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my_DAIN_class.py
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my_DAIN_class.py
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import time
import os
from torch.autograd import Variable
import math
import torch
import random
import numpy as np
import numpy
import networks
import cv2
import shutil
import PIL
import PIL.Image
from tqdm import tqdm
import time
import psnr
#from torch.cuda.amp import autocast
import setting
from DainDataset import DainDataset
#from torch.multiprocessing import Pool, set_start_method, Queue, Process, cpu_count
from shutil import copyfile
from RenderData import FrameCollection, FrameData
import RenderData
from tqdm import tqdm
DEBUG_TEST_NO_CUDA = False
SHOW_TIMING = False
USE_CUDA = True
TIMER = None
depad_value = []
import json
from json import JSONEncoder
def NumpyResultAsList(data, pad):
outputList = []
size = data[0].shape[0]
for x in range(0, size):
for i in range(0, len(data)):
if pad == None:
yy_ = torch.round(255.0 * torch.clamp(data[i][x].float(), 0.0, 1.0)[:, :, :].permute(1, 2, 0)).detach().cpu().numpy().astype(numpy.uint8)
else:
yy_ = torch.round(255.0 * torch.clamp(data[i][x].float(), 0.0, 1.0)[:, pad[2]:pad[3], pad[0]:pad[1]].permute(1, 2, 0)).detach().cpu().numpy().astype(numpy.uint8)
outputList.append(yy_)
return outputList
def lerp(a, b, f):
return int(a + f * (b - a))
def SetTiming(tag):
global TIMER, SHOW_TIMING
if TIMER == None:
TIMER = time.time()
if SHOW_TIMING:
print("\nStarting Timer: " + tag)
if SHOW_TIMING:
print("\n"+tag + ": --- %s seconds ---" % (time.time() - TIMER))
TIMER = time.time()
def CalculatePad(intWidth, intHeight):
if intWidth != ((intWidth >> 7) << 7):
intWidth_pad = (((intWidth >> 7) + 1) << 7)
intPaddingLeft =int(( intWidth_pad - intWidth)/2)
intPaddingRight = intWidth_pad - intWidth - intPaddingLeft
else:
intWidth_pad = intWidth
intPaddingLeft = 32
intPaddingRight= 32
if intHeight != ((intHeight >> 7) << 7):
intHeight_pad = (((intHeight >> 7) + 1) << 7)
intPaddingTop = int((intHeight_pad - intHeight) / 2)
intPaddingBottom = intHeight_pad - intHeight - intPaddingTop
else:
intHeight_pad = intHeight
intPaddingTop = 32
intPaddingBottom = 32
return (intPaddingLeft, intPaddingRight , intPaddingTop, intPaddingBottom,0,0)
def Configure(owner, myRenderData):
global DEBUG_TEST_NO_CUDA
useAnimationMethod = myRenderData.useAnimationMethod
(iWidth, iHeight) = owner.GetInputSize()
padding_value = CalculatePad(iWidth, iHeight)
setting.SetPad(padding_value)
global depad_value
depad_value = setting.GetPad()
depad_value = (padding_value[0], padding_value[0] +iWidth, padding_value[2], padding_value[2] +iHeight)
print("Using Model: " + myRenderData.model)
if DEBUG_TEST_NO_CUDA:
return
torch.cuda.empty_cache()
if myRenderData.interpolationAlgorithm == 0:
gl_model = networks.__dict__["DAIN"](channel=3,
filter_size = 4 ,
timestep= 0.5,
training=False,
useAnimationMethod = useAnimationMethod,
shareMemory = False,
cuda = USE_CUDA, iSize = [iWidth, iHeight],
batch_size= myRenderData.batch_size,
padding = padding_value, depadding = depad_value,
is_half = bool(myRenderData.use_half))
#gl_model = torch.jit.script(gl_model)
else:
#Broken
gl_model = networks.__dict__["DAIN_slowmotion"](channel=3,
filter_size = 4,
timestep= 0.5,
training=False,
useAnimationMethod = useAnimationMethod)
if USE_CUDA:
gl_model = gl_model.cuda()
SAVED_MODEL = myRenderData.model
if os.path.exists(SAVED_MODEL):
#self.LogPrint("The testing model weight is: " + SAVED_MODEL)
if not USE_CUDA:
pretrained_dict = torch.load(SAVED_MODEL, map_location=lambda storage, loc: storage)
# model.load_state_dict(torch.load(SAVED_MODEL, map_location=lambda storage, loc: storage))
else:
pretrained_dict = torch.load(SAVED_MODEL)
# model.load_state_dict(torch.load(SAVED_MODEL))
model_dict = gl_model.state_dict()
pretrained_dict = {k: v for k, v in pretrained_dict.items() if k in model_dict}
# 2. overwrite entries in the existing state dict
model_dict.update(pretrained_dict)
# 3. load the new state dict
gl_model.load_state_dict(model_dict)
# 4. release the pretrained dict for saving memory
pretrained_dict = []
else:
raise Exception("Model file not found. Try to start the app on Admin-mode, if the error persists try to download again the last version of the app.")
