Auto-Annotate | Automatically annotate your entire image directory | Data Labeling library

by mdhmz1 Python Version: Current License: MIT

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

kandi X-RAY | Auto-Annotate Summary

Auto-Annotate is a Python library typically used in Artificial Intelligence, Data Labeling, Deep Learning applications. Auto-Annotate 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.

Auto-Annotate - Automatically annotate your entire image directory by a single command. As simple as saying - "Annotate all the street sign (label) in the autonomous car dataset (directory)" and BAM! DONE. Each and every image with a street sign in the diverse dataset directory containing images of all sorts which have a street sign are filtered and the segmentation annotation is performed in a single command. The Auto-Annotate tool provides auto annotation of segmentation masks for the objects in the images inside some directory based on the labels. Auto-Annotate is able to provide automated annotations for the labels defined in the COCO Dataset and also supports Custom Labels.

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Quality

Security

License

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Support

Auto-Annotate has a low active ecosystem.

It has 144 star(s) with 24 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 8 have been closed. On average issues are closed in 67 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Auto-Annotate is current.

Quality

Auto-Annotate has 0 bugs and 0 code smells.

Security

Auto-Annotate has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Auto-Annotate code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Auto-Annotate 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

Auto-Annotate 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.

It has 2681 lines of code, 137 functions and 8 files.

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

Top functions reviewed by kandi - BETA

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

Builds the graph
Compute backbone shapes
Generate anchors for the given image shape
Builds the FPN mask graph
Draw boxes
Return a list of N colors
Apply a mask to an image
Train the model
Compile the keras model
Detects mold images
Unold detections
Annotate images in a directory
Display the top masks of the image
Reduce a bounding box using bilinear interpolation
Generate pyramid anchors
Load weights from a file
Resize an image
Call the image pyramid
Draw random ROIs
Calls the RNN
Run the keras graph
Compute the confidence intervals for the given feature
Compiles the keras model
Displays the differences between the ground truth and ground truth
Calculate detection graph
Display the weight statistics for each layer
R Compute the suppression of a given threshold

Get all kandi verified functions for this library.

Auto-Annotate Key Features

No Key Features are available at this moment for Auto-Annotate.

Auto-Annotate Examples and Code Snippets

No Code Snippets are available at this moment for Auto-Annotate.

Community Discussions

Trending Discussions on Auto-Annotate

Creating mutually recursive local functions with metadata in Clojure

QUESTION

Creating mutually recursive local functions with metadata in Clojure

Asked 2019-Feb-08 at 10:43

Suppose I want to define two mutually recursive functions within a local scope. I can do this with letfn:

...

ANSWER

Answered 2019-Feb-08 at 07:30

I've found the following solution, in which letfn is used to define thunks that evaluate to the actual functions f and g:

Source https://stackoverflow.com/questions/54587400

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

Vulnerabilities

No vulnerabilities reported

Install Auto-Annotate

If annotating objects supported by COCO Dataset Download pre-trained COCO weights (mask_rcnn_coco.h5) from the releases page and store it in the root directory. If annotating objects Custom Objects Train Mask RCNN and use those weights. Run Commands as below based on the mode.
Clone this repository
Install dependencies pip3 install -r requirements.txt
If annotating objects supported by COCO Dataset Download pre-trained COCO weights (mask_rcnn_coco.h5) from the releases page and store it in the root directory. If annotating objects Custom Objects Train Mask RCNN and use those weights.
Run Commands as below based on the mode.
Find the annotations in the directory - /path/to/the/image/directory/ specified above

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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