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Resizing AVIF images with transparency with FFmpeg [closed]
4 octobre 2024, par CalebmerI'm trying to resize an image with transparency with FFmpeg, however the output looks to only be a resized version of the alpha layer.


When I try to do a noop transform of the AVIF image with an alpha layer :


ffmpeg -i input.avif output.avif


output.avifappears to be the alpha layer with black representing alpha 0 and white representing alpha 1.

ffprobe input.avifgives me :

ffprobe version 7.0.2 Copyright (c) 2007-2024 the FFmpeg developers
 built with Apple clang version 15.0.0 (clang-1500.3.9.4)
 configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/7.0.2 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libharfbuzz --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libssh --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon
 libavutil 59. 8.100 / 59. 8.100
 libavcodec 61. 3.100 / 61. 3.100
 libavformat 61. 1.100 / 61. 1.100
 libavdevice 61. 1.100 / 61. 1.100
 libavfilter 10. 1.100 / 10. 1.100
 libswscale 8. 1.100 / 8. 1.100
 libswresample 5. 1.100 / 5. 1.100
 libpostproc 58. 1.100 / 58. 1.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'input.avif':
 Metadata:
 major_brand : avif
 minor_version : 0
 compatible_brands: avifmif1miaf
 Duration: N/A, start: 0.000000, bitrate: N/A
 Stream #0:0[0x1]: Video: av1 (libdav1d) (Main) (av01 / 0x31307661), gray(pc), 336x252 [SAR 1:1 DAR 4:3], 1 fps, 1 tbr, 1 tbn (default)
 Stream #0:1[0x2]: Video: av1 (libdav1d) (High) (av01 / 0x31307661), yuv444p(pc, smpte170m/bt709/iec61966-2-1), 336x252 [SAR 1:1 DAR 4:3], 1 fps, 1 tbr, 1 tbn


Seeing there are two streams (the first stream being
gray(pc), probably the alpha layer) I next tried :

ffmpeg -i input.avif -map 0:v:1 output.avif


To see the second stream and it gave me the image without any alpha channel. Transparent pixels were black.


Ultimately I want to resize the AVIF file with
ffmpeg -i input.avif -vf "scale=iw/2:-1" output.avifbut that appears to only resize the greyscale alpha channel. Furthermore, this will be part of a script that operates on some AVIF files without an alpha channel and some AVIF files with an alpha channel and I don't know which files have an alpha channel ahead of time.ffmpeg -i input.avif -vf "scale=iw/2:-1" output.avifworks for files without an alpha channel.

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What is last click attribution ? A beginner’s guide
10 mars 2024, par ErinImagine you just finished a successful marketing campaign. You reached new highs in campaign revenue. Your conversion was higher than ever. And you did it without dramatically increasing your marketing budget.
So, you start planning your next campaign with a bigger budget.
But what do you do ? Where do you invest the extra money ?
You used several marketing tactics and channels in the last campaign. To solve this problem, you need to track marketing attribution — where you give conversion credit to a channel (or channels) that acted as a touchpoint along the buyer’s journey.
One of the most popular attribution models is last click attribution.
In this article, we’ll break down what last click attribution is, its advantages and disadvantages, and examples of how you can use it to gain insights into the marketing strategies driving your growth.
What is last click attribution ?
Last click, or last interaction, is a marketing attribution model that seeks to give all credit for a conversion to the final touchpoint in the buyer’s journey. It assumes the customer’s last interaction with your brand (before the sale) was the most influential marketing channel for the conversion decision.
Example of last click attribution
Let’s say a woman named Jill stumbles across a fitness equipment website through an Instagram ad. She explores the website, looking at a few fitness bands and equipment, but she doesn’t buy anything.
A few days later, Jill was doing a workout but wished she had equipment to use.
So, she Googles the name of the company she checked out earlier to take a look at the fitness bands it offers. She’s not sure which one to get, but she signs up for a 10% discount by entering her email.
A few days later, she sees an ad on Facebook and visits the site but exits before purchasing.
The next day, Jill gets an email from the store stating that her discount code is expiring. She clicks on the link, plugs in the discount code, and buys a fitness band for $49.99.
Under the last click attribution model, the fitness company would attribute full credit for the sale to their email campaign while ignoring all other touchpoints (the Instagram ad, Jill’s organic Google search, and the Facebook ad).
3 advantages of last click attribution
Last click attribution is one of the most popular methods to credit a conversion. Here are the primary advantages of using it to measure your marketing efforts :
1. Easiest attribution method for beginners
If something’s too complicated, many people simply won’t touch it.
So, when you start diving into attribution, you might want to keep it simple. Fortunately, last click attribution is a wonderful method for beginner marketers to try out. And when you first begin tracking your marketing efforts, it’s one of the easiest methods to grasp.
2. It can have more impact on revenue
Attribution and conversions go hand in hand. But conversions aren’t just about making a sale or generating more revenue. We often need to track the conversions that take place before a sale.
This could include gaining a new follower on Instagram or capturing an email subscriber with a new lead magnet.
If you’re trying to attribute why someone converted into a follower or lead, you may want to ditch last click for something else.
But when you’re looking strictly at revenue-generating conversions, last click can be one of the most impactful methods for giving credit to a conversion.
3. It helps you understand bottom-of-funnel conversions
If SEO is your focus, chances are pretty good that you aren’t looking for a direct sale right out of the gate. You likely want to build your authority, inform and educate your audience, and then maybe turn them into a lead.
However, when your primary focus isn’t generating traffic or leads but turning your leads into customers, then you’re focused on the bottom of your sales funnel.
Last click can be helpful to use in bottom-of-funnel (BoFu) conversions since it often means following a paid ad or sales email that allows you to convert your warm audience member.
If you’re strictly after revenue, you may not need to pay as much attention to the person who reads your latest blog post. After they read the article, they may have seen a social media post. And then, maybe they saw your email with a discount to buy now — which converted them into a paying customer.
3 challenges of last click attribution
Last click attribution is a simple way to start analysing the channels that impact your conversions. But it’s not perfect.
Here are a few challenges of last click attribution you should keep in mind :
1. It ignores all other touchpoints
Last click attribution is a single-touch attribution model. This type of model declares that a single channel gets 100% of the credit for a sale.
But this can overlook impactful contributions from other channels.
Multi-touch attribution seeks to give credit to multiple channels for each conversion. This is a more holistic approach.
2. It fragments the customer journey
Most customers need a few touchpoints before they’ll make a purchase.
Maybe it’s reading a blog post via Google, checking out a social media post on Instagram, and receiving a nurture email.
If you look only at the last touchpoint before a sale, then you ignore the impact of the other channels. This leads to a fragmented customer journey.
Imagine this : You tell your marketing leaders that Facebook ads are responsible for your success because they were the last touch for 65% of conversions. So, you pour your entire budget into Facebook ads.
What happens ?
Your sales drop by 60% in one month. This happens because you ignored the traffic you were generating from SEO blog posts that led to that conversion — the nurturing that took place in email marketing.
3. Say goodbye to brand awareness marketing
Without a brand, you can’t have a sustainable business.
Some marketing activities, like brand awareness campaigns, are meant to fuel brand awareness to build a business that lasts for years.
But if you’re going to use last click attribution to measure the effectiveness of your marketing efforts, then you’re going to diminish the impact of brand awareness.
Your brand, as a whole, has the ability to generate multiples of your current revenue by simply reaching more people and creating unique brand experiences with new audiences.
Last click attribution can’t easily measure brand awareness activities, which means their importance is often ignored.
Last click attribution vs. other attribution models
Last click attribution is just one type of attribution model. Here are five other common marketing attribution models you might want to consider :
First interaction
We’ve already touched on last click interaction as a marketing attribution model. But one of the most common models does the opposite.
First interaction, or first touch, gives full credit to the first channel that brought a lead in.
First interaction is best used for top-of-funnel (ToFU) conversions, like user acquisition.
