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Morph | My entry for ModJam | Frontend Framework library

 by   iChun Java Version: Current License: LGPL-3.0

 by   iChun Java Version: Current License: LGPL-3.0

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kandi X-RAY | Morph Summary

Morph is a Java library typically used in User Interface, Frontend Framework, React applications. Morph has no bugs, it has build file available, it has a Weak Copyleft License and it has low support. However Morph has 1 vulnerabilities. You can download it from GitHub.
My entry for ModJam #2.
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • Morph has a low active ecosystem.
  • It has 138 star(s) with 179 fork(s). There are 34 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 129 open issues and 853 have been closed. On average issues are closed in 106 days. There are 4 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of Morph is current.
Morph Support
Best in #Frontend Framework
Average in #Frontend Framework
Morph Support
Best in #Frontend Framework
Average in #Frontend Framework

quality kandi Quality

  • Morph has 0 bugs and 0 code smells.
Morph Quality
Best in #Frontend Framework
Average in #Frontend Framework
Morph Quality
Best in #Frontend Framework
Average in #Frontend Framework

securitySecurity

  • Morph has 1 vulnerability issues reported (0 critical, 1 high, 0 medium, 0 low).
  • Morph code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
Morph Security
Best in #Frontend Framework
Average in #Frontend Framework
Morph Security
Best in #Frontend Framework
Average in #Frontend Framework

license License

  • Morph is licensed under the LGPL-3.0 License. This license is Weak Copyleft.
  • Weak Copyleft licenses have some restrictions, but you can use them in commercial projects.
Morph License
Best in #Frontend Framework
Average in #Frontend Framework
Morph License
Best in #Frontend Framework
Average in #Frontend Framework

buildReuse

  • Morph 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.
  • Morph saves you 3828 person hours of effort in developing the same functionality from scratch.
  • It has 8161 lines of code, 363 functions and 49 files.
  • It has high code complexity. Code complexity directly impacts maintainability of the code.
Morph Reuse
Best in #Frontend Framework
Average in #Frontend Framework
Morph Reuse
Best in #Frontend Framework
Average in #Frontend Framework
Top functions reviewed by kandi - BETA

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

  • Handles a render tick event .
  • Process chat command .
  • Generate JSON code .
  • Handles a server event .
  • update the cube of the cube
  • Creates a new biped arm .
  • Called when a living connection is being live .
  • Initializes the morph .
  • Initialize the PostModels .
  • Read entity from world .

Morph Key Features

Kill a mob to acquire it as morph.

Hit "[" or "]" (defaults) to open the Morph Selection GUI and scroll up and down.

Hit "[" or "]" while holding SHIFT (defaults) to scroll left and right.

Hit ENTER/RETURN/LEFT CLICK to select a Morph.

Hit ESCAPE/RIGHT CLICK to close the GUI.

Hit DELETE/BACKSPACE to delete a Morph.

Detecting squares in a chessboard OpenCV

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import cv2
import numpy as np

# Load image, grayscale, Gaussian blur, Otsu's threshold
image = cv2.imread("1.png")
mask = np.zeros(image.shape, dtype=np.uint8)
original = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (5,5), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

# Remove noise with morph operations
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=1)
invert = 255 - opening

# Find contours and find squares with contour area filtering + shape approximation
cnts = cv2.findContours(invert, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    area = cv2.contourArea(c)
    peri = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.02 * peri, True)
    if len(approx) == 4 and area > 100 and area < 10000:
        x,y,w,h = cv2.boundingRect(c)
        cv2.drawContours(original, [c], -1, (36,255,12), 2)
        cv2.drawContours(mask, [c], -1, (255,255,255), -1)

cv2.imshow("original", original)
cv2.imshow("mask", mask)
cv2.waitKey()

Find box in the image and save as an image cv2

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import cv2
import numpy as np

img = cv2.imread("2lscp.png", cv2.IMREAD_GRAYSCALE)
ret, img = cv2.threshold(img, 50, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)

Contours = cv2.findContours(img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)[-2]

newImg = np.zeros(img.shape, dtype=np.uint8)
for Contour in Contours:
    if cv2.pointPolygonTest(Contour, (1, 1), False) == -1:
        cv2.drawContours(newImg, [Contour], -1, 255, 1)

Contours = cv2.findContours(newImg, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
for Contour in Contours:
    [x, y, w, h] = cv2.boundingRect(Contour)

    cv2.imshow("box extracted", img[y:y+h, x:x+w])
    cv2.waitKey(0)

cv2.destroyAllWindows()

