imageio-ffmpeg | FFMPEG wrapper for Python | Video Utils library

 by   imageio Python Version: 0.5.1 License: BSD-2-Clause

kandi X-RAY | imageio-ffmpeg Summary

kandi X-RAY | imageio-ffmpeg Summary

imageio-ffmpeg is a Python library typically used in Video, Video Utils applications. imageio-ffmpeg has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install imageio-ffmpeg' or download it from GitHub, PyPI.

FFMPEG wrapper for Python.
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            kandi-support Support

              imageio-ffmpeg has a low active ecosystem.
              It has 167 star(s) with 42 fork(s). There are 7 watchers for this library.
              There were 2 major release(s) in the last 12 months.
              There are 14 open issues and 33 have been closed. On average issues are closed in 157 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of imageio-ffmpeg is 0.5.1

            kandi-Quality Quality

              imageio-ffmpeg has 0 bugs and 23 code smells.

            kandi-Security Security

              imageio-ffmpeg has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              imageio-ffmpeg code analysis shows 0 unresolved vulnerabilities.
              There are 1 security hotspots that need review.

            kandi-License License

              imageio-ffmpeg is licensed under the BSD-2-Clause License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              imageio-ffmpeg releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              It has 1337 lines of code, 69 functions and 13 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed imageio-ffmpeg and discovered the below as its top functions. This is intended to give you an instant insight into imageio-ffmpeg implemented functionality, and help decide if they suit your requirements.
            • 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
            Get all kandi verified functions for this library.

            imageio-ffmpeg Key Features

            No Key Features are available at this moment for imageio-ffmpeg.

            imageio-ffmpeg Examples and Code Snippets

            No Code Snippets are available at this moment for imageio-ffmpeg.

            Community Discussions

            QUESTION

            Why does Anaconda install pytorch cpuonly when I install cuda?
            Asked 2022-Mar-23 at 20:46

            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 14:52

            I 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

            Source https://stackoverflow.com/questions/71162459

            QUESTION

            How to unit test graphics with python3, CircleCI and Mayavi
            Asked 2022-Feb-09 at 18:09

            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 18:09

            I missed a dependency, qt5-default. I ended up having these lines for Mayavi running on Docker/CircleCi:

            Source https://stackoverflow.com/questions/71038161

            QUESTION

            Pyinstaller Codec Error on Executable When Using No Console And No Debug Option
            Asked 2021-Dec-25 at 04:58

            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 04:58

            I 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.

            Source https://stackoverflow.com/questions/70317426

            QUESTION

            How to make conda use its own gcc version?
            Asked 2021-Dec-12 at 16:12

            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 16:12

            Just 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.

            Source https://stackoverflow.com/questions/70316504

            QUESTION

            pycharm error happening at random time: Process finished with exit code 134 (interrupted by signal 6: SIGABRT)
            Asked 2021-Nov-30 at 20:26

            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 20:26

            Looks 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:

            1. 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.

            2. Do not use the debugger with interactive plots.

            3. Set "Variables Loading Policy" to "Synchronously" in Debugger as suggested by a PyCharm dev in the linked issue.

            4. Enable "Scientific mode" in Pycharm.

            5. More esoteric workarounds such as closing your figures within the code before drawing the second one. Example, after plotting the first figure:

            Source https://stackoverflow.com/questions/70063350

            QUESTION

            In conda environment, cannot import installed package
            Asked 2021-Nov-23 at 14:19

            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 14:19

            FFMPEG might be perplexing at times. When using Python, you need perform the following steps to ensure proper installation:

            Source https://stackoverflow.com/questions/70078641

            QUESTION

            RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. GPU not detected by pytorch
            Asked 2021-Mar-21 at 16:24

            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 10:44

            From the list of libraries, it looks like you've installed CPU only version of the Pytorch.

            Source https://stackoverflow.com/questions/66711799

            QUESTION

            CalledProcessError: Command '['convert', '--version']' returned non-zero exit status 1
            Asked 2020-Sep-24 at 21:01

            ANSWER

            Answered 2020-Sep-24 at 21:01

            matplotlib.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:

            Source https://stackoverflow.com/questions/64053840

            QUESTION

            Why is conda's remove not symmetric with conda's install?
            Asked 2020-Jan-19 at 20:51

            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 20:51
            Asymmetry

            In 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.

            Alternatives

            If 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:

            Source https://stackoverflow.com/questions/59773372

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install imageio-ffmpeg

            This library works with any version of Python 3.4+ (including Pypy). There are no further dependencies. The wheels on Pypi include the ffmpeg executable for all common platforms (Windows 7+, Linux kernel 2.6.32+, OSX 10.9+). Install using:. (On Linux you may want to first pip install -U pip, since pip 19 is needed to detect the manylinux2010 wheels.).

            Support

            To report a security vulnerability, please use the Tidelift security contact. Tidelift will coordinate the fix and disclosure.
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            Install
          • PyPI

            pip install imageio-ffmpeg

          • CLONE
          • HTTPS

            https://github.com/imageio/imageio-ffmpeg.git

          • CLI

            gh repo clone imageio/imageio-ffmpeg

          • sshUrl

            git@github.com:imageio/imageio-ffmpeg.git

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