#self.LogPrint("*****************************************************************")
#self.LogPrint("**** We don't load any trained weights **************************")
#self.LogPrint("*****************************************************************")
#import PWCNet
gl_model = gl_model.eval() # deploy mode
return gl_model
def interpolate_(gl_model, myRenderData, X0, X1, convert):
use_cuda=True
save_which=1
dtype = torch.cuda.FloatTensor
if myRenderData.cleanCudaCache == 1:
SetTiming("Start Cache Clean")
torch.cuda.empty_cache()
SetTiming("End Cache Clean")
if DEBUG_TEST_NO_CUDA:
return X0
X0 = X0.data.cpu().numpy()
X0 = [np.transpose(255.0 * x.clip(0,1.0), (1, 2, 0)) for x in X0]
X0 = [np.round(x).astype(numpy.uint8) for x in X0]
imgList = []
for item in X0:
imgList.append(np.round(item).astype(numpy.uint8))
return imgList
padding = [0,0 ,0,0]
SetTiming("Calling Model")
with torch.no_grad():
y_s,offset,filter = gl_model(X0, X1, padding, myRenderData.flowForce, myRenderData.SmoothFlow, myRenderData.ShareFlow, convert, not bool(myRenderData.fastMode))
torch.cuda.synchronize()
SetTiming("Ending Model Call")
y_ = y_s[save_which]
#It used to run everything under this, not anymore
if True:
return y_
imgList = []
if not isinstance(y_, list):
yy_ = [torch.round(255.0 * torch.clamp(y_, 0.0, 1.0)[:, :, :].permute(1, 2, 0)) for yy_ in y_]
SetTiming("End Changing Images")
return yy_
else:
return imgList
def SavePNG(png_compress, pil, filepath):
pil.save(filepath, optimize = False, compress_level = int(png_compress))
class DainClass():
panic = ""
myRenderData = None
# 2 / 4 / 8
mainFolder = ""
originalFrames = ""
interpolatedFrames = ""
renderFolder = ""
configFile = ""
lastFrameMs = 0
save_which = None
useMask = False
mask = []
model = None
def GetInterCounter(self):
filename = self.mainFolder + "/resume.txt"
if not os.path.exists(filename):
return 0
myfile = open(filename, 'r')
data = myfile.read()
myfile.close()
obj = json.loads(data)
obj["index"] = int(obj["index"])
obj["counter"] = int(obj["counter"])
return obj
def SetInterpolCounter(self, index, counter):
obj = {"index": index , "counter": counter}
js = json.dumps(obj, cls=json.JSONEncoder)
filename = self.mainFolder + "/resume.txt"
myfile = open(filename, 'w')
myfile.write(js)
myfile.close()
def GetInputSize(self):
for image in sorted(os.listdir(self.originalFrames)):
if image.lower().endswith(".png"):
return PIL.Image.open( os.path.join(self.originalFrames, image)).size
def PilResizeFFMPEG(self, pil, size = 1):
width, height = pil.size
w = round(width * size)
h = round(height * size)
return "scale={}:{}:flags=neighbor".format(w, h)
def PilResize(self, pil, size = 1):
width, height = pil.size
w = round(width * size)
h = round(height * size)
return pil.resize((w, h), resample = PIL.Image.NEAREST)
def extract_frames(self, video, outDir):
if self.myRenderData.inputType == 2:
index = 0
src_files = self._make_video_dataset(video)
for file_name in src_files:
if file_name.endswith("png"):
name = str(index).zfill(10) + ".png"
img = PIL.Image.open(file_name)
if self.myRenderData.resc == 1 and img.size[1] > self.myRenderData.maxResc:
img.thumbnail((99999, self.myRenderData.maxResc) , PIL.Image.ANTIALIAS)
SavePNG(self.myRenderData.pngcompress, img, outDir + "/" + name)
index += 1
return
myRenderData = self.myRenderData
vid = cv2.VideoCapture(video)
height = vid.get(cv2.CAP_PROP_FRAME_HEIGHT)
width = vid.get(cv2.CAP_PROP_FRAME_WIDTH)
vfArr = []
error = ""
if myRenderData.interpolationMethod != 0 and myRenderData.debugKeepDuplicates == 0:
vfArr.append("mpdecimate")
vfArr.append("scale=-1:"+str(myRenderData.maxResc))
if myRenderData.outStr.endswith(".mp4"):
vfArr.append("pad=ceil(iw/2)*2:ceil(ih/2)*2")
vrStr = ",".join(vfArr)
if vrStr != "":
vrStr = '-vf "{}"'.format(vrStr)
if myRenderData.interpolationMethod == 0:
retn = os.system('{} -i "{}" -vsync 0 {} {} -qscale:v 1 "{}%10d.png"'.format(os.path.join("", "ffmpeg"), video, self.panic, vrStr, outDir))
