DeepFashion | Apparel detection using deep learning | Machine Learning library

by abhishekrana Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | DeepFashion Summary

DeepFashion is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Keras applications. DeepFashion has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Apparel detection using deep learning

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Quality

Security

License

Reuse

Support

DeepFashion has a low active ecosystem.

It has 222 star(s) with 73 fork(s). There are 14 watchers for this library.

It had no major release in the last 6 months.

There are 17 open issues and 4 have been closed. On average issues are closed in 33 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of DeepFashion is current.

Quality

DeepFashion has 0 bugs and 358 code smells.

Security

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

DeepFashion code analysis shows 0 unresolved vulnerabilities.

There are 13 security hotspots that need review.

License

DeepFashion 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

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

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

DeepFashion saves you 1431 person hours of effort in developing the same functionality from scratch.

It has 3198 lines of code, 99 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 DeepFashion and discovered the below as its top functions. This is intended to give you an instant insight into DeepFashion implemented functionality, and help decide if they suit your requirements.

Train the top model
Function to create a model function
Get the number of images in path
Get an optimizer
Generate dataset images
Performs selective search
Predict model for images
Preprocess image
Builds a VGG16 network
Create a convolutional model
Train the VGG16 model
Create a trained model
Saves the bottleneck to a file
Create a prediction model
Get bounding box from an image file
Create the dataset split structure
Load and prepare the training and validation generator
Create a directory structure
Crop bounding boxes
This method saves the Bottlebeck features
Predict image name from given image path
A prediction model
Display a bounding box of bboxes
Create a VGG16 model
Train a VGG16 network
Train the model
Performs selective search using selective search

Get all kandi verified functions for this library.

DeepFashion Key Features

No Key Features are available at this moment for DeepFashion.

DeepFashion Examples and Code Snippets

No Code Snippets are available at this moment for DeepFashion.

Community Discussions

Trending Discussions on DeepFashion

Is it normal to get ETA: 6:43:26 hours to complete the first epoch

QUESTION

Is it normal to get ETA: 6:43:26 hours to complete the first epoch

Asked 2021-Jan-28 at 03:00

I have crated the below vgg16 based CNN and I want to train it for 50 epochs. but it shows nearly 7 hours (ETA: 6:43:26) to complete the first epoch. could anyone please tell me is this normal with 209222 training images and 40000 validation images(DeepFashion dataset) ? or is this any issue with my steps_per_epoch? I use a HPC with 16 workers to train this model.

...

ANSWER

Answered 2021-Jan-27 at 19:29

if you are using VGG then you should rescale the values between -1 and +1 as

that is how it was trained so use

Source https://stackoverflow.com/questions/65924667

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

Vulnerabilities

No vulnerabilities reported

Install DeepFashion

You can download it from GitHub.
You can use DeepFashion 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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