keras-applications | Reference implementations of popular deep learning models | Machine Learning library

 by   keras-team Python Version: 1.0.8 License: Non-SPDX

kandi X-RAY | keras-applications Summary

kandi X-RAY | keras-applications Summary

keras-applications is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Keras applications. keras-applications has no bugs, it has no vulnerabilities, it has build file available and it has medium support. However keras-applications has a Non-SPDX License. You can install using 'pip install keras-applications' or download it from GitHub, PyPI.

Keras Applications is the applications module of the Keras deep learning library. It provides model definitions and pre-trained weights for a number of popular archictures, such as VGG16, ResNet50, Xception, MobileNet, and more. Read the documentation at:
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              keras-applications has a medium active ecosystem.
              It has 1969 star(s) with 926 fork(s). There are 79 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 61 open issues and 103 have been closed. On average issues are closed in 98 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of keras-applications is 1.0.8

            kandi-Quality Quality

              keras-applications has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              keras-applications 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.

            kandi-Reuse Reuse

              keras-applications 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 are not available. Examples and code snippets are available.
              keras-applications saves you 1495 person hours of effort in developing the same functionality from scratch.
              It has 3333 lines of code, 98 functions and 19 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed keras-applications and discovered the below as its top functions. This is intended to give you an instant insight into keras-applications implemented functionality, and help decide if they suit your requirements.
            • R Conception V3
            • Return input shape
            • Extract submodules from kwargs
            • 1D convolution layer
            • Train a keras model
            • Compute the correct padding
            • Divide value into divisible by divisor
            • Inverse res block
            • Constructs a ResNet152 V2 v2
            • A Mobile NetworkV3
            • Construct a ResNet101 tensor
            • ResNet101v2
            • ResNet tensorflow
            • EfficientNet B5 model
            • ResNet50 v2
            • Constructs a ResNet - 152 convolutional network
            • Efficient NetworkB6
            • Efficient Network B7
            • Creates a NASNet large network
            • ResNet50
            • Xception
            • Create a NeuralNet
            • VGG19
            • Inception ResNet v2
            • VGG16
            • NASnet network
            Get all kandi verified functions for this library.

            keras-applications Key Features

            No Key Features are available at this moment for keras-applications.

            keras-applications Examples and Code Snippets

            Why is my model giving poor accuracy when the data is loaded using tf.data?
            Pythondot img1Lines of Code : 6dot img1License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            def read_images(X, y):
                X = tf.io.read_file(X)
                X = tf.image.decode_jpeg(X, channels = 3)
                X = tf.image.resize(X, [IMG_HEIGHT, IMG_WIDTH]) #/255.0
                return (X, y)
            
            Shape Error while Fine Tuning MobileNet On A Custom Data Set
            Pythondot img2Lines of Code : 12dot img2License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            mobile = tf.keras.applications.mobilenet.MobileNet()
            
              if include_top:
                x = layers.GlobalAveragePooling2D(keepdims=True)(x)
            
            mobile = keras.applications.mobilenet.MobileNet()
            x = mobile.l
            copy iconCopy
            class StreoModel(tf.keras.Model):
            
              def __init__(self):
                super(StreoModel, self).__init__()
                self.resnet_v2 = tf.keras.applications.resnet_v2.ResNet50V2(include_top=False, weights=None, classes=4, input_shape=(720, 540, 2))
                self
            copy iconCopy
               # Save out figure if desired, then close
               # Assuming not using a blocking draw/show call.
               fig.savefig('myfig.png')
               plt.close() #  Object oriented: fig.close()
            
            No module named 'matplotlib' after conda installation
            Pythondot img5Lines of Code : 2dot img5License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            conda activate -n tf_plot
            
            mamba fails to create env
            Pythondot img6Lines of Code : 24dot img6License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            name: nbdev
            channels:
              - fastai
              - defaults
              - conda-forge
            dependencies:
              - _r-mutex
              - _tflow_select
              - absl-py
              - alabaster
            
            name: nbdev
            channels:
              - fastai
              - defaults
              - conda-forge
            dependencies:
              - p
            copy iconCopy
            unet.fit((x_train, y_train))
            
            unet.fit(x_train, y_train)
            
            module 'tensorflow._api.v1.compat.v2' has no attribute '__internal__' google colab error
            Pythondot img8Lines of Code : 6dot img8License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            !pip3 uninstall keras-nightly
            !pip3 uninstall -y tensorflow
            !pip3 install keras==2.1.6
            !pip3 install tensorflow==1.15.0
            !pip3 install h5py==2.10.0
            
            module 'tensorflow._api.v1.compat.v2' has no attribute '__internal__' google colab error
            Pythondot img9Lines of Code : 4dot img9License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            !pip install tensorflow==1.13.0
            
            %tensorflow_version 1.x
            
            Image Net Preprocessing using torch transforms
            Pythondot img10Lines of Code : 10dot img10License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            transforms.Compose([transforms.RandomChoice([transforms.Resize(256), 
                                                         transforms.Resize(480)]),
                                transforms.RandomCrop(224)
                                ])
            
            tra

            Community Discussions

            QUESTION

            UnsatisfiableError on importing environment pywin32==300 (Requested package -> Available versions)
            Asked 2021-Dec-03 at 14:58

            Good day

            I am getting an error while importing my environment:

            ...

