ぼかし、音
その辺のWEBを参考に音を出した。
import glob
import torch
import cv2
import numpy as np
import os
import threading
import queue
import datetime
import time
import re
import moviepy.editor as mp
input_dir = '/content/drive/MyDrive/py_mosa/input/'
split_dir = '/content/drive/MyDrive/py_mosa/work1/'
work_dir = '/content/drive/MyDrive/py_mosa/work2/'
output_dir = '/content/drive/MyDrive/py_mosa/output/'
checkPointFilePath = '/content/drive/MyDrive/py_mosa/checkpoint.txt'
fileSplitSize = 250
def getCheckPoint():
ret = [None, None]
if not os.path.exists(checkPointFilePath):
return ret
f = open(checkPointFilePath)
for i in range(2):
line = f.readline()
if line:
ret[i] = line.replace('\n','')
else:
break
f.close()
del f
return ret
def putCheckPoint(inp1, inp2):
f = open(checkPointFilePath, "w")
f.write(inp1)
f.write("\n")
if inp2 is not None:
f.write(inp2)
f.write("\n")
f.close()
del f
def del_workdir():
files = glob.glob(split_dir + "*")
for f in files:
os.remove(f)
del files
files = glob.glob(work_dir + "*")
for f in files:
os.remove(f)
del files
def movie_split(input_video, out_video):
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
fnum = 1
writer = cv2.VideoWriter(split_dir + str(fnum) + "_" + out_video, fmt, float(frame_rate),(w,h))
num = 0
fchkp = 0
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
if fchkp >= fileSplitSize:
writer.release()
fnum += 1
writer = cv2.VideoWriter(split_dir + str(fnum) + "_" + out_video, fmt, float(frame_rate),(w,h))
fchkp = 0
else:
pass
writer.write(frame)
num += 1
fchkp += 1
else:
break
writer.release()
video.release()
del writer
del video
def atoi(text):
return int(text) if text.isdigit() else text
def natural_keys(text):
return [ atoi(c) for c in re.split(r'(\d+)', text) ]
def movie_join(input_video, out_video):
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
video.release()
writer = cv2.VideoWriter(output_dir + out_video, fmt, float(frame_rate),(w,h))
files = sorted(glob.glob(work_dir + "*"), key=natural_keys)
for f in files:
video = cv2.VideoCapture(f)
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
writer.write(frame)
else:
break
video.release()
del video
writer.release()
del writer
return img
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
writer = cv2.VideoWriter(out_video, fmt, float(frame_rate),(w,h))
num = 0
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
results = model(frame)
results.xyxy[0]
results.pandas().xyxy[0]
for j in range(len(results.pandas().xyxy[0])):
if results.pandas().xyxy[0]["class"][j] == 0 \
or results.pandas().xyxy[0]["class"][j] == 2:
ymin = int(results.pandas().xyxy[0]["ymin"][j])
ymax = int(results.pandas().xyxy[0]["ymax"][j])
xmin = int(results.pandas().xyxy[0]["xmin"][j])
xmax = int(results.pandas().xyxy[0]["xmax"][j])
frame[ymin:ymax,xmin:xmax] = mosaic(frame[ymin:ymax,xmin:xmax])
else:
pass
writer.write(frame)
num += 1
else:
break
writer.release()
video.release()
del writer
del video
def set_audio(srcfile,imgfile,outfile):
# Extract audio from input video.
clip_input = mp.VideoFileClip(srcfile)
clip_input.audio.write_audiofile('/content/drive/MyDrive/py_mosa/output/audio.mp3')
