我正在尝试使用 moviepy 将 .MOV 文件转换为 .mp4 文件，据我所知，它是 ffmpeg 的包装器。我之前曾成功过，但当 ffmpeg 在 89% 时停止时，我感到很失望。我把它放了一个多小时，但没有任何进展。我很好奇视频中是否有什么东西导致了这个问题。结果发现最后有模拟静态。
我非常确信这就是问题所在，因为我使用其他软件来修剪模拟静态，而 ffmpeg 处理得很好。但是，我尝试自动从带有时间戳的视频中提取场景，而 ffmpeg 却没有任何错误地停止运行，这无济于事！
如果有任何价值的话，我也附加了日志文件！
built with gcc 9.2.1 (GCC) 20200122
configuration: --enable-gpl --enable-version3 --enable-sdl2 --enable-fontconfig --enable-gnutls --enable-iconv --enable-libass --enable-libdav1d --enable-libbluray --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopus --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libtheora --enable-libtwolame --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libzimg --enable-lzma --enable-zlib --enable-gmp --enable-libvidstab --enable-libvorbis --enable-libvo-amrwbenc --enable-libmysofa --enable-libspeex --enable-libxvid --enable-libaom --enable-libmfx --enable-amf --enable-ffnvcodec --enable-cuvid --enable-d3d11va --enable-nvenc --enable-nvdec --enable-dxva2 --enable-avisynth --enable-libopenmpt
libavutil 56. 31.100 / 56. 31.100
libavcodec 58. 54.100 / 58. 54.100
libavformat 58. 29.100 / 58. 29.100
libavdevice 58. 8.100 / 58. 8.100
libavfilter 7. 57.100 / 7. 57.100
libswscale 5. 5.100 / 5. 5.100
libswresample 3. 5.100 / 3. 5.100
libpostproc 55. 5.100 / 55. 5.100
Input #0, rawvideo, from 'pipe:':
Duration: N/A, start: 0.000000, bitrate: 497166 kb/s
Stream #0:0: Video: rawvideo (RGB[24] / 0x18424752), rgb24, 720x480, 497166 kb/s, 59.94 tbr, 59.94 tbn, 59.94 tbc
Input #1, mp3, from 'convertedTEMP_MPY_wvf_snd.mp3':
Metadata:
encoder : Lavf58.29.100
Duration: 00:07:33.80, start: 0.025057, bitrate: 128 kb/s
Stream #1:0: Audio: mp3, 44100 Hz, stereo, fltp, 128 kb/s
Metadata:
encoder : Lavc58.54
Stream mapping:
Stream #0:0 -> #0:0 (rawvideo (native) -> h264 (libx264))
Stream #1:0 -> #0:1 (copy)
[libx264 @ 000001aea287cd80] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2
[libx264 @ 000001aea287cd80] profile High, level 3.1, 4:2:0, 8-bit
[libx264 @ 000001aea287cd80] 264 - core 159 - H.264/MPEG-4 AVC codec - Copyleft 2003-2019 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=12 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
Output #0, mp4, to 'converted.mp4':
Metadata:
encoder : Lavf58.29.100
Stream #0:0: Video: h264 (libx264) (avc1 / 0x31637661), yuv420p, 720x480, q=-1--1, 59.94 fps, 11988 tbn, 59.94 tbc
Metadata:
encoder : Lavc58.54.100 libx264
Side data:
cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
Stream #0:1: Audio: mp3 (mp4a / 0x6134706D), 44100 Hz, stereo, fltp, 128 kb/s
Metadata:
encoder : Lavc58.54
[rawvideo @ 000001aea287c400] Thread message queue blocking; consider raising the thread_queue_size option (current value: 8)
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...
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frame=24330 fps=161 q=31.0 size= 221696kB time=00:06:44.92 bitrate=4485.1kbits/s speed=2.68x
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frame=24330 fps=160 q=31.0 size= 221696kB time=00:06:44.92 bitrate=4485.1kbits/s speed=2.66x
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frame=24330 fps=159 q=31.0 size= 221696kB time=00:06:44.92 bitrate=4485.1kbits/s speed=2.64x
frame=24330 fps=158 q=31.0 size= 221696kB time=00:06:44.92 bitrate=4485.1kbits/s speed=2.63x
frame=24330 fps=158 q=31.0 size= 221696kB time=00:06:44.92 bitrate=4485.1kbits/s speed=2.62x
frame=24330 fps=157 q=31.0 size= 221696kB time=00:06:44.92 bitrate=4485.1kbits/s speed=2.61x
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答案1
忙碌了一周后终于有时间重新回顾一下。
事实证明，这与模拟静态无关。或者可能只是部分原因。我能够顺利转换另一个包含静态的视频。这让我意识到视频中存在一些独特的损坏。
我能够使用 shotcut 进行转换，很好，然后我尝试了 stock ffmpeg。Stock ffmpeg 显示了很多错误，但能够完成该过程，最后的视频看起来很棒。我不知道 pymovie 在做什么，但我喜欢直接使用 ffmpeg。
不过有趣的是，我使用 ChatGPT 3.5 快速找出了 ffmpeg 命令，并使用该subprocess命令开发了一个脚本来运行 ffmpeg。这很简单，我本来可以查阅的，但我尝试使用 ChatGPT 3.5，它成功了。最终我学会了如何subprocess.check_decode()监控输出，现在我有了一个我认为非常强大的脚本。我甚至使用硬件加速在我的 GPU 上处理视频。我还意识到我似乎不需要转换视频。我能够根据时间直接提取我想要的剪辑。对结果非常满意！
import time
start_time = '2:33'
end_time = '2:51'
input_video = "video.MOV"
output_video = "output.mp4"
#Standard video conversion
ffmpeg_cmd = [
'ffmpeg',
'-i', input_video,
'-c:v', 'h264_nvenc',
'-c:a', 'aac',
'output.mp4', '-y', '']
#Extracting clip
ffmpeg_cmd_getclip = [
'ffmpeg',
'-i', input_video,
'-ss', start_time,
'-to', end_time,
output_video,'-y']
#Extracting clip with GPU
ffmpeg_cmd_getclipGPU = [
'ffmpeg',
'-hwaccel', 'cuvid',
'-c:v', 'h264_cuvid',
'-i', input_video,
'-ss', start_time,
'-to', end_time,
'-c:v', 'h264_nvenc',
output_video, '-y']
print('Starting!')
start = time.time()
output = subprocess.check_output(ffmpeg_cmd_getclip)
output = output.decode()
end = time.time()
run1 = end - start
start = time.time()
output = subprocess.check_output(ffmpeg_cmd_getclipGPU)
output = output.decode()
end = time.time()
run2 = end - start
#Seems as if the outut decoding runs a little while after the process has completed. Small delay to make sure things are cleaned up.
time.sleep(2)
print('Completed!')
print(run1, run2)```