YAD2K | YAD2K : Yet Another Darknet 2 Keras | Machine Learning library

by allanzelener Python Version: Current License: Non-SPDX

X-Ray Key Features Code Snippets(3)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | YAD2K Summary

YAD2K is a Python library typically used in Artificial Intelligence, Machine Learning, Keras applications. YAD2K has no bugs, it has no vulnerabilities and it has medium support. However YAD2K build file is not available and it has a Non-SPDX License. You can download it from GitHub.

YAD2K: Yet Another Darknet 2 Keras

Support

Quality

Security

License

Reuse

Support

YAD2K has a medium active ecosystem.

It has 2668 star(s) with 885 fork(s). There are 92 watchers for this library.

It had no major release in the last 6 months.

There are 114 open issues and 61 have been closed. On average issues are closed in 85 days. There are 12 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of YAD2K is current.

Quality

YAD2K has 0 bugs and 0 code smells.

Security

YAD2K has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

YAD2K code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

YAD2K 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.

Reuse

YAD2K releases are not available. You will need to build from source code and install.

YAD2K has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

YAD2K saves you 561 person hours of effort in developing the same functionality from scratch.

It has 1311 lines of code, 43 functions and 13 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed YAD2K and discovered the below as its top functions. This is intended to give you an instant insight into YAD2K implemented functionality, and help decide if they suit your requirements.

Create the topology model
Yolo body
A 2D convolutional convolutional convolution layer
Darknet factory
Draws a trained stage
Wrapper around yaml
Draws boxes
Wrapper for yolo_loss
Yolo head
Train the model
Create a topless model
Draw boxes
Return a list of colors for each class
Process a single image
Computes the detection mask for the given boxes
Get the path to the image
Darknet network
Returns a list of class names
Run yolo
Add images to dataset
Read anchors from file
Yolo model
Generate a stream of unique config sections
Get a list of image ids
Wrapper for yolo evaluation
Preprocessing function
Preprocess true boxes
Get the path to an annotation file

Get all kandi verified functions for this library.

YAD2K Key Features

No Key Features are available at this moment for YAD2K.

YAD2K Examples and Code Snippets

实现步骤

Python

Lines of Code : 104

License : No License

Copy

python ./yad2k.py ./yolov2-tiny-voc.cfg ./yolov2-tiny-voc.weights ./model/yolov2-tiny-voc.h5

#把给定视频转换为图片
def preprocess_video(src_path):
    cap = cv2.VideoCapture(src_path)
    num_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
    fps = int(cap.g

YOLO V2 with TensorFlow 2.0

Jupyter Notebook

Lines of Code : 11

License : Permissive (MIT)

Copy

	LABELS           = ('sugarbeet', 'weed')

	IMAGE_H, IMAGE_W = 512, 512
	GRID_H,  GRID_W  = 16, 16 # GRID size = IMAGE size / 32

	TRAIN_BATCH_SIZE = 10
	VAL_BATCH_SIZE   = 10

	# Train and validation directories

	train_image_folder = 'data/train/im

YAD2K: Yet Another Darknet 2 Keras,Requirements,Installation

Python

Lines of Code : 10

License : Non-SPDX (NOASSERTION)

Copy

git clone https://github.com/allanzelener/yad2k.git
cd yad2k

# [Option 1] To replicate the conda environment:
conda env create -f environment.yml
source activate yad2k
# [Option 2] Install everything globaly.
pip install numpy h5py pillow
pip instal

Community Discussions

Trending Discussions on YAD2K

'tensorflow' has no attribute 'space_to_depth' error with tensorflow 2.3 when running yad2k to generate model h5 file

How to fix AttributeError: module 'tensorflow' has no attribute 'space_to_depth'

QUESTION

'tensorflow' has no attribute 'space_to_depth' error with tensorflow 2.3 when running yad2k to generate model h5 file

Asked 2020-Sep-20 at 20:18

I am trying to generate YOLOv2 model yolo.h5 so that I can load this pre-trained model. I am trying to port Andrew Ng coursera Yolo assignment ( which runs in tensorflow 1.x) to tensorflow 2.3.

I was able to cleanly port it thanks to tensorflow uprade (https://www.tensorflow.org/guide/upgrade), But little did I realize that I cannot download the yolo.h5 file ( either its get corrupted or the download times out) and therefore I thought I should build one and I followed instructions from https://github.com/JudasDie/deeplearning.ai/issues/2. It looked pretty straight forward as I cloned YAD2k repo and downloaded both the yolo.weights and yolo.cfg. I ran the following the command as per the instructions:

python yad2k.py yolo.cfg yolo.weights model_data/yolo.h5

But I got the following error:-

...

ANSWER

Answered 2020-Sep-20 at 20:18

The above problem goes away when you upgrade all of your code under yad2k repo ( particularly yad2k.py and python files under models folder to tensorflow 2.x. The beautiful upgrade utility provided by tensorflow does the magic for you by replacing the original call to the compatible tf.compat.v1.space_to_depth(input=x, block_size=...)

Therefore for those who are planning to do the hard job of downgrading their tensorflow and keras, I would recommend them to try the tensorflow upgrade. This saves a lot of time.

This takes care of my model h5 file creation. My bad - I didn't think about it when I asking the question.

Source https://stackoverflow.com/questions/63964143

QUESTION

How to fix AttributeError: module 'tensorflow' has no attribute 'space_to_depth'

Asked 2020-May-18 at 04:01

I have python 3.7.4 installed and tensorflow version 2.2.0 installed on my Windows 10 x64. I am trying to execute this:

...

ANSWER

Answered 2020-May-18 at 04:01

Seem to be conflict tensorflow version and keras version. Downgrade tensorflow to 1.14.0 and keras to 2.3.1 fix the problem

Source https://stackoverflow.com/questions/61850232

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

Vulnerabilities

No vulnerabilities reported

Install YAD2K

See ./yad2k.py --help and ./test_yolo.py --help for more options.
Download Darknet model cfg and weights from the official YOLO website.
Convert the Darknet YOLO_v2 model to a Keras model.
Test the converted model on the small test set in images/.

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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