[英]Reading a video directly into Numpy with PyAV (no iterations)
是否可以使用 PyAV 將視頻直接讀入 3D Numpy? 目前,我正在遍歷每一幀:
i = 0
container = av.open('myvideo.avi')
for frame in container.decode(video=0):
if i == 0: V = np.array(frame.to_ndarray(format='gray'))
else: V = np.dstack((V, np.array(frame.to_ndarray(format='gray'))))
i += 1
第一幀定義了一個2D Numpy數組(i=0); 每個后續幀 (i>0) 使用np.dstack
堆疊到第一個數組上。 理想情況下,我想一次將整個視頻讀入灰度幀的 3D Numpy 數組。
我找不到使用 PyAV 的解決方案,而是使用ffmpeg-python 。
ffmpeg-python是FFmpeg的 Pythonic 綁定,如PyAV 。
該代碼一次性將整個視頻讀入灰度幀的 3D Numpy 數組。
該解決方案執行以下步驟:
nx height x width
numpy 數組。這是代碼(請閱讀評論):
import ffmpeg
import numpy as np
from PIL import Image
in_filename = 'in.avi'
"""Build synthetic video, for testing begins:"""
# ffmpeg -y -r 10 -f lavfi -i testsrc=size=160x120:rate=1 -c:v libx264 -t 5 in.mp4
width, height = 160, 120
(
ffmpeg
.input('testsrc=size={}x{}:rate=1'.format(width, height), r=10, f='lavfi')
.output(in_filename, vcodec='libx264', t=5)
.overwrite_output()
.run()
)
"""Build synthetic video ends"""
# Use ffprobe to get video frames resolution
p = ffmpeg.probe(in_filename, select_streams='v');
width = p['streams'][0]['width']
height = p['streams'][0]['height']
# https://github.com/kkroening/ffmpeg-python/blob/master/examples/README.md
# Stream the entire video as one large array of bytes
in_bytes, _ = (
ffmpeg
.input(in_filename)
.video # Video only (no audio).
.output('pipe:', format='rawvideo', pix_fmt='gray') # Set the output format to raw video in 8 bit grayscale
.run(capture_stdout=True)
)
n_frames = len(in_bytes) // (height*width) # Compute the number of frames.
frames = np.frombuffer(in_bytes, np.uint8).reshape(n_frames, height, width) # Reshape buffer to array of n_frames frames (shape of each frame is (height, width)).
im = Image.fromarray(frames[0, :, :]) # Convert first frame to image object
im.show() # Display the image
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