Last non-direct interaction
A similar model to last click attribution is one called last non-direct interaction. But one major difference is that it excludes all direct traffic from the calculation. Instead, it assigns full conversion credit to the channel that precedes it.
For instance, let’s say you see someone comes to your website via a Facebook ad but doesn’t purchase. Then one week later, they go directly to your website through a bookmark they saved and they complete a purchase. Instead of giving attribution to the direct traffic touchpoint (entering your site through a saved bookmark), you attribute the conversion to the previous channel.
In this case, the Facebook ad gets the credit.
Last non-direct attribution is best used for BoFu conversions.
Linear
Another common attribution model is called linear attribution. Here, you split the credit for a conversion equally across every single touchpoint.
This means if someone clicks on your blog post in Google, TikTok post, email, and a Facebook ad, then the credit for the conversion is equally split between each of these channels.
This model is helpful for looking at both BoFu and ToFu activities.
Time decay
Time decay is an attribution model that more accurately credits conversions across different touchpoints. This means the closer a channel is to a conversion, the more weight is given to it.
The time decay model assumes that the closer a channel is to a conversion, the greater that channel’s impact is on a sale.
Position based
Position-based, also called U-shaped attribution, is an interesting model that gives multiple channels credit for a conversion.
But it doesn’t give equal credit to channels or weighted credit to the channels closest to the conversion.
Instead, it gives the most credit to the first and last interactions.
In other words, it emphasises the conversion of someone to a lead and, eventually, a customer.
It gives the first and last interaction 40% of the credit for a conversion and then splits the remaining 20% across the other touchpoints in the customer journey.
If you’re ever unsure about which attribution model to use, with Matomo, you can compare them to determine the one that best aligns with your goals and accurately reflects conversion paths.
In the above screenshot from Matomo, you can see how last-click compares to first-click and linear models to understand their respective impacts on conversions.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Use Matomo to track last click attribution
If you want to improve your marketing, you need to start tracking your efforts. Without marketing attribution, you will never be certain which marketing activities are pushing your business forward.
Last click attribution is one of the most popular ways to get started with attribution since it, very simply, gives full credit to the last interaction for a conversion.
If you want to start tracking last click attribution (or any other previously mentioned attribution model), sign up for Matomo’s 21-day free trial today. No credit card required.
Try Matomo for Free
21 day free trial. No credit card required.
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ffmpeg seek calculating wrong byte range ?
17 décembre 2015, par user4455I’m running into an issue while trying to extract thumbnails from a movie file at a specific timestamp. Generally I’ve had no issues with this, but I’ve come across a set of movie files that are getting an error about the byte range requested (416 Requested Range Not Satisfiable).
The odd thing is that the server is correctly returning the content length in the partial content request, yet when it requests the movie file it requests a length that exceeds that.
This is a bit over my head, so I’m not sure what could be happening here. Any insight would be great.
The Command :