-----------------------
import cv2
import numpy as np

#Read input image
img = cv2.imread('hw_data.png')

#convert from BGR to HSV color space
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

#apply threshold
thresh = cv2.threshold(gray, 30, 255, cv2.THRESH_BINARY)[1]

# find contours and get one with area about 180*35
# draw all contours in green and accepted ones in red
contours = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
contours = contours[0] if len(contours) == 2 else contours[1]
#area_thresh = 0
min_area = 0.95*180*44
max_area = 1.05*180*44
print(min_area)
print(max_area)
result = img.copy()
i = 1
for c in contours:
#     print(c)
    area = cv2.contourArea(c)
    cv2.drawContours(result, [c], -1, (0, 255, 0), 1)
    
    x,y,w,h = cv2.boundingRect(c)
    # crop region of img using bounding box
    region = result[y:y+h, x:x+w]
    # save region to new image
    print(region.shape,' i ',i)
#     cv2.imwrite("black_region_{0}.png".format(i), region)
    i = i + 1
    if region.shape[0]>70 and region.shape[1]<100:
        cv2.imwrite("black_region_{0}.png".format(i), region)
#         break
#     if area > min_area and area < max_area:
#             cv2.drawContours(result, [c], -1, (0, 0, 255), 1)
#             break

# save result
# cv2.imwrite("box_found.png", result)

# show images
# cv2.imshow("GRAY", gray)
# cv2.imshow("THRESH", thresh)
# cv2.imshow("RESULT", result)
# cv2.waitKey(0)

Selecting a class within a used defs/symbol

copy iconCopydownload iconDownload
use{ fill: red; }/*will fill red both use elements*/
.rect2 { fill: yellow; }/*will fill yellow the .rect2 inside defs*/
.morph { fill: green; }/*will fill green the second use element overwritting the fill:red from the first roule.*/

rect { stroke: black; }
svg { background-color: lightblue; }
<svg viewBox="0 0 100 100">
  <defs>
    <g id="house-def">
      <rect class="rect1" x="10" y="10" width="20" height="10" />
      <rect class="rect2" x="10" y="20" width="20" height="10" />
    </g>
  </defs>
  <use class="a" xlink:href="#house-def" />
  <use xlink:href="#house-def" class="morph" transform="translate(30)" />
  
</svg>
-----------------------
use{ fill: red; }/*will fill red both use elements*/
.rect2 { fill: yellow; }/*will fill yellow the .rect2 inside defs*/
.morph { fill: green; }/*will fill green the second use element overwritting the fill:red from the first roule.*/

rect { stroke: black; }
svg { background-color: lightblue; }
<svg viewBox="0 0 100 100">
  <defs>
    <g id="house-def">
      <rect class="rect1" x="10" y="10" width="20" height="10" />
      <rect class="rect2" x="10" y="20" width="20" height="10" />
    </g>
  </defs>
  <use class="a" xlink:href="#house-def" />
  <use xlink:href="#house-def" class="morph" transform="translate(30)" />
  
</svg>

RxJs listen to scroll and take first emit of both directions

copy iconCopydownload iconDownload
lastScrollTop: number = 0;

ngOnInit() {
  fromEvent(window, 'scroll')
    .pipe(
      untilDestroyed(this),
      debounceTime(100),
      map(() => {
        let st = window.pageYOffset || document.documentElement.scrollTop;
        let diff = st - this.lastScrollTop;
        this.lastScrollTop = st <= 0 ? 0 : st;
        return diff >= 0 ? 'Down' : 'Up';
      }),
      distinctUntilChanged()
    )
    .subscribe((scrollDirection) => {
      console.log('Scroll Direction:',scrollDirection);
    });
}

getting notifiable and implementing custom morph relation in Laravel notification

copy iconCopydownload iconDownload
    public function up()
    {
        Schema::table('notifications', function (Blueprint $table) {
            $table->string("causer_type")->after('notifiable_id');
            $table->unsignedInteger("causer_id")->after('causer_type');
            $table->index(["causer_type", "causer_id"]);
        });
    }

    public function down()
    {
        Schema::table('notifications', function (Blueprint $table) {
            $table->dropMorphs('causer');
        });
    }

Horizontal scroll bar appears

copy iconCopydownload iconDownload
#svg1 {
  position: absolute;
  z-index: 2 !important;
  filter: drop-shadow(0px 3px 6px rgba(0, 0, 0, 0.16));
  right: 0;
}