# Add audio to output video.
clip = mp.VideoFileClip(imgfile).subclip()
clip.write_videofile(outfile, audio='/content/drive/MyDrive/py_mosa/output/audio.mp3')
if __name__ == '__main__':
model = torch.hub.load('ultralytics/yolov5', 'yolov5x', pretrained=True, force_reload=True)
chkPoint1,chkPoint2 = getCheckPoint()
files = sorted(glob.glob(input_dir + "*.mp4"), key=natural_keys)
for f in files:
input_video = f
if chkPoint1 is not None:
if chkPoint1 == input_video:
chkPoint1 = None
else:
print("skip1", input_video)
continue
if chkPoint2 is None:
putCheckPoint(input_video, None)
out_video_fname = os.path.basename(f)
if chkPoint2 is None:
del_workdir()
movie_split(input_video, out_video_fname)
queF = queue.Queue()
files2 = sorted(glob.glob(split_dir + "*.mp4"), key=natural_keys)
for f2 in files2:
if chkPoint2 is not None:
if chkPoint2 == f2:
chkPoint2 = None
else:
print("skip2", f2)
continue
queF.put(f2)
del files2
while True:
print(input_video, "queF.unfinished_tasks", queF.unfinished_tasks)
if queF.unfinished_tasks == 0:
break
wInput_video = queF.get()
wOut_video = work_dir + os.path.basename(wInput_video)
movie_mosaic(wInput_video, wOut_video)
putCheckPoint(input_video, wInput_video)
queF.task_done()
movie_join(input_video, out_video_fname)
set_audio(input_video,output_dir + out_video_fname,(output_dir + out_video_fname).replace(".mp4", "_audio.mp4"))
del_workdir()
os.remove(checkPointFilePath)
del model
img = cv2.blur(img, (30, 30))でぼかした。
モザイクだったところをimg = cv2.blur(img, (30, 30))でぼかした。
import glob
import torch
import cv2
import numpy as np
import os
import threading
import queue
import datetime
import time
import re
input_dir = '/content/drive/MyDrive/py_mosa/input/'
split_dir = '/content/drive/MyDrive/py_mosa/work1/'
work_dir = '/content/drive/MyDrive/py_mosa/work2/'
output_dir = '/content/drive/MyDrive/py_mosa/output/'
checkPointFilePath = '/content/drive/MyDrive/py_mosa/checkpoint.txt'
fileSplitSize = 250
def getCheckPoint():
ret = [None, None]
if not os.path.exists(checkPointFilePath):
return ret
f = open(checkPointFilePath)
for i in range(2):
line = f.readline()
if line:
ret[i] = line.replace('\n','')
else:
break
f.close()
del f
return ret
def putCheckPoint(inp1, inp2):
f = open(checkPointFilePath, "w")
f.write(inp1)
f.write("\n")
if inp2 is not None:
f.write(inp2)
f.write("\n")
f.close()
del f
def del_workdir():
files = glob.glob(split_dir + "*")
for f in files:
os.remove(f)
del files
files = glob.glob(work_dir + "*")
for f in files:
os.remove(f)
del files
def movie_split(input_video, out_video):
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
fnum = 1
writer = cv2.VideoWriter(split_dir + str(fnum) + "_" + out_video, fmt, float(frame_rate),(w,h))
num = 0
fchkp = 0
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
if fchkp >= fileSplitSize:
writer.release()
fnum += 1
writer = cv2.VideoWriter(split_dir + str(fnum) + "_" + out_video, fmt, float(frame_rate),(w,h))
fchkp = 0
else:
pass
writer.write(frame)
num += 1
fchkp += 1
else:
break
writer.release()
video.release()
del writer
del video
def atoi(text):
return int(text) if text.isdigit() else text
def natural_keys(text):
return [ atoi(c) for c in re.split(r'(\d+)', text) ]
def movie_join(input_video, out_video):
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
video.release()
writer = cv2.VideoWriter(output_dir + out_video, fmt, float(frame_rate),(w,h))
files = sorted(glob.glob(work_dir + "*"), key=natural_keys)
for f in files:
video = cv2.VideoCapture(f)
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
writer.write(frame)
else:
break
video.release()
del video
writer.release()
del writer
return img
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
writer = cv2.VideoWriter(out_video, fmt, float(frame_rate),(w,h))
num = 0
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
