MDNet | Learning Multi-Domain Convolutional Neural Networks | Machine Learning library

by hyeonseobnam C++ Version: Current License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | MDNet Summary

MDNet is a C++ library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. MDNet has no bugs, it has no vulnerabilities and it has low support. However MDNet has a Non-SPDX License. You can download it from GitHub.

MDNet is the state-of-the-art visual tracker based on a CNN trained on a large set of tracking sequences, and the winner tracker of The VOT2015 Challenge. Detailed description of the system is provided by our paper. This software is implemented using MatConvNet and part of R-CNN.

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MDNet has a low active ecosystem.

It has 440 star(s) with 172 fork(s). There are 47 watchers for this library.

It had no major release in the last 6 months.

There are 11 open issues and 10 have been closed. On average issues are closed in 6 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of MDNet is current.

Quality

MDNet has no bugs reported.

Security

MDNet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

MDNet has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

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MDNet releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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MDNet Key Features

No Key Features are available at this moment for MDNet.

MDNet Examples and Code Snippets

No Code Snippets are available at this moment for MDNet.

Community Discussions

Trending Discussions on MDNet

Creating several weight tensors for each object in Multi-Object Tracking (MOT) using TensorFlow

Google Cloud - Downloading data from bucket to instance

QUESTION

Creating several weight tensors for each object in Multi-Object Tracking (MOT) using TensorFlow

Asked 2020-May-05 at 03:52

I am using TensorFlow V1.10.0 and developing a Multi-Object Tracker based on MDNet. I need to assign a separate weight matrix for each detected object for the fully connected layers in order to get different embedding for each object during online training. I am using this tf.map_fn in order to generate a higher-order weight tensor (n_objects, flattened layer, hidden_units),

'''

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ANSWER

Answered 2020-May-05 at 03:52

Here is a workaround, I was able to generate the multiple kernels outside the graph in a for loop and then giving it to the graph:

Source https://stackoverflow.com/questions/61190366

QUESTION

Google Cloud - Downloading data from bucket to instance

Asked 2019-Jul-13 at 10:39

I'm trying download the whole data from my bucket (tracking-data) on google cloud to my instance (instance-1) on Linux system.

I see some options here: https://cloud.google.com/compute/docs/instances/transfer-files#transfergcloud but I'm not sure there's a way there to download from bucket to instance.

I'm accessing my instance through my terminal and I've made a few tries with gsutil, but not successfully so far. Any idea how can I download the whole bucket into my instance? (preferably to put it in MDNet/data, I don't have such directory yet, but I probably should store the data there).

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ANSWER

Answered 2019-Jun-03 at 09:19

Use gsutil cp or gsutil rsync

https://cloud.google.com/storage/docs/gsutil/commands/cp

https://cloud.google.com/storage/docs/gsutil/commands/rsync

Source https://stackoverflow.com/questions/56424213

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

Vulnerabilities

No vulnerabilities reported

Install MDNet

Compile MatConvNet according to the installation guideline. An example script is provided in 'compile_matconvnet.m'.
Run 'setup_mdnet.m' to set the environment for running MDNet.

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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