/usr/bin/ffmpeg -y -ss 1400 -i 'https://s3-us-west-2.amazonaws.com/my-bucket/mymoviefile.mp4' -qscale:v 2 -f image2 -vframes 1 -filter:v 'scale=192:108' -loglevel debug /data/www/storage/test.jpg 2>&1The Error :
[https @ 0x22e1e00] header='HTTP/1.1 416 Requested Range Not Satisfiable'
[https @ 0x22e1e00] http_code=416
[https @ 0x22e1e00] HTTP error 416 Requested Range Not SatisfiableSource File Size :
1776706045 bytesSource Content Duration :
2897.624271Partial Content Request :
[https @ 0x22e1e00] header='HTTP/1.1 206 Partial Content'
[https @ 0x22e1e00] http_code=206
[https @ 0x22e1e00] header='x-amz-id-2: 4J1pgHExIUA0GxIxSBmGJjrRqliHbsIjXeuGzVfTlaaoVXbyZI5FQNma8fGaifcovkXfxJev5yU='
[https @ 0x22e1e00] header='x-amz-request-id: 78B3BDBB0356EF40'
[https @ 0x22e1e00] header='Date: Wed, 16 Dec 2015 23:51:29 GMT'
[https @ 0x22e1e00] header='x-amz-meta-content-length: 2898'
[https @ 0x22e1e00] header='x-amz-meta-cb-modifiedtime: Tue, 15 Dec 2015 17:59:51 GMT'
[https @ 0x22e1e00] header='Last-Modified: Wed, 16 Dec 2015 23:44:59 GMT'
[https @ 0x22e1e00] header='ETag: "6341a8022630667a8070a83575e542e7-27"'
[https @ 0x22e1e00] header='Accept-Ranges: bytes'
[https @ 0x22e1e00] header='Content-Range: bytes 0-1776706044/1776706045'
[https @ 0x22e1e00] header='Content-Type: video/mp4'
[https @ 0x22e1e00] header='Content-Length: 1776706045'
[https @ 0x22e1e00] header='Server: AmazonS3'
[https @ 0x22e1e00] header='Connection: close'FFmpeg Request :
request: GET /my-bucket/mymoviefile.mp4 HTTP/1.1
User-Agent: Lavf/56.25.101
Accept: */*
Range: bytes=1781732960-
Connection: close
Host: s3-us-west-2.amazonaws.com
Icy-MetaData: 1Entire Log :
# /usr/bin/ffmpeg -y -ss 1400 -i 'https://s3-us-west-2.amazonaws.com/my-bucket/mymoviefile.mp4' -qscale:v 2 -f image2 -vframes 1 -filter:v 'scale=192:108' -loglevel debug /data/www/storage/test.jpg 2>&1
ffmpeg version 2.6.4 Copyright (c) 2000-2015 the FFmpeg developers
built with gcc 4.9.2 (Debian 4.9.2-10)
configuration: --prefix=/usr --extra-cflags='-g -O2 -fstack-protector-strong -Wformat -Werror=format-security ' --extra-ldflags='-Wl,-z,relro' --cc='ccache cc' --enable-shared --enable-libmp3lame --enable-gpl --enable-nonfree --enable-libvorbis --enable-pthreads --enable-libfaac --enable-libxvid --enable-postproc --enable-x11grab --enable-libgsm --enable-libtheora --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libx264 --enable-libspeex --enable-nonfree --disable-stripping --enable-libvpx --enable-libschroedinger --disable-encoder=libschroedinger --enable-version3 --enable-libopenjpeg --enable-librtmp --enable-avfilter --enable-libfreetype --enable-libvo-aacenc --disable-decoder=amrnb --enable-libvo-amrwbenc --enable-libaacplus --libdir=/usr/lib/x86_64-linux-gnu --disable-vda --enable-libbluray --enable-libcdio --enable-gnutls --enable-frei0r --enable-openssl --enable-libass --enable-libopus --enable-fontconfig --enable-libpulse --disable-mips32r2 --disable-mipsdspr1 --disable-mipsdspr2 --enable-libvidstab --enable-libzvbi --enable-avresample --disable-htmlpages --disable-podpages --enable-libutvideo --enable-libfdk-aac --enable-libx265 --enable-libiec61883 --enable-vaapi --enable-libdc1394 --disable-altivec --shlibdir=/usr/lib/x86_64-linux-gnu
libavutil 54. 20.100 / 54. 20.100
libavcodec 56. 26.100 / 56. 26.100
libavformat 56. 25.101 / 56. 25.101
libavdevice 56. 4.100 / 56. 4.100
libavfilter 5. 11.102 / 5. 11.102
libavresample 2. 1. 0 / 2. 1. 0
libswscale 3. 1.101 / 3. 1.101
libswresample 1. 1.100 / 1. 1.100
libpostproc 53. 3.100 / 53. 3.100
Splitting the commandline.
Reading option '-y' ... matched as option 'y' (overwrite output files) with argument '1'.
Reading option '-ss' ... matched as option 'ss' (set the start time offset) with argument '1400'.
Reading option '-i' ... matched as input file with argument 'https://s3-us-west-2.amazonaws.com/my-bucket/mymoviefile.mp4'.
Reading option '-qscale:v' ... matched as option 'qscale' (use fixed quality scale (VBR)) with argument '2'.
