imageio-ffmpeg | FFMPEG wrapper for Python | Video Utils library
kandi X-RAY | imageio-ffmpeg Summary
kandi X-RAY | imageio-ffmpeg Summary
FFMPEG wrapper for Python.
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Top functions reviewed by kandi - BETA
- Write frames to a file
- Returns True if the given executable is valid
- Return the platform name
- Return the ffmpeg executable
- Build image
- Clear all binaries in a directory
- Copy image files to target directory
- Remove build files
- Read frames from a video file
- Parse ffmpeg header
- Convert duration to seconds
- Return a string representation of the message
- Process the stream
- Return the first output line from a list of lines
- Auto - format options
- Run black
- Count the number of frames in a video
- Download the ffmpeg binary
- Get the version of ffmpeg
- Check format
imageio-ffmpeg Key Features
imageio-ffmpeg Examples and Code Snippets
Community Discussions
Trending Discussions on imageio-ffmpeg
QUESTION
I have created a Python 3.7 conda virtual environment and installed the following packages using this command:
conda install pytorch torchvision torchaudio cudatoolkit=11.3 matplotlib scipy opencv -c pytorch
They install fine, but then when I come to run my program I get the following error which suggests that a CUDA enabled device is not found:
...ANSWER
Answered 2022-Feb-18 at 14:52I beleive I had the following things wrong that prevented me from using Cuda. Despite having cuda installed the nvcc --version
command indicated that Cuda was not installed and so what I did was add it to the path using this answer.
Despite doing that and deleting my original conda environment and using the conda install pytorch torchvision torchaudio cudatoolkit=11.3 matplotlib scipy opencv -c pytorch
command again I still got False
when evaluating torch.cuda.is_available()
.
I then used this command conda install pytorch torchvision torchaudio cudatoolkit=10.2 matplotlib scipy opencv -c pytorch
changing cudatoolkit from verison 11.3 to version 10.2 and then it worked!
Now torch.cuda.is_available()
evaluates to True
Unfortunately, Cuda version 10.2 was incompatible with my RTX 3060 gpu (and I'm assuming it is not compatible with all RTX 3000 cards). Cuda version 11.0 was giving me errors and Cuda version 11.3 only installs the CPU only versions for some reason. Cuda version 11.1 worked perfectly though!
This is the command I used to get it to work in the end:
pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html
QUESTION
I wrote a bunch of visualization functions in my python3 library using Mayavi. I am not very familiar with this library, nor am I with testing visualizations using python.
Ideally, I would just like the visualization code to generate some graphics on disk, I don't care too much about popping up windows (although I'm not sure to understand if Mayavi can work properly without popping such windows).
Anyway, my code works on local, but when I push it on develop, CircleCI fails at running the tests with the following error:
...ANSWER
Answered 2022-Feb-09 at 18:09I missed a dependency, qt5-default
. I ended up having these lines for Mayavi running on Docker/CircleCi:
QUESTION
I'm making this program that uses imageio and imageio-ffmpeg, I want to turn it into an executable, so I entered the virtualenv environment I'm using for the project, generated the .spec with pyi-makespec
, and after trying for a long time, I got it working by adding this into the binaries
section of the .spec file:
ANSWER
Answered 2021-Dec-25 at 04:58I found out why it wasn't working, it's a bug in pyinstaller. It worked when I used the development version of pyinstaller. I ran pip install https://github.com/pyinstaller/pyinstaller/archive/develop.zip
in cmd, and ran the pyinstaller command again, and it worked.
QUESTION
I am trying to run the training of stylegan2-pytorch on a remote system. The remote system has gcc (9.3.0) installed on it. I'm using conda env that has the following installed (cudatoolkit=10.2, torch=1.5.0+, and ninja=1.8.2, gcc_linux-64=7.5.0). I encounter the following error:
...ANSWER
Answered 2021-Dec-12 at 16:12Just to share, not sure it will help you. However it shows that in standard conditions it is possible to use the conda
gcc
as described in the documentation instead of the system gcc
.
