DNN | A DNN learning project | Machine Learning library

 by   13952522076 Python Version: Current License: No License

kandi X-RAY | DNN Summary

kandi X-RAY | DNN Summary

DNN is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Deep Learning applications. DNN has no bugs, it has no vulnerabilities and it has low support. However DNN build file is not available. You can download it from GitHub.

This is a DNN Learning project from Xu Ma, Computer Science, Univerisity of North Texas. Here is a list for the papers I have read. Paper List More papers are made publicly avaiable at CV_papers Some details in DNN will be presented here: details.
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            kandi-support Support

              DNN has a low active ecosystem.
              It has 7 star(s) with 1 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              DNN has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of DNN is current.

            kandi-Quality Quality

              DNN has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              DNN does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              DNN releases are not available. You will need to build from source code and install.
              DNN has no build file. You will be need to create the build yourself to build the component from source.
              It has 9498 lines of code, 890 functions and 114 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed DNN and discovered the below as its top functions. This is intended to give you an instant insight into DNN implemented functionality, and help decide if they suit your requirements.
            • Generates an image for a given filter .
            • Calculate rpn rpn features .
            • Reads and parses the image files .
            • Calculate the II angle .
            • Augment image .
            • Generate a list of non - maximum suppression .
            • Calculate the thumbnail anchor point .
            • Convert rpn layer to ROI .
            • Compute the probability map for each bounding box .
            • Constructs a convolutional network .
            Get all kandi verified functions for this library.

            DNN Key Features

            No Key Features are available at this moment for DNN.

            DNN Examples and Code Snippets

            Generate shared embedding columns .
            pythondot img1Lines of Code : 181dot img1License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def shared_embedding_columns(categorical_columns,
                                         dimension,
                                         combiner='mean',
                                         initializer=None,
                                         shared_embedding_collection_name=None,  
            Embed dense_embedding_columns .
            pythondot img2Lines of Code : 172dot img2License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def shared_embedding_columns_v2(categorical_columns,
                                            dimension,
                                            combiner='mean',
                                            initializer=None,
                                            shared_embedding_collec  
            Create a cross - section cross section .
            pythondot img3Lines of Code : 125dot img3License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            def crossed_column(keys, hash_bucket_size, hash_key=None):
              """Returns a column for performing crosses of categorical features.
            
              Crossed features will be hashed according to `hash_bucket_size`. Conceptually,
              the transformation can be thought of   

            Community Discussions

            QUESTION

            ImportError: cannot import name 'dnn_logit_fn_builder' from partially initialized module 'tensorflow_estimator.python.estimator.canned.dnn'
            Asked 2022-Mar-06 at 17:25

            Using jupyter notebook in a conda env leads me to that error when importing tensorflow_hub:

            ...

            ANSWER

            Answered 2021-Oct-07 at 06:27

            Works with Tensorflow 2.6.0 with little change in the api name as tf.compat.v1.estimator.experimental.dnn_logit_fn_builder

            Source https://stackoverflow.com/questions/69339917

            QUESTION

            How to upload an Image File modified by OpenCV using FileSystemStorage in Django?
            Asked 2022-Feb-13 at 16:57

            I am taking an uploaded image from the user and then sending it to a YOLO model which then returns me an image.

            I want to store that returned image in my Local Directory and then display it on the user interface.

            This is the Code of views.py that takes in an image and sends it to the Yolo Model,

            ...

            ANSWER

            Answered 2022-Feb-13 at 16:57

            You can use the imwrite function of cv2 library to store your files in the local directory, i.e.,

            In your case, simply do this,

            Source https://stackoverflow.com/questions/71100904

            QUESTION

            Colab: (0) UNIMPLEMENTED: DNN library is not found
            Asked 2022-Feb-08 at 19:27

            I have pretrained model for object detection (Google Colab + TensorFlow) inside Google Colab and I run it two-three times per week for new images I have and everything was fine for the last year till this week. Now when I try to run model I have this message:

            ...

            ANSWER

            Answered 2022-Feb-07 at 09:19

            It happened the same to me last friday. I think it has something to do with Cuda instalation in Google Colab but I don't know exactly the reason

            Source https://stackoverflow.com/questions/71000120

            QUESTION

            How to use Intel oneAPI in right way?
            Asked 2022-Jan-11 at 15:16

            Today, I'm wondering what the difference between Conda in oneAPI and Conda in Anaconda is and how to use the oneAPI in the right way to get the maximum usage of the latest Intel Core gen 12.

            After installing oneAPI, they also contain conda. However, I cannot use this as a normal condition when:

            -It does not contain conda-build and several packages like normal conda in Anaconda.