results = model(frame)
results.xyxy[0]
results.pandas().xyxy[0]
for j in range(len(results.pandas().xyxy[0])):
if results.pandas().xyxy[0]["class"][j] == 0 \
or results.pandas().xyxy[0]["class"][j] == 2:
ymin = int(results.pandas().xyxy[0]["ymin"][j])
ymax = int(results.pandas().xyxy[0]["ymax"][j])
xmin = int(results.pandas().xyxy[0]["xmin"][j])
xmax = int(results.pandas().xyxy[0]["xmax"][j])
frame[ymin:ymax,xmin:xmax] = mosaic(frame[ymin:ymax,xmin:xmax])
else:
pass
writer.write(frame)
num += 1
else:
break
writer.release()
video.release()
del writer
del video
if __name__ == '__main__':
model = torch.hub.load('ultralytics/yolov5', 'yolov5x', pretrained=True, force_reload=True)
chkPoint1,chkPoint2 = getCheckPoint()
files = sorted(glob.glob(input_dir + "*.mp4"), key=natural_keys)
for f in files:
input_video = f
if chkPoint1 is not None:
if chkPoint1 == input_video:
chkPoint1 = None
else:
print("skip1", input_video)
continue
if chkPoint2 is None:
putCheckPoint(input_video, None)
out_video_fname = os.path.basename(f)
if chkPoint2 is None:
del_workdir()
movie_split(input_video, out_video_fname)
queF = queue.Queue()
files2 = sorted(glob.glob(split_dir + "*.mp4"), key=natural_keys)
for f2 in files2:
if chkPoint2 is not None:
if chkPoint2 == f2:
chkPoint2 = None
else:
print("skip2", f2)
continue
queF.put(f2)
del files2
while True:
print(input_video, "queF.unfinished_tasks", queF.unfinished_tasks)
if queF.unfinished_tasks == 0:
break
wInput_video = queF.get()
wOut_video = work_dir + os.path.basename(wInput_video)
movie_mosaic(wInput_video, wOut_video)
putCheckPoint(input_video, wInput_video)
queF.task_done()
movie_join(input_video, out_video_fname)
del_workdir()
os.remove(checkPointFilePath)
del model
■
Rate exceeded がでるので、スレッドは止めてみた・・・
import glob
import torch
import cv2
import numpy as np
import os
import threading
import queue
import datetime
import time
import re
input_dir = '/content/drive/MyDrive/py_mosa/input/'
split_dir = '/content/drive/MyDrive/py_mosa/work1/'
work_dir = '/content/drive/MyDrive/py_mosa/work2/'
output_dir = '/content/drive/MyDrive/py_mosa/output/'
checkPointFilePath = '/content/drive/MyDrive/py_mosa/checkpoint.txt'
fileSplitSize = 250
def getCheckPoint():
ret = [None, None]
if not os.path.exists(checkPointFilePath):
return ret
f = open(checkPointFilePath)
for i in range(2):
line = f.readline()
if line:
ret[i] = line.replace('\n','')
else:
break
f.close()
del f
return ret
def putCheckPoint(inp1, inp2):
f = open(checkPointFilePath, "w")
f.write(inp1)
f.write("\n")
if inp2 is not None:
f.write(inp2)
f.write("\n")
f.close()
del f
def del_workdir():
files = glob.glob(split_dir + "*")
for f in files:
os.remove(f)
del files
files = glob.glob(work_dir + "*")
for f in files:
os.remove(f)
del files
def movie_split(input_video, out_video):
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
fnum = 1
writer = cv2.VideoWriter(split_dir + str(fnum) + "_" + out_video, fmt, float(frame_rate),(w,h))
num = 0
fchkp = 0
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
if fchkp >= fileSplitSize:
writer.release()
fnum += 1
writer = cv2.VideoWriter(split_dir + str(fnum) + "_" + out_video, fmt, float(frame_rate),(w,h))
fchkp = 0
else:
pass
writer.write(frame)
num += 1
fchkp += 1
else:
break
writer.release()
video.release()
del writer
del video
def atoi(text):
return int(text) if text.isdigit() else text
def natural_keys(text):
return [ atoi(c) for c in re.split(r'(\d+)', text) ]
def movie_join(input_video, out_video):
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
video.release()
writer = cv2.VideoWriter(output_dir + out_video, fmt, float(frame_rate),(w,h))
files = sorted(glob.glob(work_dir + "*"), key=natural_keys)
for f in files:
video = cv2.VideoCapture(f)
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