#svg2 {
  position: absolute;
  z-index: 1 !important;
  filter: drop-shadow(0px 3px 6px rgba(0, 0, 0, 0.16));
  right: 0;
}

How to svg morph in ReactJs between two elements

copy iconCopydownload iconDownload
const getPoints = radius => {
  const factor = Math.sqrt(3);
  return [
    {x: 0, y: -radius},
    {x: radius / factor, y: -radius},
    {x: radius * factor / 2, y: -radius / 2},
    {x: radius * 2 / factor, y: 0},
    {x: radius * factor / 2, y: radius / 2},
    {x: radius / factor, y: radius},
    {x: 0, y: radius},
    {x: -radius / factor, y: radius},
    {x: -radius * factor / 2, y: radius / 2},
    {x: -radius * 2 / factor, y: 0},
    {x: -radius * factor / 2, y: -radius / 2},              
    {x: -radius / factor, y: -radius}
  ];
}


const getRoundPath = radius => {
  const p = getPoints(radius);
  return `M ${p[0].x},${p[0].y} 
    Q ${p[1].x},${p[1].y} ${p[2].x},${p[2].y} 
    Q ${p[3].x},${p[3].y} ${p[4].x},${p[4].y} 
    Q ${p[5].x},${p[5].y} ${p[6].x},${p[6].y} 
    Q ${p[7].x},${p[7].y} ${p[8].x},${p[8].y} 
    Q ${p[9].x},${p[9].y} ${p[10].x},${p[10].y} 
    Q ${p[11].x},${p[11].y} ${p[0].x},${p[0].y}`
};

const getHexagonPath = radius => {
  const p = getPoints(radius);
  for (let index = 1; index < 12; index += 2) {
    const prev = p[index - 1];
    const next = p[(index + 1) % 12];
    p[index].x = (prev.x + next.x) / 2;
    p[index].y = (prev.y + next.y) / 2;
  }
  return `M ${p[0].x},${p[0].y} 
    Q ${p[1].x},${p[1].y} ${p[2].x},${p[2].y} 
    Q ${p[3].x},${p[3].y} ${p[4].x},${p[4].y} 
    Q ${p[5].x},${p[5].y} ${p[6].x},${p[6].y} 
    Q ${p[7].x},${p[7].y} ${p[8].x},${p[8].y} 
    Q ${p[9].x},${p[9].y} ${p[10].x},${p[10].y} 
    Q ${p[11].x},${p[11].y} ${p[0].x},${p[0].y}`
}

const morphPath = (toHex) => {
  const path = toHex ? getHexagonPath(80) : getRoundPath(80);
  d3.select('path')
    .transition()
    .duration(750)
    .attr('d', path);
  setTimeout(() => morphPath(!toHex), 1000);
};

d3.select('path').attr('d', getRoundPath(80))

morphPath(true);
<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/5.7.0/d3.min.js"></script>
<svg width="200" height="200">
  <g transform="translate(100,100)">     
    <path />
  </g>
</svg>
-----------------------
const getPoints = radius => {
  const factor = Math.sqrt(3);
  return [
    {x: 0, y: -radius},
    {x: radius / factor, y: -radius},
    {x: radius * factor / 2, y: -radius / 2},
    {x: radius * 2 / factor, y: 0},
    {x: radius * factor / 2, y: radius / 2},
    {x: radius / factor, y: radius},
    {x: 0, y: radius},
    {x: -radius / factor, y: radius},
    {x: -radius * factor / 2, y: radius / 2},
    {x: -radius * 2 / factor, y: 0},
    {x: -radius * factor / 2, y: -radius / 2},              
    {x: -radius / factor, y: -radius}
  ];
}


const getRoundPath = radius => {
  const p = getPoints(radius);
  return `M ${p[0].x},${p[0].y} 
    Q ${p[1].x},${p[1].y} ${p[2].x},${p[2].y} 
    Q ${p[3].x},${p[3].y} ${p[4].x},${p[4].y} 
    Q ${p[5].x},${p[5].y} ${p[6].x},${p[6].y} 
    Q ${p[7].x},${p[7].y} ${p[8].x},${p[8].y} 
    Q ${p[9].x},${p[9].y} ${p[10].x},${p[10].y} 
    Q ${p[11].x},${p[11].y} ${p[0].x},${p[0].y}`
};