            ANSWER

            Answered 2021-Dec-03 at 09:22

            Build tags in you environment.yml are quite strict requirements to satisfy and most often not needed. In your case, changing the yml file to

            Source https://stackoverflow.com/questions/70209921

            QUESTION

            No module named 'matplotlib' after conda installation
            Asked 2021-Nov-22 at 07:31

            I created a new environment and added it to jupyter like this:

            ...

            ANSWER

            Answered 2021-Nov-22 at 07:31

            Going by the SO answer here the virtual environment named tf_plot needs to be activated first before import. i.e,

            Source https://stackoverflow.com/questions/70062009

            QUESTION

            How to manually load pretrained model if I can't download it using TensorFlow
            Asked 2021-Nov-13 at 06:08

            I am trying to download the VGG19 model via TensorFlow

            ...

            ANSWER

            Answered 2021-Nov-13 at 06:08

            You're using load_model on weights, instead of a model. You need to have a defined model first, then load the weights.

            Source https://stackoverflow.com/questions/69947553

            QUESTION

            Python: matplotlib.pyplot.show() is not showing the plot
            Asked 2021-Nov-03 at 13:35
            import matplotlib.pyplot as plt
            
            plt.plot([1,2,3])
            plt.show()
            
            input("Press enter to continue...")
            
            ...

            ANSWER

            Answered 2021-Nov-03 at 13:32

            As of late, conda and matplotlib have been having issues.

            You can try to downgrade freetype from 2.11.0 to 2.10.4 by doing conda install freetype=2.10.4

            Source https://stackoverflow.com/questions/69825742

            QUESTION

            mamba fails to create env
            Asked 2021-Aug-04 at 05:11

            I had just installed Anaconda from anaconda.com. The installation proceeded smoothly. After that, I was trying to create a new environment from this environment.yml file. (nbdev.yml)

            ...

            ANSWER

            Answered 2021-Aug-04 at 05:11

            QUESTION

            AttributeError: could not import keras and segmentation models
            Asked 2021-Jul-02 at 05:33

            I am trying to import segmentation models and keras and i am getting an attribute error, i am using tensor flow version 2.5.0

            ...

            ANSWER

            Answered 2021-Jul-02 at 05:33

            I have solved my issue by adding tf.compat.v1.enable_eager_execution() to import and it works fine

            Source https://stackoverflow.com/questions/68209795

            QUESTION

            Keras logits and labels must have the same first dimension, got logits shape [10240,151] and labels shape [1], sparse_categorical_crossentropy
            Asked 2021-Jun-10 at 13:36

            I'm trying to create a Unet for semantic segmentation.. I've been following this repo that has the code from this article. I'm using the scene parsing 150 dataset instead of the one used in the article. My data is not one-hot encoded so I'm trying to use sparse_categorical_crossentropy for loss.

            This is the shape of my data. x is RGB images, y is 1 channel annotations of categories (151 categories). Yes, I'm using just 10 samples of each, just for testing, this will be changed when I can actually get it to start training.

            ...

            ANSWER

            Answered 2021-Jun-10 at 13:36

            QUESTION

            module 'tensorflow._api.v1.compat.v2' has no attribute '__internal__' google colab error
            Asked 2021-May-29 at 01:40

            I am running a tensorflow model on google colab. Today, I got this error:

            ...

            ANSWER

            Answered 2021-May-27 at 03:19

            Try downgrading Python to 3.6 using this link. You need to re-install the packages you previously used.

            Source https://stackoverflow.com/questions/67694895

            QUESTION

            plaidml-setup is not recognized on Windows, even after successful installation
            Asked 2021-May-14 at 23:43

            I followed all the steps as on the doccumentation from VertexAI but after installing plaidml-keras, when I try to run setup, its throws an error.

            ...

            ANSWER

            Answered 2021-May-14 at 23:43

            So, I didn't find a solution to the original problem, even after multiple reinstalls. Finally, I uninstalled Python, and installed Anaconda3. Installing plaidml through the Anaconda prompt worked. Sadly my GPU is too old to even be recognized. AMD Radeon HD 7870.

            But hey, if any future reader of this post has the same issue, try Anaconda prompt. Its highly probable you have it installed anyways. Happy Coding.

            Source https://stackoverflow.com/questions/67166024

            QUESTION

            Issue of installing tensorflow 1.15 with python 3.7.7
            Asked 2021-May-05 at 12:50

            I am trying to install tensorflow 1.15, and it's installed well. When I run again pip install tensorflow==1.15 it shows me the below screen:

            ...

            ANSWER

            Answered 2021-May-05 at 12:31

            The problem is that tensorflow is well installed in your machine but in which environment? for pycharm to see tensorflow, tensorflow must be installed in the same environment that pycharm uses to execute code. But if for example your pycharm is configured to execute codes in a virtual environment and tensorflow is installed in anaconda, there is has no way it works. So the simple solution that you can do is to change the environment of pycham to the environment where tensorflow is installed

            Source https://stackoverflow.com/questions/67400463

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

            Vulnerabilities

            No vulnerabilities reported

            Install keras-applications

            You can install using 'pip install keras-applications' or download it from GitHub, PyPI.
            You can use keras-applications 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:

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            Install
          • PyPI

            pip install Keras-Applications

          • CLONE
          • HTTPS

            https://github.com/keras-team/keras-applications.git

          • CLI

            gh repo clone keras-team/keras-applications

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            git@github.com:keras-team/keras-applications.git

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