if myRenderData.interpolationMethod == 1:
retn = os.system('{} -i "{}" -vsync 0 {} {} -qscale:v 1 "{}%10d.png"'.format(os.path.join("", "ffmpeg"), video, self.panic, vrStr, outDir))
if myRenderData.interpolationMethod == 2 or myRenderData.interpolationMethod == 3:
retn = os.system('{} -vsync 0 -i "{}" -copyts -r 1000 {} -frame_pts true {} -qscale:v 1 "{}%10d.png"'.format(os.path.join("", "ffmpeg"), video, self.panic, vrStr, outDir))
if self.myRenderData.palette == 1:
os.system('ffmpeg -y -i "{}" {} -filter_complex palettegen=reserve_transparent=1 "{}"'.format(video, self.panic, os.path.join(self.mainFolder, "palette.png") ))
list = sorted(os.listdir(outDir))
first = list[0]
second = list[1]
last = list[len(list)-1]
if myRenderData.interpolationMethod == 2 or myRenderData.interpolationMethod == 3:
if video.endswith("gif"):
self.lastFrameMs = self.filename2timestamp(last) + self.LastFrameTiming(video)
else:
self.lastFrameMs = self.filename2timestamp(last) + self.filename2timestamp(second)
else:
self.lastFrameMs = int(self.filename2timestamp(last)) + 1
if int(self.myRenderData.loop) == 1:
formated = str(self.lastFrameMs).zfill(10) + ".png"
copyfile(os.path.join(outDir, sorted(os.listdir(outDir))[0]), os.path.join(outDir, formated))
if myRenderData.interpolationMethod == 2 or myRenderData.interpolationMethod == 3:
if video.endswith("gif"):
self.lastFrameMs = self.filename2timestamp(last) + self.LastFrameTiming(video) + self.filename2timestamp(second)
else:
self.lastFrameMs = self.filename2timestamp(last) + self.filename2timestamp(second) + self.filename2timestamp(second)
else:
self.lastFrameMs = int(self.filename2timestamp(last)) + 2
fList = sorted(os.listdir(outDir))
frames = FrameCollection()
for i in range(0, len(fList)):
f = FrameData()
f.frameName = fList[i]
f.tsStart = self.filename2timestamp(fList[i])
if i != len(fList) -1:
f.tsEnd = self.filename2timestamp(fList[i+1])
else:
f.tsEnd = self.lastFrameMs
frames.AddFrame(f)
frames.ToJsonFile(self.framesFile)
def LastFrameTiming(self, file):
cam = cv2.VideoCapture(file)
frames = cam.get(cv2.CAP_PROP_FRAME_COUNT)
fps = cam.get(cv2.CAP_PROP_FPS)
p = PIL.Image.open(file)
p.seek(int(frames)-1)
return int(p.info['duration'])
def export_png(self, dir):
path = os.path.dirname(self.myRenderData.outStr) + "/png_frames"
if not os.path.isdir(path):
os.makedirs(path)
src_files = os.listdir(dir)
for file_name in src_files:
full_file_name = os.path.join(dir, file_name)
if os.path.isfile(full_file_name):
if self.myRenderData.palette == 1:
os.system('ffmpeg -y -i "{}" -i "{}" {} -filter_complex "[0:v][1:v] paletteuse" "{}"'.format(full_file_name, os.path.join(self.mainFolder, "palette.png"), self.panic, path + "/" + file_name))
else:
shutil.copy(full_file_name, path)
def RenameSeqFolder(self, src):
ext = ".png"
files = self._make_video_dataset(src)
for i,filename in enumerate(files):
if filename.endswith(ext):
strOut = src + str(i+1).zfill(15)+ext
if filename != strOut:
self.LogPrint("Renaming " + filename +" to " + strOut)
os.rename(filename, strOut)
def GetLastTimingFromGif(path):
cam = cv2.VideoCapture(path)
fps = cam.get(cv2.CAP_PROP_FRAME_COUNT)
p = PIL.Image.open(path)
p.seek(int(fps)-1)
return int(p.info['duration'])
def filesToPil(self, list, original):
pal = PIL.Image.open(original).convert("P")
pal.load()
pilList = []
for i in range(0, len(list)):
f = PIL.Image.open(list[i]).convert("P", None, 0, pal.im)
pilList.append(f)
return pilList
def filename2timestamp(self, filename):
name = os.path.basename(filename)
name_no_ext = name.split(".")[0]
return int(name_no_ext)
def GeneratePILGif(self, outname, fps):
self.gifFolder = os.path.join(self.mainFolder, "gif_frames/")
pallFolder = os.path.join(self.mainFolder, "palette.png")
if not os.path.isfile(pallFolder):
raise Exception("pallet.png not found. Did you run step 1 with 'Limit Colors' on?")
