object-detection-with-deep-learning | demonstrating use of convolution neural networks | Machine Learning library

by neerajdixit Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | object-detection-with-deep-learning Summary

object-detection-with-deep-learning is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras, OpenCV applications. object-detection-with-deep-learning has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However object-detection-with-deep-learning build file is not available. You can download it from GitHub.

demonstrating use of convolution neural networks to detect objects in a video

Support

Quality

Security

License

Reuse

Support

object-detection-with-deep-learning has a low active ecosystem.

It has 16 star(s) with 10 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 1024 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of object-detection-with-deep-learning is current.

Quality

object-detection-with-deep-learning has 0 bugs and 0 code smells.

Security

object-detection-with-deep-learning has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

object-detection-with-deep-learning code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

object-detection-with-deep-learning is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

object-detection-with-deep-learning releases are not available. You will need to build from source code and install.

object-detection-with-deep-learning has no build file. You will be need to create the build yourself to build the component from source.

object-detection-with-deep-learning saves you 73 person hours of effort in developing the same functionality from scratch.

It has 188 lines of code, 13 functions and 3 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of object-detection-with-deep-learning

Get all kandi verified functions for this library.

object-detection-with-deep-learning Key Features

No Key Features are available at this moment for object-detection-with-deep-learning.

object-detection-with-deep-learning Examples and Code Snippets

No Code Snippets are available at this moment for object-detection-with-deep-learning.

Community Discussions

Trending Discussions on object-detection-with-deep-learning

How to fix, "error: (-215) pbBlob.raw_data_type() == caffe::FLOAT16 in function blobFromProto" when running neural network in OpenCV

Neural network doesn't accept grayscale images

How create my own deep neural network model file?

How to use caffe convnet for object detection in video frames?

QUESTION

How to fix, "error: (-215) pbBlob.raw_data_type() == caffe::FLOAT16 in function blobFromProto" when running neural network in OpenCV

Asked 2019-Feb-11 at 17:13

I am currently trying to use Nvidia DIGITS to train a CNN on a custom dataset for object detection, and eventually I want to run that network on an Nvidia Jetson TX2. I followed the recommended instructions to download the DIGITS image from Docker, and I am able to successfully train a network with reasonable accuracy. But when I try to run my network in python using OpenCv, I get this error,

"error: (-215) pbBlob.raw_data_type() == caffe::FLOAT16 in function blobFromProto"

I have read in a few other threads that this is due to the fact that DIGITS stores its networks in a form that is incompatible with OpenCv's DNN functionality.

Before training my network, I have tried selecting the option in DIGITS that is supposed to make the network compatible with other software, however that doesn't seem to change the network at all, and I get the same error when running my python script. This is the script I run that creates the error (it comes from this tutorial https://www.pyimagesearch.com/2017/09/11/object-detection-with-deep-learning-and-opencv/)

...

ANSWER

Answered 2019-Feb-11 at 17:13

Harrison McIntyre, Thank you! This PR fixes it: https://github.com/opencv/opencv/pull/13800. Please note that there is a layer with type "ClusterDetections". It's not supported by OpenCV but you can implement it using custom layers mechanic (see a tutorial)

Source https://stackoverflow.com/questions/54536676

QUESTION

Neural network doesn't accept grayscale images

Asked 2018-Oct-26 at 14:38

I followed this tutorial: https://www.pyimagesearch.com/2017/09/11/object-detection-with-deep-learning-and-opencv/ I changed this part where I converted the image feed to grayscale before inserting it to the neural network

...

ANSWER

Answered 2018-Sep-05 at 15:12

The vast majority of these models require color, i.e. 3-channel images; by converting to grayscale you end up with a single-channel image, and the code crashes.

Let's have a quick look to confirm this; the script in the linked blog post is run as

Source https://stackoverflow.com/questions/52187913

QUESTION

How create my own deep neural network model file?

Asked 2018-May-22 at 10:22

I would like create my own deep neural network model. I would like use a python script to detect specific object.

It is possible to create my own caffemodel file (or other model file) using python or c++ with a set of pictures ?

Do you have any research or tracks ?

For example, I would like create simylary programm like this project, but with my own deep neural image network without image-net neural pictures network:

...

ANSWER

Answered 2018-May-22 at 10:22

I have found this project on GitHub. It explained how build own deep neural network model file with images.

Here is the link to the project

Source https://stackoverflow.com/questions/50413507

QUESTION

How to use caffe convnet for object detection in video frames?

Asked 2018-Mar-16 at 07:59

I have use codes from this link and sucessfully done the detection but the problem is it is only from webcam. I tried to modify the code so that it can read from file. the part I have modified is : I have written this

...

ANSWER

Answered 2018-Mar-16 at 07:59

I am unfamiliar with any of the code you are referencing, but the error is straightforward and similar errors hav been answered in other questions: You're trying to do a fancy method on a plain tuple object. Here's an example of this python concept using a common package, numpy for arrays:

Source https://stackoverflow.com/questions/49314500

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

Vulnerabilities

No vulnerabilities reported

Install object-detection-with-deep-learning

You can download it from GitHub.
You can use object-detection-with-deep-learning 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 .

Find more information at: