CenterNet | Object detection , 3D detection | Computer Vision library

by xingyizhou Python Version: Current License: MIT

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

kandi X-RAY | CenterNet Summary

CenterNet is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning, Tensorflow applications. CenterNet has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.

Object detection, 3D detection, and pose estimation using center point detection:. Objects as Points, Xingyi Zhou, Dequan Wang, Philipp Krähenbühl, arXiv technical report (arXiv 1904.07850).

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Quality

Security

License

Reuse

Support

CenterNet has a medium active ecosystem.

It has 6889 star(s) with 1913 fork(s). There are 112 watchers for this library.

It had no major release in the last 6 months.

There are 428 open issues and 559 have been closed. On average issues are closed in 77 days. There are 9 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of CenterNet is current.

Quality

CenterNet has 0 bugs and 0 code smells.

Security

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

CenterNet code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

CenterNet is licensed under the MIT License. This license is Permissive.

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

Reuse

CenterNet 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, examples and code snippets are available.

CenterNet saves you 3948 person hours of effort in developing the same functionality from scratch.

It has 8404 lines of code, 479 functions and 80 files.

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

Top functions reviewed by kandi - BETA

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

Decode heatmap
Left aggregation function
Right aggregation function
Compute nms of a heatmap
Counts the number of anchors for each image
Generate thumbnail anchors
Convert a coco box to a bbox
Evaluate recall
Returns the intersection between two bounding boxes
Example demo
Create a convolution layer
Debugging function
Debugger for debugging
Wrapper for parallel_apply
Debugger function
Count the number of images in the given split
Process the model
Locate the CUDA
Load a trained model
Counts the number of images in the given split
Count the number of images in the image
Convert a coco box to bbox
Update the information of the dataset
Parse arguments
Wrapper for agnex_decode
Runs ddd prediction
Forward computation

Get all kandi verified functions for this library.

CenterNet Key Features

No Key Features are available at this moment for CenterNet.

CenterNet Examples and Code Snippets

CenterNet with Unsupervised Domain Adaptation methods,Usage,Configuration

Python

Lines of Code : 122

License : Permissive (MIT)

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experiment: default # experiment name and also folder name (outputs/default) where logs a.s.o. are saved

# path to pretrained weights
# optimizer states are not restored
pretrained: /mnt/data/Projects/centernet-uda/weights/coco_dla_2x.pth

# path to

CenterNet with Unsupervised Domain Adaptation methods,Dataset

Python

Lines of Code : 43

License : Permissive (MIT)

Copy

  ...
  "images": [
    {
      "id": 1,
      "width": 1680,
      "height": 1680,
      "file_name": "Record_00600.jpg",
      "license": 0,
      "flickr_url": "",
      "coco_url": "",
      "date_captured": 0
    },
    ...

  {
      "id": 17,

预测步骤,b、使用自己训练的权重

Python

Lines of Code : 37

License : Permissive (MIT)

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_defaults = {
    #--------------------------------------------------------------------------#
    #   使用自己训练好的模型进行预测一定要修改model_path和classes_path！
    #   model_path指向logs文件夹下的权值文件，classes_path指向model_data下的txt
    #   如果出现shape不匹配，同时要注意训练时的model_pat

gluon-cv - demo center net

Python

Lines of Code : 12

License : Non-SPDX (Apache License 2.0)

Copy

"""11. Predict with pre-trained CenterNet models
================================================

This article shows how to play with pre-trained CenterNet models with only a few
lines of code.

First let's import some necessary libraries:
"""

from

Community Discussions

Trending Discussions on CenterNet

Tensorflow Object Detection API GPU memory issue

Accessing to Weights and Layers in Tensorflow Hub

Gtk-WARNING **: 13:51:34.650: cannot open display

Loading ResNet50 on RTX2070 - Out of Memory

QUESTION

Tensorflow Object Detection API GPU memory issue

Asked 2021-Mar-11 at 07:39

I'm currently trying to train a model based off the model detection zoo for object detection. Running the setup on the CPU works as expected but trying the same on my GPU results in the following error.

...

ANSWER

Answered 2021-Mar-11 at 07:39

I've done a complete reinstallation of every involving component. I might have done something different this time but I cannot say what. Atleast I'm now able to utilize the GPU for training.

Source https://stackoverflow.com/questions/66563512

QUESTION

Accessing to Weights and Layers in Tensorflow Hub

Asked 2021-Feb-17 at 07:44

When I try to get the model from tensorflow-hub resporitory. I can see it as a Saved Model format, but I cant get access to model architecture as well as weights store for each layer.

...

ANSWER

Answered 2021-Feb-16 at 08:48

With the CLI tool saved_model_cli provided by the package tensorflow-serving-api it's possible to inspect a saved model. In the first step I downloaded and cached the model:

Source https://stackoverflow.com/questions/66115204

QUESTION

Gtk-WARNING **: 13:51:34.650: cannot open display

Asked 2020-Aug-25 at 03:17

I am running a docker container for a CV Deep Learning project. Before running the docker container:

...

ANSWER

Answered 2020-Aug-25 at 03:17

Before running the container, the following steps are required:

Source https://stackoverflow.com/questions/63364094

QUESTION

Loading ResNet50 on RTX2070 - Out of Memory

Asked 2020-Jan-14 at 13:05

I'm trying to load ResNext50, and on top of it CenterNet, I'm able to do it with Google Colab or Kaggle's GPU. But,

Would love to know how much GPU Memory (VRAM) does this network need?
When using RTX 2070 with free 5.5GB VRAM left on it (out of 8GB), I'm not able to load it.

Batch size is 1, #of workers is 1, everything is set to minimum values. OS: Ubuntu 18.04 (Using PyTorch)

In TensorFlow, I know that I can restrict the amount of VRAM (which enables me to load and run networks although I don't have enough VRAM), but in PyTorch I didn't find this functionality yet.

Any ideas how to solve this?

...

ANSWER

Answered 2020-Jan-14 at 13:05

Using third party dependency

You could get size of model in bytes using third party library torchfunc (disclaimer I'm the author).

Source https://stackoverflow.com/questions/59728088

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

Vulnerabilities

No vulnerabilities reported

Install CenterNet

Please refer to INSTALL.md for installation instructions.

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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