if not os.path.isdir(self.gifFolder):
os.makedirs(self.gifFolder)
files = self._make_video_dataset(self.interpolatedFrames)
pilImages = []
pilDurations = []
std = int(math.ceil(1 / fps * 1000/10)*10)
for i in range(0, len(files)):
filename = os.path.join(self.gifFolder, str(i).zfill(15) + ".gif")
os.system('ffmpeg -y -i "{}" -i "{}" {} -lavfi paletteuse=dither=0 "{}"'.format(files[i], pallFolder, self.panic, filename))
if(i != len(files) - 1):
ts = self.filename2timestamp(files[i+1])
else:
ts = self.filename2timestamp(files[i]) + std
if i == 0:
lastTs = 0
else:
lastTs = self.filename2timestamp(files[i])
img = PIL.Image.open(filename)
if self.myRenderData.pixelUpscaleDowscaleBefore != 1:
img = self.PilResize(img, 1 / self.myRenderData.pixelUpscaleDowscaleBefore)
if self.myRenderData.pixelDownscaleUpscaleAfter != 1:
img = self.PilResize(img, 1 / self.myRenderData.pixelDownscaleUpscaleAfter)
img = self.PilResize(img, self.myRenderData.pixelDownscaleUpscaleAfter)
if self.myRenderData.pixelUpscaleAfter != 1:
img = self.PilResize(img, self.myRenderData.pixelUpscaleAfter)
pilImages.append( img)
if self.myRenderData.interpolationMethod == 2 or self.myRenderData.interpolationMethod == 3:
pilDurations.append( math.ceil(ts/10)*10-math.ceil(lastTs/10)*10 )
else:
pilDurations.append(std)
pilImages[0].save(
outname,
save_all = True,
append_images = pilImages[1:],
duration = pilDurations,
loop = 0,
optimize=False,
disposal=2
)
def create_video2(self, dir, outSub, speed):
myRenderData = self.myRenderData
interpolationMethod = myRenderData.interpolationMethod
error = ""
scaleF = ""
palArg = ''
if interpolationMethod == 0 or interpolationMethod == 1:
self.RenameSeqFolder(dir)
name = os.path.basename(self.myRenderData.outStr)
path = os.path.dirname(self.myRenderData.outStr)
name_base_no_ext = name.split(".")[0]
originalF = self._make_video_dataset(self.originalFrames)
interpolF = self._make_video_dataset(self.interpolatedFrames)
imgOri = PIL.Image.open(originalF[0])
imgInt = PIL.Image.open(interpolF[0])
if myRenderData.onlyRenderMissing == 1:
fps = self.myRenderData.fps
fpsStr = str(int(fps))
elif interpolationMethod == 2 or interpolationMethod == 3:
fps = self.myRenderData.fps * speed
fpsStr = str(int(fps))
else:
originalSize = max(1, len(originalF))
self.LogPrint("Original FPS: " + str(self.myRenderData.fps))
self.LogPrint("Total frames Original: " + str(len(originalF)))
self.LogPrint("Total frames interpolated: " + str(len(interpolF)))
self.LogPrint("Final FPS: " + str(self.myRenderData.fps * (len(interpolF) / originalSize)))
fps = self.myRenderData.fps * (len(interpolF) / originalSize)
fpsStr = str(int(fps))
vf = []
if self.myRenderData.pixelUpscaleDowscaleBefore != 1:
vf.append(self.PilResizeFFMPEG(imgInt, 1 / self.myRenderData.pixelUpscaleDowscaleBefore))
if self.myRenderData.pixelDownscaleUpscaleAfter != 1:
vf.append(self.PilResizeFFMPEG(imgOri, 1 / self.myRenderData.pixelDownscaleUpscaleAfter))
vf.append(self.PilResizeFFMPEG(imgOri, 1))
if self.myRenderData.pixelUpscaleAfter != 1:
vf.append(self.PilResizeFFMPEG(imgOri, self.myRenderData.pixelUpscaleAfter))
vfStr = ",".join(vf)
vf.append("paletteuse=dither=0")
vfPixelStr = ",".join(vf)
if vfStr != "":
vfStr = '-lavfi "{}"'.format(vfStr)
vfPixelStr = '-lavfi "{}"'.format(vfPixelStr)
outFile = outSub+ fpsStr + "fps_" + name
outFile60 = outSub +str(myRenderData.use60RealFps)+ "fps_" + name
outFileSmooth60 = outSub +str(myRenderData.use60RealFps)+ "fps_Smooth_" + name
outFileSharp60 = outSub +str(myRenderData.use60RealFps)+ "fps_Sharp_" + name
outFilePallet = outSub + fpsStr + "fps_limitPallete_" + name
outFilePalletPIL = outSub + fpsStr + "fps_limitPallete_PIL_" + name_base_no_ext + ".gif"
outFileAudio = outSub+ fpsStr + "fps_audio_" + name
outFile60Audio = outSub +str(myRenderData.use60RealFps)+ "fps_audio_" + name
outFileSmooth60Audio = outSub +str(myRenderData.use60RealFps)+ "fps_audio_Smooth_" + name
outFileSharp60Audio = outSub +str(myRenderData.use60RealFps)+ "fps_audio_Sharp_" + name
self.LogPrint("Interpolation Folder: " + dir)
self.LogPrint("Output Video: " + outFile)
muxer = ""
pixFmt = "-pix_fmt yuv420p"
if outFile.endswith(".mp4"):
muxer = "-c:v libx264 -crf " + str(self.myRenderData.crf)
if outFile.endswith(".gif"):
pixFmt = ""
if outFile.endswith(".apng"):
pixFmt = "-pix_fmt rgb32"
if interpolationMethod == 0 or interpolationMethod == 1:
retn = os.system('ffmpeg -y -framerate {fps} -i "{input}%15d.png" {panic} -qscale:v 0 {muxer} {fmt} {vf} "{out}"'.format(fps=fps, input=dir, panic=self.panic, muxer=muxer, fmt=pixFmt, vf=vfStr, out=outFile))
if self.myRenderData.palette == 1:
palArg = '-framerate "{fps}" -i "{input}" {vf}'.format(fps=fps, input=os.path.join(self.mainFolder, "palette.png"), vf=vfPixelStr)
f = 'ffmpeg -y -framerate "{fps}" -i "{input}%15d.png" {pallet} {panic} -qscale:v 0 {muxer} {fmt} "{out}"'.format(fps=fps, input=dir, pallet=palArg, panic=self.panic, muxer=muxer, fmt=pixFmt, out=outFilePallet)
os.system(f)
self.GeneratePILGif(outFilePalletPIL, fps)
else:
files = []
files = self._make_video_dataset(dir)
strFile = ""
pilDurations = []
for i in range(0, len(files)-1):
name = os.path.basename(files[i])
name_no_ext = name.split(".")[0]
duration = float(name_no_ext) / 1000
name2 = os.path.basename(files[i+1])
name_no_ext2 = name2.split(".")[0]
duration2 = float(name_no_ext2) / 1000
pilDurations.append(float(name_no_ext2) - float(name_no_ext))
dur = (duration2-duration)
strFile += "file '"+ name+"'\nduration "+ "{:.5f}".format(dur) + "\n"
framesCol = FrameCollection()
framesCol.FromJsonFile(self.framesFile)
if len(framesCol.frames) != 0:
file = files[len(files)-1]
name = os.path.basename(file)
lastF = framesCol.frames[len(framesCol.frames) - 1]
file = files[len(files)-1]
name = os.path.basename(file)
strFile += "file '"+name+"'\nduration "+ "{:.5f}".format(dur) + "\n"
dir_path = os.path.dirname(os.path.realpath(__file__))
filename = dir + "/my_file.txt"
myfile = open(filename, 'w')
myfile.write(strFile)
myfile.close()
txtPath= os.path.join(dir, "my_file.txt")
