In the README.md there is a link for referring the project documentation redirecting to https://scorelab.org/ImageLab. But is not working right now by showing the page not found. I can update the README.md if the correct link is provided.

Currently the UI is made for a fixed width. The panes don't fit other widths.

The colormap functionality under the convertions section hasn't been implemented yet

yarn install for the folder \imagelab_react>
is stuck in this part

Hough Circle Transformation is used to detect circles in a given image. You can use Imgproc.HoughCircles() method in OpenCV library to apply this operator.

Current imagelab electron UI doesn't include a section for help for the starters. Need to implement such a feature to onboard the users extensively.

The current version of the ImageLab backend properties forms works upon text fields in most of the operators. it raised an exception when the text field got empty. It is easy to remove the exceptions and improve the UX by using sliders in javafx.scene

Also, it makes easy to make property changing task for an operator and make it easy for the end-user

The colorspace functionality to convert once color space to another is not implemented yet.

The save and load buttons are currently unresponsive and no action can be performed.

Currently there is no filter2D operation in the electron version of imagelab.

Erosion is quite a similar process as dilation. But the pixel value computed here is minimum rather than the maximum in dilation. The image is replaced under the anchor point with that minimum pixel value.

With this procedure, the areas of dark regions grow in size and bright regions reduce. For example, the size of an object in the dark shade or black shade increases, while it decreases in the white shade or bright shade.

You can perform this operation on an image using the erode() method of the OpenCV imgproc class.

Check the project documentation for more information related to the project setup and contributions.

We can add various borders to an image in using the method copyMakeBorder() of the class named Core, which belongs to the package org.opencv.core.

Check the project documentation for more information related to the project setup and contributions.

On running npm run dev i am getting this error.
'BROWSER' is not recognized as an internal or external command.

Operators like ImagePyramids(both Pyramids Up and Down) need variable image size(scale up or down) to show the scaling changes applied for the image. Fixed Image Size would be a barrier for that. To Resolve that ProcessedImageView.java should be updated accordingly.

The description panel in the electron app does not show the description for the related operator. It shows only a dummy message of here is the operation description. When a user selects an operator in the playground the description panel needs to display the details regarding the selected operator.

This feature can help the user in removing a specific filter. Till now, if the user has to remove the filter then he/she have to reset it which removes all the filter and the image itself due to which the user has to start all over again which is time-consuming.

It will be better if there is shortcut for run operation (for example: Ctrl+R) . It will ease usage.

Currently, the UI of ImageLab is not very interactive There is no exit, minimize button so every time the user has to force close the app.

When running the electron app in macOS the name of the app is showing under the windows operations.

OS version - macOS Monterey
nom version - 8.5.4

We can apply different colour maps to an image using the method applyColorMap() of the OpenCV class Imgproc.

Check out the project documentation for more information related to the project setup and contributions.

this error message is showing in terminal while running electron app.
and in the browser window another error is displaying.

Current imagelab documentation page doesn't include the electron project documentation and steps support for setup. It needs to include in the original wiki page.

At the time I'm viewing readme, here's the install instructions -

Given that now there are electron and react renders of the app (alongwith original java one) (idk what to call the seperate directories "imagelab_react" , "imagelab_java" and "imagelab_electron" other than seperate renders of the app) , a simple mvn clean install in project directory doesn't work. It gives the following error -

When I changed my directory to /ImageLab/imagelab_java, it gave the following error -

[Updated]

At now when we click the execute command it shows the download window again and again. Instead of that add a download button (with icon) and integrate the image download operation with it.

The Box Filter operation is similar to the averaging blur operation; it applies a bilateral image to a filter. You can perform this operation on an image using the boxFilter() method of the openCV imgproc class.

Check the project documentation for more information related to the project setup and contributions.

Expect to add hacktoberfest label to readme and the documentation to indicate that project is eligible and and open for hactoberfest contributors.

Unlike the java project, the electron project is yet to have undo/redo functions.

the bilateral filter is one of the main filtering operations that allow you to do bilateral image applies to a filter. It performs this operation on an image using the medianBlur() method of the imgproc class. bilateralFilter() is the syntax of this method of the OpenCV imgproc class.

Currently, I'm looking forward to implementing this feature for the purpose of complete the filtering operation section on ImageLab.

The following templates are required

1. PR Template
2. Issues - Bug Report
3. Issues - Feature Request

Remapping is the process of taking pixels from one place in the image and locating them in another position in a new image. OpenCV supports remapping with Imgproc.remap()

Following higher-level tasks needs to be discussed and finalized.

• Finalizing the proposed architecture and technologies for ImageLab
• Finalizing the mockups related to the user interface of ImageLab
• Imlpementing user interfacer
  • Implemeting tools panel
  • Implemeting building panel to drag and drop UI elements
  • Implemeting visualizing panel to display current output
  • Implemeting info pannel which shows errors and recommendations
• Finalizing the features to be developed and start developement
  • Feat: implementing a UI element structure to invoke image processing with openCV
  • Feat: implementing imageLab core which communicates with openCV
  • Feat: implementing communication pipeline
• Writing tests to evaluate developed features
• Making project documentation
• Updating project README with relevant information

Thresholding is a method of image segmentation, in general, it is used to create binary images. Thresholding is of two types namely, simple thresholding and adaptive thresholding.

We can perform a simple threshold operation on an image using the method threshold() of the Imgproc class.

