UCF-101_video_classification | Classify UCF101 videos using one frame at a time with a CNN | Machine Learning library
kandi X-RAY | UCF-101_video_classification Summary
kandi X-RAY | UCF-101_video_classification Summary
UCF-101_video_classification is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras, Neural Network applications. UCF-101_video_classification has no bugs, it has no vulnerabilities and it has low support. However UCF-101_video_classification build file is not available. You can download it from GitHub.
Classify UCF101 videos using one frame at a time with a CNN(InceptionV3)
Classify UCF101 videos using one frame at a time with a CNN(InceptionV3)
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Quality
Security
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Support
UCF-101_video_classification has a low active ecosystem.
It has 186 star(s) with 57 fork(s). There are 5 watchers for this library.
It had no major release in the last 6 months.
There are 12 open issues and 4 have been closed. On average issues are closed in 1 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of UCF-101_video_classification is current.
Quality
UCF-101_video_classification has 0 bugs and 3 code smells.
Security
UCF-101_video_classification has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
UCF-101_video_classification code analysis shows 0 unresolved vulnerabilities.
There are 2 security hotspots that need review.
License
UCF-101_video_classification does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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UCF-101_video_classification releases are not available. You will need to build from source code and install.
UCF-101_video_classification has no build file. You will be need to create the build yourself to build the component from source.
UCF-101_video_classification saves you 139 person hours of effort in developing the same functionality from scratch.
It has 348 lines of code, 29 functions and 7 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed UCF-101_video_classification and discovered the below as its top functions. This is intended to give you an instant insight into UCF-101_video_classification implemented functionality, and help decide if they suit your requirements.
- Generate a frame generator
- Split train and test data
- Extract a sequence from a file
- Get images for a given sample
- Rescales a list
- Process an image
- Get one - hot row of a given class
- Extract video files
- Split a video path into a trainor
- Check if video already extracted
- Returns the number of frames for a video
- Move files
- Get all the sequences in the training dataset
- Return a generator of the images
- Get train test lists
- Create a pre - trained model
- Firesune inception layer
- Train a model
Get all kandi verified functions for this library.
UCF-101_video_classification Key Features
No Key Features are available at this moment for UCF-101_video_classification.
UCF-101_video_classification Examples and Code Snippets
No Code Snippets are available at this moment for UCF-101_video_classification.
Community Discussions
Trending Discussions on UCF-101_video_classification
QUESTION
Can anyone tell me why I get IndexError: list index out of range?
Asked 2020-Feb-18 at 08:58
Trying to replicate this repository: https://github.com/sujiongming/UCF-101_video_classification. I get the following error when I run the CNN_train_UCF101.py file.
...ANSWER
Answered 2020-Feb-18 at 08:58You have a blank line in the CSV file, which is resulting in an empty list at the end of self.data.
You should skip empty items.
QUESTION
how do I resolve IndexError: list index out of range?
Asked 2020-Feb-17 at 20:41
I am trying to replicate this repository: https://github.com/sujiongming/UCF-101_video_classification. I get the following error when I run the 2_extract_files.py file.
...ANSWER
Answered 2020-Feb-17 at 20:41It is recommended to use just os.path.split(video_path) and os.path.splitext() and work your way through, it safer and also more portable:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install UCF-101_video_classification
You can download it from GitHub.
You can use UCF-101_video_classification like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use UCF-101_video_classification like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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