palletPath = os.path.join(self.mainFolder, "palette.png")
retn = os.system('ffmpeg -y -vsync 1 -f concat -i "{txtPath}" {panic} {muxer} {fmt} -qscale:v 1 {vf} -r {fps} "{out}"'.format(txtPath=txtPath, fps=fps, speed=speed, panic=self.panic, muxer=muxer, fmt=pixFmt, vf=vfStr, out=outFile))
if self.myRenderData.palette == 1:
retn = os.system('ffmpeg -y -vsync 0 -f concat -i "{txtPath}" -i "{palletPath}" {panic} {muxer} {fmt} -qscale:v 1 {vf} -r {fps} "{out}"'.format(txtPath=txtPath, palletPath=palletPath, fps=fps, panic=self.panic, muxer=muxer, fmt=pixFmt, vf=vfPixelStr, out=outFilePallet))
self.GeneratePILGif(outFilePalletPIL, fps)
if myRenderData.audioVersion == 1:
self.LogPrint("Creating audio version")
self.AddAudio(outFile, myRenderData.video, outFileAudio)
if fps > myRenderData.use60RealFps:
if myRenderData.use60:
self.SetTo60(outFile, outFile60, myRenderData.use60RealFps)
if myRenderData.audioVersion == 1:
self.AddAudio(outFile60, myRenderData.video, outFile60Audio)
if myRenderData.use60C1:
self.SetTo60Smooth(outFile, outFileSmooth60, myRenderData.use60RealFps)
if myRenderData.audioVersion == 1:
self.AddAudio(outFileSmooth60, myRenderData.video, outFileSmooth60Audio)
if myRenderData.use60C2:
self.SetTo60Shart(outFile, outFileSharp60, myRenderData.use60RealFps)
if myRenderData.audioVersion == 1:
self.AddAudio(outFileSharp60, myRenderData.video, outFileSharp60Audio)
if retn:
error = "Error creating output video. Exiting."
return error
def SetTo60(self, inFile, outFile, fps):
os.system('ffmpeg -y -i "{}" {} -filter:v fps=fps={} -crf {} -qscale:v 0 "{}"'.format(inFile, self.panic, fps, str(self.myRenderData.crf), outFile))
def SetTo60Smooth(self, inFile, outFile, fps):
os.system('ffmpeg -y -i "{}" {} -vf "minterpolate=fps={}:mi_mode=mci:mc_mode=aobmc:me_mode=bidir:vsbmc=1" -crf {} -qscale:v 0 "{}"'.format(inFile, self.panic, fps, str(self.myRenderData.crf), outFile))
def SetTo60Shart(self, inFile, outFile, fps):
os.system('ffmpeg -y -i "{}" {} -vf "minterpolate=fps={}:mi_mode=mci:mc_mode=aobmc:me_mode=bidir:vsbmc=0" -crf {} -qscale:v 0 "{}"'.format(inFile, self.panic, fps, str(self.myRenderData.crf), outFile))
def AddAudio(self, inFile, audioSource, outFile):
v = cv2.VideoCapture(audioSource)
fps = max(1, v.get(cv2.CAP_PROP_FPS)) # OpenCV2 version 2 used "CV_CAP_PROP_FPS"
frame_count = int(v.get(cv2.CAP_PROP_FRAME_COUNT))
vDuration = frame_count/fps
a = cv2.VideoCapture(inFile)
fps = max(1, a.get(cv2.CAP_PROP_FPS)) # OpenCV2 version 2 used "CV_CAP_PROP_FPS"
frame_count = int(a.get(cv2.CAP_PROP_FRAME_COUNT))
aDuration = frame_count/fps
if aDuration == 0:
atempo = 0
else:
atempo = vDuration / aDuration
os.system('ffmpeg -y -i "{}" -i "{}" {} -filter_complex "[0:v:0]setpts=PTS[v];[1:a:0]atempo={}[a]" -crf {} -qscale:v 0 -map "[v]" -map "[a]" "{}"'.format(inFile, audioSource, self.panic, atempo, str(self.myRenderData.crf), outFile))
def _make_video_dataset(self, dir):
framesPath = []
# Find and loop over all the frames in root `dir`.
for image in sorted(os.listdir(dir)):