writer.write(frame)
else:
break
video.release()
del video
writer.release()
del writer
def mosaic(img, alpha):
w = img.shape[1]
h = img.shape[0]
if w < 20 or h < 20:
return img
else:
pass
img = cv2.resize(img, (int(w*alpha), int(h*alpha)))
img = cv2.resize(img, (w, h), interpolation=cv2.INTER_NEAREST)
return img
def movie_mosaic(input_video, out_video):
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
writer = cv2.VideoWriter(out_video, fmt, float(frame_rate),(w,h))
num = 0
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
results = model(frame)
results.xyxy[0]
results.pandas().xyxy[0]
for j in range(len(results.pandas().xyxy[0])):
if results.pandas().xyxy[0]["class"][j] == 0 or results.pandas().xyxy[0]["class"][j] == 2:
ymin = int(results.pandas().xyxy[0]["ymin"][j])
ymax = int(results.pandas().xyxy[0]["ymax"][j])
xmin = int(results.pandas().xyxy[0]["xmin"][j])
xmax = int(results.pandas().xyxy[0]["xmax"][j])
frame[ymin:ymax,xmin:xmax] = mosaic(frame[ymin:ymax,xmin:xmax], alpha)
else:
pass
writer.write(frame)
num += 1
else:
break
writer.release()
video.release()
del writer
del video
if __name__ == '__main__':
model = torch.hub.load('ultralytics/yolov5', 'yolov5x', pretrained=True, force_reload=True)
chkPoint1,chkPoint2 = getCheckPoint()
alpha = 0.05
files = sorted(glob.glob(input_dir + "*.mp4"), key=natural_keys)
for f in files:
input_video = f
if chkPoint1 is not None:
if chkPoint1 == input_video:
chkPoint1 = None
else:
print("skip1", input_video)
continue
if chkPoint2 is None:
putCheckPoint(input_video, None)
out_video_fname = os.path.basename(f)
if chkPoint2 is None:
del_workdir()
movie_split(input_video, out_video_fname)
queF = queue.Queue()
files2 = sorted(glob.glob(split_dir + "*.mp4"), key=natural_keys)
for f2 in files2:
if chkPoint2 is not None:
if chkPoint2 == f2:
chkPoint2 = None
else:
print("skip2", f2)
continue
queF.put(f2)
del files2
while True:
print(input_video, "queF.unfinished_tasks", queF.unfinished_tasks)
if queF.unfinished_tasks == 0:
break
wInput_video = queF.get()
wOut_video = work_dir + os.path.basename(wInput_video)
movie_mosaic(wInput_video, wOut_video)
putCheckPoint(input_video, wInput_video)
queF.task_done()
movie_join(input_video, out_video_fname)
del_workdir()
os.remove(checkPointFilePath)
del model
python初心者がcolabる
無料枠でメモリ間に合うようにせこく分割したりしてる。
何で音が消えるんだ？
import glob
import torch
import cv2
import numpy as np
import os
import threading
import queue
import datetime
import time
import re
input_dir = '/content/drive/MyDrive/py_mosa/input/'
split_dir = '/content/drive/MyDrive/py_mosa/work1/'
work_dir = '/content/drive/MyDrive/py_mosa/work2/'
output_dir = '/content/drive/MyDrive/py_mosa/output/'
checkPointFilePath = '/content/drive/MyDrive/py_mosa/checkpoint.txt'
thCnt = 4
fileSplitSize = 250
modelFirst =torch.hub.load('ultralytics/yolov5', 'yolov5x', pretrained=True)
del modelFirst
def getCheckPoint():
ret = [None, None]
if not os.path.exists(checkPointFilePath):
return ret
f = open(checkPointFilePath)
for i in range(2):
line = f.readline()
if line:
ret[i] = line.replace('\n','')
else:
break
f.close()
del f
return ret
def putCheckPoint(inp1, inp2):
f = open(checkPointFilePath, "w")
f.write(inp1)
f.write("\n")
if inp2 is not None:
f.write(inp2)
f.write("\n")
f.close()
del f
def del_workdir():
files = glob.glob(split_dir + "*")
for f in files:
os.remove(f)
del files
files = glob.glob(work_dir + "*")
for f in files:
os.remove(f)
del files
def movie_split(input_video, out_video):
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
fnum = 1
writer = cv2.VideoWriter(split_dir + str(fnum) + "_" + out_video, fmt, float(frame_rate),(w,h))
num = 0
fchkp = 0
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
if fchkp >= fileSplitSize:
writer.release()
fnum += 1