QUESTION
I am working with pycharm community on a tensorflow model with keras backend, sometimes this error appears in a random time, specially after I call pyplot and close the window:
...ANSWER
Answered 2021-Nov-30 at 20:26Looks like this is part of an actively tracked issue with Tkinter in PyCharm. You can find the reference on the Pycharm's developer's issue tracker. The issue is undiagnosed, but if looking at similar problems with Tk on StackOverflow, one can see that it's an issue with thread safety and/or multithreading.
All I can do is speculate as to the cause, which is not helpful, however, I can at least collate the suggested workarounds:
Switch to a different Matplotlib backend (See docs: What is a backend?). Such as Qt5, but you will need to make sure they are available in your environment.
This approach is the most promising as other backends are better able to deal with not being the main thread or are explicitly safe for multi-threading. It's also the simplest unless you have a really specific reason for preferring TkAgg.
Do not use the debugger with interactive plots.
Set "Variables Loading Policy" to "Synchronously" in Debugger as suggested by a PyCharm dev in the linked issue.
Enable "Scientific mode" in Pycharm.
More esoteric workarounds such as closing your figures within the code before drawing the second one. Example, after plotting the first figure:
QUESTION
Fresh installation of Anaconda on Ubuntu 20.04, created new env, installed moviepy
and ffmpeg
.
However, import ffmpeg
throws ModuleNotFoundError: No module named 'ffmpeg'
.
Why is that, and how can I fix it?
I have looked at a similar question (Installed a package with Anaconda, can't import in Python) and tried all the diagnostic / fix suggestions from that question:
...ANSWER
Answered 2021-Nov-23 at 14:19FFMPEG might be perplexing at times. When using Python, you need perform the following steps to ensure proper installation:
QUESTION
Having trouble with CUDA + Pytorch this is the error. I reinstalled CUDA and cudnn multiple times.
Conda env is detecting GPU but its giving errors with pytorch and certain cuda libraries. I tried with Cuda 10.1 and 10.0, and cudnn version 8 and 7.6.5, Added cuda to path and everything.
However anaconda is showing cuda tool kit 9.0 is installed, whilst I clearly installed 10.0, so I am not entirely sure what's the deal with that.
...ANSWER
Answered 2021-Mar-20 at 10:44From the list of libraries, it looks like you've installed CPU only version of the Pytorch.
QUESTION
Got the DLC-GPU.yaml from here: https://github.com/DeepLabCut/DeepLabCut/blob/master/conda-environments/DLC-GPU.yaml
...ANSWER
Answered 2020-Sep-24 at 21:01matplotlib.animation
requires ffmpeg
for saving movies and ImageMagick
for saving animated gifs.
See https://matplotlib.org/users/installing.html#install-requirements
Install them with your system package manager:
QUESTION
Why do seemingly simple/atomic conda
installs result in fairly complex uninstalls??
I recently tried the following conda install
ANSWER
Answered 2020-Jan-19 at 20:51In the installation part, Conda runs with an implicit --freeze-installed
flag, making it a simple install if all the packages are already there.
In the uninstallation, Conda doesn't have an equivalent simple uninstall. Instead, it will attempt to remove the requested package, plus any of its dependencies that were not explicitly installed or required by other packages. Unfortunately, it appears to accomplish this by trying to solve for an environment that consists of only previously requested packages for the env, and this means that all packages that have superseding versions are subject to being updated.
Your particular case appears to be exacerbated by the fact that you have installed from different channels (e.g., conda-forge), but never explicitly defined those channel priorities in your Conda configuration (globally or in the env). So, most of the changes involve switching back to the defaults channel version of packages.
AlternativesIf you're confident that nothing else has changed, then you could use the --force-remove
flag.
Another option, if this was the latest thing you've installed, is to try a revision roll-back, but this may also result in drastic changes. That is, check your revision history:
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