mmdetect | Intel ME Manufacturing Mode Detection Tools | Computer Vision library

by ptresearch Python Version: Current License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(5)Vulnerabilities Install Support

kandi X-RAY | mmdetect Summary

mmdetect is a Python library typically used in Artificial Intelligence, Computer Vision applications. mmdetect has no bugs, it has no vulnerabilities and it has low support. However mmdetect build file is not available and it has a Non-SPDX License. You can download it from GitHub.

Intel ME Manufacturing Mode Detection Tools.

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Quality

Security

License

Reuse

Support

mmdetect has a low active ecosystem.

It has 99 star(s) with 21 fork(s). There are 9 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 3 have been closed. On average issues are closed in 38 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of mmdetect is current.

Quality

mmdetect has 0 bugs and 0 code smells.

Security

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

mmdetect code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

mmdetect 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

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

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

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

mmdetect saves you 39 person hours of effort in developing the same functionality from scratch.

It has 104 lines of code, 7 functions and 1 files.

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

Top functions reviewed by kandi - BETA

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

Install the PCI utility
Downloads the PCI tool
Try to find the PCI extension
Get the extended register status
Checks if the platform is supported
Parse arguments

Get all kandi verified functions for this library.

mmdetect Key Features

No Key Features are available at this moment for mmdetect.

mmdetect Examples and Code Snippets

No Code Snippets are available at this moment for mmdetect.

Community Discussions

Trending Discussions on mmdetect

faster_rcnn_r50 pretrained converted to ONNX hosted in Triton model server

Wrong "-1 background" annotations loaded from Custom COCO Dataset using Mmdetection

Passing arguments to shell command

How to append all items in the list?

fatal error: cuda_runtime_api.h: No such file or directory when trying to use cuda in docker

QUESTION

faster_rcnn_r50 pretrained converted to ONNX hosted in Triton model server

Asked 2021-Dec-03 at 21:00

I went through the mmdetection documentation to convert a pytorch model to onnx here link

All installations are correct and i'm using onnxruntime==1.8.1, custom operators for ONNX Runtime MMCV_WITH_OPS.

I'm using the configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py for faster rcnn link and using R-5-FPN pretrained model link

I used this to convert the pretrained model to onnx and successfully saved an onnx file named fasterrcnn.onnx

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ANSWER

Answered 2021-Dec-03 at 21:00

Looking at the conversion script seems like dets is a combo of boxes plus score

Source https://stackoverflow.com/questions/70192619

QUESTION

Wrong "-1 background" annotations loaded from Custom COCO Dataset using Mmdetection

Asked 2021-Sep-23 at 15:47

Introduction

I'm working using Mmdetection to train a Deformable DETR model using a custom COCO Dataset. Meaning a Custom Dataset using the COCO format of annotations. The dataset uses the same images as the COCO with different "toy" annotations for a "playground" experiment and the annotation file was created using the packages pycocotools and json exclusively.

I have made five variations of this playground dataset: 2 datasets with three classes (classes 1, 2, and 3), 1 dataset with six classes (classes 1 to 6) and 2 datasets with 7 classes (classes 1 to 7).

The Problem

Now, after creating the dataset in mmdetection using mmdet.datasets.build_dataset, I used the following code to check if everything was OK:

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ANSWER

Answered 2021-Sep-23 at 15:47

There was a mismatch between the classes names in the annotation file and the classes names in the mmdetection config object. Correcting those solved the problem.

Source https://stackoverflow.com/questions/69293877

QUESTION

Passing arguments to shell command

Asked 2021-Jul-25 at 15:27

I have a shell script that I am executing inside a python script and i want to pass two variables to the script as arguments.I used $ sign but it's not working. this is the shell script:

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ANSWER

Answered 2021-Jul-25 at 15:27

I guess string interpolation can be used to pass your Python variables to the args of the call command. For example, if you use fstring, the code will look like this:

Source https://stackoverflow.com/questions/68519873

QUESTION

How to append all items in the list?

Asked 2021-Jun-06 at 04:10

I need to write image_ids in a file which exist in mmdetection class . i tried to get the image_id by img_meta['ori_filename'] and implement this code to write all of the ids

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ANSWER

Answered 2021-Jun-06 at 04:10

I assume you have a variable image_metas where all the images are stored.

Source https://stackoverflow.com/questions/67855631

QUESTION

fatal error: cuda_runtime_api.h: No such file or directory when trying to use cuda in docker

Asked 2020-Oct-22 at 14:06

I am trying to build a docker image for a python script that I would like to deploy. This is the first time I am using docker so I'm probably doing something wrong but I have no clue what.

My System:

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ANSWER

Answered 2020-Oct-22 at 13:20

EDIT: this answer just tells you how to verify what's happening in your docker image. Unfortunately I'm unable to figure out why it is happening.

How to check it?

At each step of the docker build, you can see the various layers being generated. You can use that ID to create a temporary image to check what's happening. e.g.

Source https://stackoverflow.com/questions/64481487

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

Vulnerabilities

No vulnerabilities reported

Install mmdetect

You can download it from GitHub.
You can use mmdetect 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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