            -Can not create as well as clone other environments from the "base" of Conda OneAPI. If I clone the "base" to the new one as conda create --name new_env --clone base and then activate the "new_env", I cannot use Conda anymore and it warns me like the conda does not exist. The warning is as below.

            ...

            ANSWER

            Answered 2022-Jan-04 at 05:55
            • Conda executable in one api does not support all the features supported by conda in anaconda.

            • Conda executable in one api can be used to download both intel optimized packages as well as anaconda packages.

            • Conda executable in one api gives performance improvement for intel optimized packages.

            • Since setvars is not sourced you are getting this warning

            Source https://stackoverflow.com/questions/70534207

            QUESTION

            How to use another model as a layer in current model which input has unknown shape
            Asked 2021-Dec-31 at 17:51

            Suppose I have a base model take two inputs and output single value:

            ...

            ANSWER

            Answered 2021-Dec-31 at 17:18

            Something like this should work -

            Source https://stackoverflow.com/questions/70540207

            QUESTION

            How to add a new user profile field to Dnn?
            Asked 2021-Nov-17 at 05:35

            I want to add a new profile field in the DNN portal to be displayed in the registration form. I could not find it inside the DNN portal menu.

            ...

            ANSWER

            Answered 2021-Nov-17 at 05:35

            in dnn7 go to this address : Admin -> Site Settings -> User Account Settings -> Profile Settings -> Add New Profile Property

            in dnn9 go to this address : Settings -> Site Settings -> Site Behavior -> User Profile -> Add Field

            Source https://stackoverflow.com/questions/69999357

            QUESTION

            Loading YOLO: invalid index to scalar variable
            Asked 2021-Nov-08 at 09:29

            Getting an error for IndexError: invalid index to scalar variable on the yolo_layers line.

            ...

            ANSWER

            Answered 2021-Nov-08 at 09:29

            It's may caused by the different versions of cv2. The version of cv2 module with CUDA support will give you a 2-D array when calling network.getUnconnectedOutLayers(). However, the version without CUDA support will give a 1-D array.

            You may try to take the brackets out which closing the index 0.

            Source https://stackoverflow.com/questions/69834335

            QUESTION

            PyTorch to onnx and use with opencv-dnn?
            Asked 2021-Oct-12 at 08:16

            I want to run yolov5 with opencv dnn in C++, for this, I have converted PyTorch model to onnx, from this link But that onnx is not working with opencv dnn module. Anyhelp would be appreciated.

            ...

            ANSWER

            Answered 2021-Oct-12 at 08:16

            I have followed below links and have successfully run yolov5 with C++

            Link-1

            Link-2

            Source https://stackoverflow.com/questions/68771371

            QUESTION

            Is there a way to output DNN pages to the page via a 2sxc app using C# Razor template?
            Asked 2021-Oct-05 at 10:03

            I want to set up a 2sxc app that handles the DNN menu instead of using DDR Menu. So the template would grab the pages as on the Pages part of DNN and render them on the page just like a DDR Menu template would. However, I would be able to template my own structure.

            The reason why I want to do this is so that I can make a maximally editable header that includes a mega menu with content other than typical pages in DNN. Is this even possible? If so, how? What would the C# Razor code be?

            ...

            ANSWER

            Answered 2021-Oct-05 at 10:03

            all is possible, the only question is how complex it will be.

            One option is to use the DNN APIs to get the data. You could look at the DDR code to find out how it's done

            Another option is to use a Visual Query with the Pages data source. https://docs.2sxc.org/api/dot-net/ToSic.Sxc.DataSources.Pages.html which was added ca. 2sxc 12. So far it's only used in the page-picker in the edit-dialog, so it may not be feature complete. But I would personally start there.

            Source https://stackoverflow.com/questions/69421795

            QUESTION

            Python OpenCV with Cuda not working after successful build
            Asked 2021-Sep-19 at 21:52

            I am on Windows 10, using Python 3.9.6 and my cv2 version is 4.4.0. I built OpenCV with Cuda successfully and after calling cv2.cuda.getCudaEnabledDeviceCount(), it returns 1 as expected. The following lines also work fine.

            ...

            ANSWER

            Answered 2021-Sep-19 at 21:52

            "Sources say" the MX130 has a Maxwell core, not a Pascal core. Maxwell is the predecessor of Pascal.

            Hence, you only have CUDA compute capability 5.0.

            You should check that with an appropriate tool such as GPU-Z that does its best to query the hardware instead of going by specs.

            Sources:

            Source https://stackoverflow.com/questions/69246441

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

            Vulnerabilities

            No vulnerabilities reported

            Install DNN

            You can download it from GitHub.
            You can use DNN 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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