#!/bin/sh -x
# $1 - input video file, e.g. video.mp4
# $2 - timestamp, e.g. 00:33
# $3 - output image file, e.g. output.jpg
ffmpeg -ss $2 -i $1 -vframes 1 -q:v 2 $3#!/bin/sh -x
# $1 - input file, e.g. input.mp4
ffmpeg -i "$1" -q:v 2 %06d.jpgffmpeg -f image2 -framerate 30 -i %06d.jpg -c:v libx264 out.mp4
Thanks for the scripts!
I built a web-based tool (Video To JPG) that also uses FFmpeg, but I added a sharpness detection feature on top of it.
Instead of manually sifting through hundreds of extracted frames to find a focused shot, the tool automatically calculates a clarity score and highlights the crispest images. It’s really helpful for filtering out motion blur. Hope it helps someone looking for the "best" frame rather than just "all" frames.
@ankurbhatia24 I see you want to understand the cause of the difference. I don't know the answer. In fact more questions come up in my head. Similar to you, I would start with color space of video vs images. Also I would have a rigorous way to measure luma difference, eg bits in files or some luma intensity definition. If you end up doing the analysis, I would be interested in the findings.