify engine building

REAL-Video-Enhancer.py

@@ -1,5 +1,6 @@
 import sys
 import os
+
 # patch for macos
 if sys.platform == "darwin":
     os.chdir(os.path.dirname(os.path.abspath(__file__)))
@@ -15,7 +16,7 @@
 )
 from PySide6.QtGui import QIcon
 from src.Util import printAndLog
-from mainwindow import Ui_MainWindow  
+from mainwindow import Ui_MainWindow
 from PySide6 import QtSvg  # Import the QtSvg module so svg icons can be used on windows
 from src.version import version
 from src.InputHandler import VideoInputHandler
@@ -464,11 +465,11 @@ def closeEvent(self, event):
     app = QApplication(sys.argv)
 
     # setting the pallette
-    
+
     app.setPalette(Palette())
     window = MainWindow()
     if len(sys.argv) > 1:
-        if sys.argv[1] == '--fullscreen':
+        if sys.argv[1] == "--fullscreen":
             window.showFullScreen()
     window.show()
     sys.exit(app.exec())

backend/rve-backend.py

@@ -247,8 +247,6 @@ def checkArguments(self):
             raise ValueError(
                 "Interpolation factor must be 1 if no interpolation model is used.\nPlease use --interpolateFactor 1 for no interpolation!"
             )
-
-
 
 
 if __name__ == "__main__":

backend/src/FFmpeg.py

@@ -377,22 +377,6 @@ def writeOutInformation(self, fcs):
 
             time.sleep(0.1)
 
-    def openMPVProc(self):
-        self.mpv_process = subprocess.Popen(
-            [
-                "mpv",
-                "--no-correct-pts",
-                f"--fps={self.fps * self.ceilInterpolateFactor}",
-                "--demuxer-thread=no",
-                "--",
-                "-",
-            ],
-            stdin=subprocess.PIPE,
-            stdout=subprocess.PIPE,
-            stderr=subprocess.PIPE,
-            text=False,
-        )
-
     def writeOutVideoFrames(self):
         """
         Writes out frames either to ffmpeg or to pipe
@@ -401,9 +385,6 @@ def writeOutVideoFrames(self):
         ffmpeg -f rawvideo -pix_fmt rgb24 -s 1920x1080 -framerate 24 -i - -c:v libx264 -crf 18 -pix_fmt yuv420p -c:a copy out.mp4
         """
         log("Rendering")
-        #
-
-        # self.openMPVProc()
         self.startTime = time.time()
         self.framesRendered: int = 1
         self.last_length: int = 0

backend/src/InterpolateArchs/DetectInterpolateArch.py

@@ -1,5 +1,6 @@
 import torch
 
+
 class RIFE46:
     def __init__():
         pass

backend/src/InterpolateArchs/GMFSS/FeatureNet.py

@@ -1,6 +1,7 @@
 import torch.nn as nn
 from .util import MyPReLU
 
+
 class FeatureNet(nn.Module):
     """The quadratic model"""
 

backend/src/InterpolateArchs/GMFSS/GMFSS.py

@@ -12,9 +12,18 @@
 
 
 class GMFSS(nn.Module):
-    def __init__(self, model_path, model_type:str="union", scale:int=1, ensemble:bool=False, width:int=1920, height:int=1080):
+    def __init__(
+        self,
+        model_path,
+        model_type: str = "union",
+        scale: int = 1,
+        ensemble: bool = False,
+        width: int = 1920,
+        height: int = 1080,
+    ):
         super(GMFSS, self).__init__()
         from .FusionNet_u import GridNet
+
         # get gmfss from here, as its a combination of all the models https://github.com/TNTwise/real-video-enhancer-models/releases/download/models/GMFSS.pkl
         self.width = width
         self.height = height
@@ -25,12 +34,12 @@ def __init__(self, model_path, model_type:str="union", scale:int=1, ensemble:boo
         self.fusionnet = GridNet()
         combined_state_dict = torch.load(model_path, map_location="cpu")
         if model_type != "base":
-            self.ifnet.load_state_dict(combined_state_dict['rife'])
-        self.flownet.load_state_dict(combined_state_dict['flownet'])
-        self.metricnet.load_state_dict(combined_state_dict['metricnet'])
-        self.feat_ext.load_state_dict(combined_state_dict['feat_ext'])
-        self.fusionnet.load_state_dict(combined_state_dict['fusionnet'])
-        
+            self.ifnet.load_state_dict(combined_state_dict["rife"])
+        self.flownet.load_state_dict(combined_state_dict["flownet"])
+        self.metricnet.load_state_dict(combined_state_dict["metricnet"])
+        self.feat_ext.load_state_dict(combined_state_dict["feat_ext"])
+        self.fusionnet.load_state_dict(combined_state_dict["fusionnet"])
+
         self.model_type = model_type
         self.scale = scale
 

backend/src/InterpolateArchs/GMFSS/softsplat.py

@@ -642,4 +642,4 @@ def backward(self, tenOutgrad):
     # end
 
 
-# end
+# end

backend/src/InterpolateArchs/RIFE/warplayer.py

@@ -31,6 +31,8 @@ def warp(tenInput, tenFlow, tenFlow_div, backwarp_tenGrid):
     tenInput = tenInput.to(torch.float)
     tenFlow = tenFlow.to(torch.float)
 
-    tenFlow = torch.cat([tenFlow[:, 0:1] / tenFlow_div[0], tenFlow[:, 1:2] / tenFlow_div[1]], 1)
+    tenFlow = torch.cat(
+        [tenFlow[:, 0:1] / tenFlow_div[0], tenFlow[:, 1:2] / tenFlow_div[1]], 1
+    )
     g = (backwarp_tenGrid + tenFlow).permute(0, 2, 3, 1)
-    return torch.ops.aten.grid_sampler_2d(tenInput, g, 0, 1, True).to(dtype)
+    return torch.ops.aten.grid_sampler_2d(tenInput, g, 0, 1, True).to(dtype)

backend/src/InterpolateNCNN.py

@@ -237,7 +237,7 @@ def process_fast(
             self.height, self.width, self.channels
         )
 
-  
+
 class RIFE(Rife): ...