Reading option '-f' ... matched as option 'f' (force format) with argument 'image2'.
Reading option '-vframes' ... matched as option 'vframes' (set the number of video frames to output) with argument '1'.
Reading option '-filter:v' ... matched as option 'filter' (set stream filtergraph) with argument 'scale=192:108'.
Reading option '-loglevel' ... matched as option 'loglevel' (set logging level) with argument 'debug'.
Reading option '/data/www/storage/test.jpg' ... matched as output file.
Finished splitting the commandline.
Parsing a group of options: global .
Applying option y (overwrite output files) with argument 1.
Applying option loglevel (set logging level) with argument debug.
Successfully parsed a group of options.
Parsing a group of options: input file https://s3-us-west-2.amazonaws.com/my-bucket/mymoviefile.mp4.
Applying option ss (set the start time offset) with argument 1400.
Successfully parsed a group of options.
Opening an input file: https://s3-us-west-2.amazonaws.com/my-bucket/mymoviefile.mp4.
[https @ 0x22e1e00] request: GET /my-bucket/mymoviefile.mp4 HTTP/1.1
User-Agent: Lavf/56.25.101
Accept: */*
Range: bytes=0-
Connection: close
Host: s3-us-west-2.amazonaws.com
Icy-MetaData: 1
[https @ 0x22e1e00] header='HTTP/1.1 206 Partial Content'
[https @ 0x22e1e00] http_code=206
[https @ 0x22e1e00] header='x-amz-id-2: 4J1pgHExIUA0GxIxSBmGJjrRqliHbsIjXeuGzVfTlaaoVXbyZI5FQNma8fGaifcovkXfxJev5yU='
[https @ 0x22e1e00] header='x-amz-request-id: 78B3BDBB0356EF40'
[https @ 0x22e1e00] header='Date: Wed, 16 Dec 2015 23:51:29 GMT'
[https @ 0x22e1e00] header='x-amz-meta-content-length: 2898'
[https @ 0x22e1e00] header='x-amz-meta-cb-modifiedtime: Tue, 15 Dec 2015 17:59:51 GMT'
[https @ 0x22e1e00] header='Last-Modified: Wed, 16 Dec 2015 23:44:59 GMT'
[https @ 0x22e1e00] header='ETag: "6341a8022630667a8070a83575e542e7-27"'
[https @ 0x22e1e00] header='Accept-Ranges: bytes'
[https @ 0x22e1e00] header='Content-Range: bytes 0-1776706044/1776706045'
[https @ 0x22e1e00] header='Content-Type: video/mp4'
[https @ 0x22e1e00] header='Content-Length: 1776706045'
[https @ 0x22e1e00] header='Server: AmazonS3'
[https @ 0x22e1e00] header='Connection: close'
[https @ 0x22e1e00] header=''
[mov,mp4,m4a,3gp,3g2,mj2 @ 0x22e1740] Format mov,mp4,m4a,3gp,3g2,mj2 probed with size=2048 and score=100
[mov,mp4,m4a,3gp,3g2,mj2 @ 0x22e1740] ISO: File Type Major Brand: mp42
[mov,mp4,m4a,3gp,3g2,mj2 @ 0x22e1740] Before avformat_find_stream_info() pos: 1647960 bytes read:1652200 seeks:0
[h264 @ 0x22e92c0] no picture
[mov,mp4,m4a,3gp,3g2,mj2 @ 0x22e1740] All info found
[mov,mp4,m4a,3gp,3g2,mj2 @ 0x22e1740] After avformat_find_stream_info() pos: 1862326 bytes read:1878504 seeks:0 frames:16
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'https://s3-us-west-2.amazonaws.com/my-bucket/mymoviefile.mp4':
Metadata:
major_brand : mp42
minor_version : 1
compatible_brands: isommp41avc1
creation_time : 2015-11-18 02:34:41
Duration: 00:48:17.70, start: 0.000000, bitrate: 4905 kb/s
Stream #0:0(und), 15, 1/2997: Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv, left), 1920x1080 (1920x1088) [SAR 1:1 DAR 16:9], 1001/60000, 9994 kb/s, 29.97 fps, 29.97 tbr, 2997 tbn, 59.94 tbc (default)
Metadata:
creation_time : 2015-11-18 02:34:41
handler_name : ?Apple Video Media Handler
Stream #0:1(und), 1, 1/48000: Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 192 kb/s (default)
Metadata:
creation_time : 2015-11-18 02:34:41
handler_name : ?Apple Sound Media Handler
Successfully opened the file.