writer = cv2.VideoWriter(split_dir + str(fnum) + "_" + out_video, fmt, float(frame_rate),(w,h))
fchkp = 0
else:
pass
writer.write(frame)
num += 1
fchkp += 1
else:
break
writer.release()
video.release()
del writer
del video
def atoi(text):
return int(text) if text.isdigit() else text
def natural_keys(text):
return [ atoi(c) for c in re.split(r'(\d+)', text) ]
def movie_join(input_video, out_video):
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
video.release()
writer = cv2.VideoWriter(output_dir + out_video, fmt, float(frame_rate),(w,h))
files = sorted(glob.glob(work_dir + "*"), key=natural_keys)
for f in files:
video = cv2.VideoCapture(f)
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
writer.write(frame)
else:
break
video.release()
del video
writer.release()
del writer
def mosaic(img, alpha):
w = img.shape[1]
h = img.shape[0]
if w < 20 or h < 20:
return img
else:
pass
img = cv2.resize(img, (int(w*alpha), int(h*alpha)))
img = cv2.resize(img, (w, h), interpolation=cv2.INTER_NEAREST)
return img
def movie_mosaic(input_video, out_video):
model =torch.hub.load('ultralytics/yolov5', 'yolov5x', pretrained=True)
video = cv2.VideoCapture(input_video)
w = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
h = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = (w,h)
frame_count = video.get(cv2.CAP_PROP_FRAME_COUNT)
frame_rate = video.get(cv2.CAP_PROP_FPS)
fmt = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
writer = cv2.VideoWriter(out_video, fmt, float(frame_rate),(w,h))
num = 0
while(video.isOpened()):
ret,frame = video.read()
if ret == True:
results = model(frame)
results.xyxy[0]
results.pandas().xyxy[0]
for j in range(len(results.pandas().xyxy[0])):
if results.pandas().xyxy[0]["class"][j] == 0 or results.pandas().xyxy[0]["class"][j] == 2:
ymin = int(results.pandas().xyxy[0]["ymin"][j])
ymax = int(results.pandas().xyxy[0]["ymax"][j])
xmin = int(results.pandas().xyxy[0]["xmin"][j])
xmax = int(results.pandas().xyxy[0]["xmax"][j])
frame[ymin:ymax,xmin:xmax] = mosaic(frame[ymin:ymax,xmin:xmax], alpha)
else:
pass
writer.write(frame)
num += 1
else:
break
writer.release()
video.release()
del writer
del video
del model
class ThreadingMosaic(threading.Thread):
def __init__(self, input_video, out_video):
super(ThreadingMosaic, self).__init__()
self.input_video = input_video
self.out_video = out_video
def run(self):
movie_mosaic(self.input_video, self.out_video)
def inputfile(self):
return self.input_video
if __name__ == '__main__':
chkPoint1,chkPoint2 = getCheckPoint()
alpha = 0.05
files = sorted(glob.glob(input_dir + "*.mp4"), key=natural_keys)
for f in files:
input_video = f
if chkPoint1 is not None:
if chkPoint1 == input_video:
chkPoint1 = None
else:
print("skip1", input_video)
continue
if chkPoint2 is None:
putCheckPoint(input_video, None)
out_video_fname = os.path.basename(f)
if chkPoint2 is None:
del_workdir()
movie_split(input_video, out_video_fname)
queF = queue.Queue()
thMap = {}
for i in range(thCnt):
thMap[str(i)] = None
files2 = sorted(glob.glob(split_dir + "*.mp4"), key=natural_keys)
for f2 in files2:
if chkPoint2 is not None:
if chkPoint2 == f2:
chkPoint2 = None
else:
print("skip2", f2)
continue
queF.put(f2)
del files2
while True:
print(input_video, "queF.unfinished_tasks", queF.unfinished_tasks)
if queF.unfinished_tasks == 0:
break
for i in range(thCnt):
thMapKey = str(i)
wInput_video = queF.get()
wOut_video = work_dir + os.path.basename(wInput_video)
threadingMosaic = ThreadingMosaic(wInput_video, wOut_video)
thMap[thMapKey] = threadingMosaic;
threadingMosaic.start()
queF.task_done()
if queF.unfinished_tasks == 0:
break
for i in range(thCnt):
thMapKey = str(i)
if thMap[str(i)] is not None:
putCheckPoint(input_video, thMap[str(i)].inputfile())
thMap[str(i)].join()
movie_join(input_video, out_video_fname)
del_workdir()
os.remove(checkPointFilePath)