Check the project documentation for more information related to the project setup and contributions.

adding feature of Light Mode/Dark Mode for the program

Description

Grammatical and spelling errors appear on the introduction screen of the electron app.

Screenshot for reviewing

Following are the milestones for GSoC 2023

Milestone 1 (UI/UX Revamp)

• Proof of concept for electron app built on top of react
• Integrate react-blockly framework
• Initialise new project
• Rewrite UI components in React based on updated design
• Migrate boilerplate code from original project
• Connect the backend with the new UI

Milestone 2 (Add testing framework)

• Finalize testing framework
• Write unit and end to end tests for the React & Electron App

Milestone 3 (Implement video processing operators)

• Implement the meanShift operator
• Implement the camShift operator
• Implement the Dense Optical flow operator
• Implement the background subtraction operator

Milestone 4 (Implement neural network operators)

• Implement the image-classification operator
• Implement the Object Detection operator
• Implement the Semantic Segmentation operator
• Implement the Style Transfer operator
• Implement the Pose Estimation operator
• Configure import model block

Milestone 5 (Documentation)

• Update the documentation based on the frameworks used
• Update the Readme and contributing docs to comprehensively cover the entire electron project

Following higher-level milestones and tasks needs to be discussed and finalized in the GSoC 2021 under ImageLab - extend the functionality.

Milestone 1 - Architecture Improvements

• Finalize the implementation of architecture changes to the code

Milestone 2 - Implementation of the OpenCV operators(Phase 01)

• Implement Extended geometric transformation operators
• Implement Extended filtering operators
• Implement Drawing operators
• Implement Morphological operators
• Implement Sobel Derivation
• Implement Transformation operators

Milestone 3 - Implementation of the OpenCV operators(Phase 02)

• Implement Histogram operators
• Implement Contour operators
• Implement Miscellaneous operators
• Implement Image Segmentation with Distance Transform and Watershed Algorithm
• Export OpenCV Operation Stream as an illustration

Milestone 4 - Implementation of visualization pane and application section

• Implement the visualization pane section using histograms
• Implement the application section with predefined operator streams

Milestone 5 - Testing

• Writing tests to evaluate developed features

Milestone 6 - Documentation

• Updating the project documentation for newly created functionality
• Updating project README with relevant information

Erosion and dilation are the two types of morphological operations. As the name implies, morphological operations are the set of operations that process images according to their shapes.

Based on the given input image a "structural element" is developed. This might be done in any of the two procedures. These are aimed at removing noise and settling down the imperfections, to make the image clear

You can perform the dilation operation on an image using the dilate() method of the OpenCV imgproc class.

Check the project documentation for more information related to the project setup and contributions.

GSoC 2021 Milestones

Phase 1

• Designing a logo for ImageLab project
• Designing a splash screen (loading screen)
• Making a quick guide on the first use
• Improving the project User Interface and implementing it
• Adding night mode
• Designing new block shapes and replacing all blocks with the new design
• Adding zooming in the playground and also in preview pane.
• Add save or don’t save pipeline option when closing the app.

Phase 2

• Enhance the view of the project documentation.
• Improve new way for unmergeable blocks.
• Adding help section
• Adding Info (About us) section
• Providing availability for all image sizes
• Adding history pane
• Drag and drop in basket to remove a specific filter
• Add (new pipeline) button
• Package the application into an installable exe file in windows
• Run with keyboard shortcut.

Here are some a picture shows my imagination about the new UI :

For detailed information you can check my proposal

Your feedbacks are much welcomed !

Polygon is a figure with at least three straight sides and angles.OpenCV provides polygon drawing facility with Improc.fillPoly() method. Moreover, the operator enables to add custom points dynamically and it will generate the filled polygon accordingly.

The spelling of "changed" is misspelled in the operator information pane. Issue Link

The undo, redo, execute and reset buttons have dark colors in dark mode. They seem to camouflage with the background.

The text seems proper once the drop-down is active. Outer Text needs padding as well. The 'r' of filter is getting cut.

You can draw various shapes like Circle, Rectangle, Line, Ellipse, Polylines, Convex, Polylines, Polylines on an image using the respective methods of the org.opencv.imgproc package.

So, in this issue we expect you to add drawing operations to ImageLab.

Check the project documentation for more information related to the project setup and contributions.

Preview Pane plays a major role in ImageLab since it displays the processed image in the operator stream. The current solution has less space for the preview pane. it should spread more over the application to give more user experience and to provide a good learning experience

.

Operations in the "convertions" section are not working. When those blocks are added, there is no visible change in the output

Current ImageLab works with an operator pipeline to do the image processing tasks. If a user mistakenly adds an unwanted operator, he/she has to reset the whole pipeline. But, the feature Undo/Redo operation enables users to recover that action and go to the previous state. In order to do that task, DashboardControlller should be improved accordingly.

In Pyramid Up, the image is initially up-sampled and then blurred. You can perform Pyramid Up operation on an image using the pyrUP() method of the OpenCV imgproc class.

Check the project documentation for more information related to the project setup and contributions.

Adaptive thresholding is the method where the threshold value is calculated for smaller regions and therefore, there will be different threshold values for different regions.

In OpenCV, you can perform Adaptive threshold operation on an image using the method adaptiveThreshold() of the Imgproc class.

So, this issue expects contributors to add adaptive threshold operator to ImageLab.

Check the project documentation for more information related to the project setup and contributions.

When installing the packages a dependency issue occur. Try to fix the issue by changing the dependency versions.