Parsing a group of options: output file /data/www/storage/test.jpg.
Applying option qscale:v (use fixed quality scale (VBR)) with argument 2.
Applying option f (force format) with argument image2.
Applying option vframes (set the number of video frames to output) with argument 1.
Applying option filter:v (set stream filtergraph) with argument scale=192:108.
Successfully parsed a group of options.
Opening an output file: /data/www/storage/test.jpg.
Successfully opened the file.
detected 2 logical cores
[Parsed_scale_0 @ 0x22cd4c0] Setting 'w' to value '192'
[Parsed_scale_0 @ 0x22cd4c0] Setting 'h' to value '108'
[Parsed_scale_0 @ 0x22cd4c0] Setting 'flags' to value '0x4'
[Parsed_scale_0 @ 0x22cd4c0] w:192 h:108 flags:'0x4' interl:0
[graph 0 input from stream 0:0 @ 0x22ccfe0] Setting 'video_size' to value '1920x1080'
[graph 0 input from stream 0:0 @ 0x22ccfe0] Setting 'pix_fmt' to value '0'
[graph 0 input from stream 0:0 @ 0x22ccfe0] Setting 'time_base' to value '1/2997'
[graph 0 input from stream 0:0 @ 0x22ccfe0] Setting 'pixel_aspect' to value '1/1'
[graph 0 input from stream 0:0 @ 0x22ccfe0] Setting 'sws_param' to value 'flags=2'
[graph 0 input from stream 0:0 @ 0x22ccfe0] Setting 'frame_rate' to value '2997/100'
[graph 0 input from stream 0:0 @ 0x22ccfe0] w:1920 h:1080 pixfmt:yuv420p tb:1/2997 fr:2997/100 sar:1/1 sws_param:flags=2
[format @ 0x2798640] compat: called with args=[yuvj420p|yuvj422p|yuvj444p]
[format @ 0x2798640] Setting 'pix_fmts' to value 'yuvj420p|yuvj422p|yuvj444p'
[AVFilterGraph @ 0x22cda60] query_formats: 5 queried, 4 merged, 0 already done, 0 delayed
[Parsed_scale_0 @ 0x22cd4c0] picking yuvj420p out of 3 ref:yuv420p alpha:0
[swscaler @ 0x22c3c80] deprecated pixel format used, make sure you did set range correctly
[Parsed_scale_0 @ 0x22cd4c0] w:1920 h:1080 fmt:yuv420p sar:1/1 -> w:192 h:108 fmt:yuvj420p sar:1/1 flags:0x4
[mjpeg @ 0x2854e20] intra_quant_bias = 96 inter_quant_bias = 0
[mjpeg @ 0x28716c0] intra_quant_bias = 96 inter_quant_bias = 0
[mjpeg @ 0x2795320] intra_quant_bias = 96 inter_quant_bias = 0
Output #0, image2, to '/data/www/storage/test.jpg':
Metadata:
major_brand : mp42
minor_version : 1
compatible_brands: isommp41avc1
encoder : Lavf56.25.101
Stream #0:0(und), 0, 100/2997: Video: mjpeg, yuvj420p(pc, left), 192x108 [SAR 1:1 DAR 16:9], 100/2997, q=2-31, 200 kb/s, 29.97 fps, 29.97 tbn, 29.97 tbc (default)
Metadata:
creation_time : 2015-11-18 02:34:41
handler_name : ?Apple Video Media Handler
encoder : Lavc56.26.100 mjpeg
Stream mapping:
Stream #0:0 -> #0:0 (h264 (native) -> mjpeg (native))
Press [q] to stop, [?] for help
[https @ 0x22e1e00] request: GET /my-bucket/mymoviefile.mp4 HTTP/1.1
User-Agent: Lavf/56.25.101
Accept: */*
Range: bytes=1781732960-
Connection: close
Host: s3-us-west-2.amazonaws.com
Icy-MetaData: 1
[https @ 0x22e1e00] header='HTTP/1.1 416 Requested Range Not Satisfiable'
[https @ 0x22e1e00] http_code=416
[https @ 0x22e1e00] HTTP error 416 Requested Range Not Satisfiable
[mov,mp4,m4a,3gp,3g2,mj2 @ 0x22e1740] stream 0, offset 0x6a331660: partial file
https://s3-us-west-2.amazonaws.com/my-bucket/mymoviefile.mp4: Invalid data found when processing input
[output stream 0:0 @ 0x22d7500] EOF on sink link output stream 0:0:default.