# Add path to list.
if image.lower().endswith(".png"):
framesPath.append(os.path.join(dir, image))
return framesPath
def FitFrame(self, frame):
return (frame.clamp(0.0, 1.0).numpy().transpose(1, 2, 0) * 255.0).astype(numpy.uint8)
def easySin(self, t, repeats):
inc = int(t * repeats)
incDiv = inc / repeats
t2 = t * repeats
cos = 0.5 * (1 - math.cos((t2 - int(t2)) * math.pi))
return cos / repeats + incDiv
def Splitter(self, img, img2, ww, hh, padding):
areas1 = []
areas2 = []
areaPoints = []
debug = False
indexW = 3
indexH = 2
wSource = img.shape[indexW]
hSource = img.shape[indexH]
width = math.ceil(wSource / ww)
height = math.ceil(hSource / hh)
if not self.didSplitterPrinted:
print("\n--Splits:")
print("Using X_Param:{x} and Y_Param:{y}".format(x=ww, y=hh))
splitCounter = 1
for x in range(0, img.shape[indexW], width):
for y in range(0, img.shape[indexH], height):
left = max(0, x - padding)
right = min(img.shape[indexW], x + width + padding)
top = max(0, y - padding)
down = min(img.shape[indexH], y + height + padding)
if right - left % 2 == 1 and right != 0:
left -= 1
xIni = max(0, x)
xEnd = min(img.shape[indexW], x + width)
yIni = max(0, y)
yEnd = min(img.shape[indexH], y + height)
if not self.didSplitterPrinted:
print("Split {c}: No-Padded frame: From_X:{xIni:4} To_X:{xEnd:4} From_Y:{yIni:4} To_Y: {yEnd:4}".format(
xIni=xIni, xEnd=xEnd, yIni=yIni, yEnd=yEnd, c=splitCounter))
print("Split {c}: Padded frame : From_X:{xIni:4} To_X:{xEnd:4} From_Y:{yIni:4} To_Y: {yEnd:4}".format(
xIni=left, xEnd=right, yIni=top, yEnd=down, c=splitCounter))
if(debug):
xEnd -= 1
yEnd -= 1
points = []
points.append(xIni)
points.append(xEnd)
points.append(yIni)
points.append(yEnd)
points.append(xIni - left)
points.append(xEnd - x)
points.append(yIni - top)
points.append(yEnd - y)
areaPoints.append(points)
areas1.append(img[:, :, top:down, left:right])
areas2.append(img2[:, :, top:down, left:right])
splitCounter += 1
self.didSplitterPrinted = True
areaInter = []
for i in range(0, len(areas1)):
loopW = areas1[i].shape[indexW]
loopH = areas1[i].shape[indexH]
pad = CalculatePad(loopW, loopH)
areas1[i] = torch.nn.functional.pad(areas1[i].float(), (pad[0], pad[1] , pad[2], pad[3]), mode='replicate', value=0)
areas2[i] = torch.nn.functional.pad(areas2[i].float(), (pad[0], pad[1] , pad[2], pad[3]), mode='replicate', value=0)
depad = (pad[0], pad[1] +loopW, pad[2], pad[3] +loopH)
self.model.depadding = depad
newArea = interpolate_(self.model, self.myRenderData, areas1[i], areas2[i], True)
areaInter.append(newArea.cpu())
frames = len(areaInter[0])
sewed = torch.empty((frames, 3, img.shape[indexH], img.shape[indexW]))
for f in range(0, frames):
for i in range(0, len(areaInter)):
p = areaPoints[i]
sewed[f, :, p[2]:p[3], p[0]:p[1]] = areaInter[i][f][:, p[6]:p[7] + p[6], p[4]:p[5] + p[4]]
return sewed
def DoInterpolation(self, x0, x1, loops):
myRenderData = self.myRenderData
if myRenderData.splitFrames == 0:
image = interpolate_(self.model, self.myRenderData, x0, x1, False)
else:
image = self.Splitter(x0, x1, myRenderData.splitSizeX, myRenderData.splitSizeY, myRenderData.splitPad)
if myRenderData.interpolationAlgorithm == 1:
if isinstance(image, list):
return image
if loops - 1 > 0:
imB = self.DoInterpolation(x0, image, loops-1)
imA = self.DoInterpolation(image, x1, loops-1)
return imB + [image] + imA
return [image]
def TakeMedium(self, f1, f2):
currFilename = os.path.basename(f1)
prevFilename = os.path.basename(f2)
fC = int(currFilename.split(".")[0])
fP = int(prevFilename.split(".")[0])
return fC
return (fC + fP) / 2
def dirtHack(self, i, val):
temp = i
while temp < val:
temp = (temp * 2) + 1
i += 1
return i - 1
def FillMissingOriginalFrames(self):
toFill = []
list = self._make_video_dataset(self.originalFrames)
last_name = os.path.basename(list[len(list)-1])