No more output streams to write to, finishing.
frame= 0 fps=0.0 q=0.0 Lsize=N/A time=00:00:00.00 bitrate=N/A
video:0kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: unknown
Input file #0 (https://s3-us-west-2.amazonaws.com/my-bucket/mymoviefile.mp4):
Input stream #0:0 (video): 0 packets read (0 bytes); 0 frames decoded;
Input stream #0:1 (audio): 0 packets read (0 bytes);
Total: 0 packets (0 bytes) demuxed
Output file #0 (/data/www/storage/test.jpg):
Output stream #0:0 (video): 0 frames encoded; 0 packets muxed (0 bytes);
Total: 0 packets (0 bytes) muxed
Output file is empty, nothing was encoded (check -ss / -t / -frames parameters if used)
0 frames successfully decoded, 0 decoding errors
[AVIOContext @ 0x27ab100] Statistics: 1878504 bytes read, 0 seeksFFprobe Result :
# /usr/bin/ffprobe -show_format -show_streams -i 'https://s3-us-west-2.amazonaws.com/my-bucket/mymoviefile.mp4'
ffprobe version 2.6.4 Copyright (c) 2007-2015 the FFmpeg developers
built with gcc 4.9.2 (Debian 4.9.2-10)
configuration: --prefix=/usr --extra-cflags='-g -O2 -fstack-protector-strong -Wformat -Werror=format-security ' --extra-ldflags='-Wl,-z,relro' --cc='ccache cc' --enable-shared --enable-libmp3lame --enable-gpl --enable-nonfree --enable-libvorbis --enable-pthreads --enable-libfaac --enable-libxvid --enable-postproc --enable-x11grab --enable-libgsm --enable-libtheora --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libx264 --enable-libspeex --enable-nonfree --disable-stripping --enable-libvpx --enable-libschroedinger --disable-encoder=libschroedinger --enable-version3 --enable-libopenjpeg --enable-librtmp --enable-avfilter --enable-libfreetype --enable-libvo-aacenc --disable-decoder=amrnb --enable-libvo-amrwbenc --enable-libaacplus --libdir=/usr/lib/x86_64-linux-gnu --disable-vda --enable-libbluray --enable-libcdio --enable-gnutls --enable-frei0r --enable-openssl --enable-libass --enable-libopus --enable-fontconfig --enable-libpulse --disable-mips32r2 --disable-mipsdspr1 --disable-mipsdspr2 --enable-libvidstab --enable-libzvbi --enable-avresample --disable-htmlpages --disable-podpages --enable-libutvideo --enable-libfdk-aac --enable-libx265 --enable-libiec61883 --enable-vaapi --enable-libdc1394 --disable-altivec --shlibdir=/usr/lib/x86_64-linux-gnu
libavutil 54. 20.100 / 54. 20.100
libavcodec 56. 26.100 / 56. 26.100
libavformat 56. 25.101 / 56. 25.101
libavdevice 56. 4.100 / 56. 4.100
libavfilter 5. 11.102 / 5. 11.102
libavresample 2. 1. 0 / 2. 1. 0
libswscale 3. 1.101 / 3. 1.101
libswresample 1. 1.100 / 1. 1.100
libpostproc 53. 3.100 / 53. 3.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'https://s3-us-west-2.amazonaws.com/my-bucket/mymoviefile.mp4':
Metadata:
major_brand : mp42
minor_version : 1
compatible_brands: isommp41avc1
creation_time : 2015-11-18 02:34:41
Duration: 00:48:17.70, start: 0.000000, bitrate: 4905 kb/s
Stream #0:0(und): Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv), 1920x1080 [SAR 1:1 DAR 16:9], 9994 kb/s, 29.97 fps, 29.97 tbr, 2997 tbn, 59.94 tbc (default)
Metadata:
creation_time : 2015-11-18 02:34:41
handler_name : ?Apple Video Media Handler
Stream #0:1(und): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 192 kb/s (default)
Metadata:
creation_time : 2015-11-18 02:34:41
handler_name : ?Apple Sound Media Handler
[STREAM]
index=0
codec_name=h264
codec_long_name=H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10
profile=High
codec_type=video
codec_time_base=1001/60000
codec_tag_string=avc1
codec_tag=0x31637661
width=1920
height=1080
has_b_frames=1
sample_aspect_ratio=1:1
display_aspect_ratio=16:9
pix_fmt=yuv420p
level=40
color_range=tv
color_space=unknown
color_transfer=unknown
color_primaries=unknown
chroma_location=left
timecode=N/A
refs=3
is_avc=1
nal_length_size=4
id=N/A
r_frame_rate=2997/100
avg_frame_rate=2997/100
time_base=1/2997
start_pts=0
start_time=0.000000
duration_ts=8684300
duration=2897.664331
bit_rate=9994429
max_bit_rate=N/A
bits_per_raw_sample=8
nb_frames=86843
nb_read_frames=N/A
nb_read_packets=N/A
DISPOSITION:default=1
DISPOSITION:dub=0
DISPOSITION:original=0
DISPOSITION:comment=0
DISPOSITION:lyrics=0
DISPOSITION:karaoke=0
DISPOSITION:forced=0
DISPOSITION:hearing_impaired=0
DISPOSITION:visual_impaired=0
DISPOSITION:clean_effects=0
DISPOSITION:attached_pic=0
TAG:creation_time=2015-11-18 02:34:41
TAG:language=und
TAG:handler_name=Apple Video Media Handler
[/STREAM]
[STREAM]
index=1
codec_name=aac
codec_long_name=AAC (Advanced Audio Coding)
profile=LC
codec_type=audio
codec_time_base=1/48000
codec_tag_string=mp4a
codec_tag=0x6134706d
sample_fmt=fltp
sample_rate=48000
channels=2
channel_layout=stereo
bits_per_sample=0
id=N/A
r_frame_rate=0/0
avg_frame_rate=0/0
time_base=1/48000
start_pts=0
start_time=0.000000
duration_ts=139085965
duration=2897.624271
bit_rate=192002
max_bit_rate=N/A
bits_per_raw_sample=N/A
nb_frames=135828
nb_read_frames=N/A
nb_read_packets=N/A
DISPOSITION:default=1
DISPOSITION:dub=0
DISPOSITION:original=0
DISPOSITION:comment=0
DISPOSITION:lyrics=0
DISPOSITION:karaoke=0
DISPOSITION:forced=0
DISPOSITION:hearing_impaired=0
DISPOSITION:visual_impaired=0
DISPOSITION:clean_effects=0
DISPOSITION:attached_pic=0
TAG:creation_time=2015-11-18 02:34:41
TAG:language=und
TAG:handler_name=Apple Sound Media Handler
[/STREAM]
[FORMAT]
filename=https://s3-us-west-2.amazonaws.com/my-bucket/mymoviefile.mp4
nb_streams=2
nb_programs=0
format_name=mov,mp4,m4a,3gp,3g2,mj2
format_long_name=QuickTime / MOV
start_time=0.000000
duration=2897.695000
size=1776706045
bit_rate=4905156
probe_score=100
TAG:major_brand=mp42
TAG:minor_version=1
TAG:compatible_brands=isommp41avc1
TAG:creation_time=2015-11-18 02:34:41
[/FORMAT]
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