last_index = int(last_name.split('.')[0])
lastF = 1
for i in range(1, last_index):
if os.path.exists(self.originalFrames + str(i).zfill(10) + ".png"):
print("Exist : " + str(i).zfill(10))
lastF = i
else:
print("Not : " + str(i).zfill(10))
def GetChannel(self, _filePath, type):
conversions = []
for _, filePath in enumerate(_filePath):
myRenderData = self.myRenderData
img = PIL.Image.open(filePath)
if self.myRenderData.pixelUpscaleDowscaleBefore != 1:
img = self.PilResize(img, self.myRenderData.pixelUpscaleDowscaleBefore)
if myRenderData.alphaMethod == 0:
conversions.append(img.convert('RGB'))
continue
red, green, blue, alpha = img.convert('RGBA').split()
alphaRGB = alpha.convert("RGB")
red = PIL.ImageChops.multiply(red, alphaRGB.split()[0])
green = PIL.ImageChops.multiply(green, alphaRGB.split()[1])
blue = PIL.ImageChops.multiply(blue, alphaRGB.split()[2])
if myRenderData.alphaMethod == 1:
return PIL.Image.merge("RGBA", (red, green, blue, alpha))
if type == 0:
conversions.append(PIL.Image.merge("RGB", (red, green, blue)))
if type == 1:
conversions.append(PIL.Image.merge("RGB", (alpha, alpha, alpha)))
if type == 2:
conversions.append(PIL.Image.merge("RGB", (red, green, alpha)))
return conversions
def LogPrint(self, str):
if self.myRenderData.quiet == 0:
print(str)
def CheckAllScenes(self, myRenderData, diff):
self.SetFolders(myRenderData)
files = self._make_video_dataset(self.originalFrames)
diffs = []
for i in range(1, len(files)):
if psnr.IsDiffScenes(files[i-1], files[i], diff):
diffs.append(files[i-1])
diffs.append(files[i])
return diffs
def SetFolders(self, myRenderData):
name = os.path.basename(myRenderData.outStr)
self.mainFolder = myRenderData.outFolder
self.originalFrames = self.mainFolder + "original_frames/"
self.interpolatedFrames = self.mainFolder + "interpolated_frames/"
self.renderFolder = self.mainFolder + "output_videos/"
self.configFile = self.mainFolder + "config.json"
self.framesFile = self.mainFolder + "frames.json"
self.LogPrint("Main Folder: " + self.mainFolder)
if not os.path.isdir(self.mainFolder):
os.makedirs(self.mainFolder)
if myRenderData.inputType != 3:
myRenderData.ToJsonFile(self.configFile)
else:
do = myRenderData.doOriginal
di = myRenderData.doIntepolation
dv = myRenderData.doVideo
myRenderData.FromJsonFile(self.configFile)
myRenderData.doOriginal = do
myRenderData.doIntepolation = di
myRenderData.doVideo = dv
myRenderData.uploadBar = None
myRenderData.cleanOriginal = 0
myRenderData.cleanInterpol = 0
myRenderData.inputType = 3
def StepExtractFrames(self, myRenderData):
self.LogPrint("Starting PNG frames extraction!")
if myRenderData.cleanOriginal == 1:
if os.path.isdir(self.originalFrames):
shutil.rmtree(self.originalFrames)
time.sleep(2)
if not os.path.isdir(self.originalFrames):
os.makedirs(self.originalFrames)
self.extract_frames(myRenderData.video, self.originalFrames)
self.LogPrint("Finished PNG frames extraction!")
def StepRenderInterpolation(self, myRenderData):
self.LogPrint("Starting Interpolation!")
files = self._make_video_dataset(self.originalFrames)
if myRenderData.cleanInterpol == 1:
if os.path.isdir(self.interpolatedFrames):
shutil.rmtree(self.interpolatedFrames)
#Try to avoid Denied access
time.sleep(2)
if not os.path.isdir(self.interpolatedFrames):
os.makedirs(self.interpolatedFrames)
if myRenderData.onlyRenderMissing == 1:
framesCol = FrameCollection()
framesCol.FromJsonFile(self.framesFile)
fList = framesCol.frames
missingInterpolations = []
lastIndex = 0
newList = []
for i in range(0, len(fList)):
framepath = self.originalFrames + fList[i]["frameName"]
if os.path.isfile(framepath):
newList.append(framepath)
index = len(newList)- 1
missingInterpolations.append(0)
lastIndex = index
else:
missingInterpolations[lastIndex] += 1
files = newList
if myRenderData.interpolationMethod:
myRenderData.batch_size = 1