const getHexagonPath = radius => {
  const p = getPoints(radius);
  for (let index = 1; index < 12; index += 2) {
    const prev = p[index - 1];
    const next = p[(index + 1) % 12];
    p[index].x = (prev.x + next.x) / 2;
    p[index].y = (prev.y + next.y) / 2;
  }
  return `M ${p[0].x},${p[0].y} 
    Q ${p[1].x},${p[1].y} ${p[2].x},${p[2].y} 
    Q ${p[3].x},${p[3].y} ${p[4].x},${p[4].y} 
    Q ${p[5].x},${p[5].y} ${p[6].x},${p[6].y} 
    Q ${p[7].x},${p[7].y} ${p[8].x},${p[8].y} 
    Q ${p[9].x},${p[9].y} ${p[10].x},${p[10].y} 
    Q ${p[11].x},${p[11].y} ${p[0].x},${p[0].y}`
}

const morphPath = (toHex) => {
  const path = toHex ? getHexagonPath(80) : getRoundPath(80);
  d3.select('path')
    .transition()
    .duration(750)
    .attr('d', path);
  setTimeout(() => morphPath(!toHex), 1000);
};

d3.select('path').attr('d', getRoundPath(80))

morphPath(true);
<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/5.7.0/d3.min.js"></script>
<svg width="200" height="200">
  <g transform="translate(100,100)">     
    <path />
  </g>
</svg>

Video Morph Between Two Images, FFMPEG/Minterpolate

copy iconCopydownload iconDownload
ffmpeg -y -r 0.3 -stream_loop 1 -i test02_01.png -r 0.3 -stream_loop 2 -i test02_02.png -filter_complex "[0][1]concat=n=2:v=1:a=0[v];[v]minterpolate=fps=24:scd=none,trim=3:7,setpts=PTS-STARTPTS" -pix_fmt yuv420p test02.mp4

Android Jetpack Compose (Composable) Change Image source with animation

copy iconCopydownload iconDownload
Crossfade(
    flag,
    animationSpec = tween(1000)
) { targetState ->
    Image(
        painterResource(if (targetState) R.drawable.ic_redo else R.drawable.ic_undo),
        contentDescription = null,
        modifier = Modifier.background(Color.Black)
    )
}
AnimatedContent(
    flag,
    transitionSpec = {
        fadeIn(animationSpec = tween(durationMillis = 1500)) with
                fadeOut(animationSpec = tween(durationMillis = 500))
    }
) { targetState ->
    Image(
        painterResource(if (targetState) R.drawable.ic_redo else R.drawable.ic_undo),
        contentDescription = null,
        modifier = Modifier.background(Color.Black)
    )
}
-----------------------
Crossfade(
    flag,
    animationSpec = tween(1000)
) { targetState ->
    Image(
        painterResource(if (targetState) R.drawable.ic_redo else R.drawable.ic_undo),
        contentDescription = null,
        modifier = Modifier.background(Color.Black)
    )
}
AnimatedContent(
    flag,
    transitionSpec = {
        fadeIn(animationSpec = tween(durationMillis = 1500)) with
                fadeOut(animationSpec = tween(durationMillis = 500))
    }
) { targetState ->
    Image(
        painterResource(if (targetState) R.drawable.ic_redo else R.drawable.ic_undo),
        contentDescription = null,
        modifier = Modifier.background(Color.Black)
    )
}

How to get full AST representation of union type in typescript?

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// available as @ts-morph/bootstrap on npm
import { ts, createProjectSync } from "https://deno.land/x/ts_morph@13.0.3/bootstrap/mod.ts";

// setup code... you can use the vanilla ts compiler for this, but it's a lot of work
const project = createProjectSync();
const sourceCode = "type Foo = keyof Array<number>";
const sourceFile = project.createSourceFile("file.ts", sourceCode);
const typeChecker = project.createProgram().getTypeChecker();

// example use with the compiler API
const fooTypeAlias = sourceFile.statements[0] as ts.TypeAliasDeclaration;

const fooType = typeChecker.getTypeAtLocation(fooTypeAlias.name);
if (fooType.isUnion()) {
  for (const type of fooType.types) {
    console.log(typeChecker.typeToString(type, fooTypeAlias.name));
  }
}
number
"length"
"toString"
"toLocaleString"
"pop"
"push"
"concat"
"join"
"reverse"
"shift"
"slice"
"sort"
"splice"
"unshift"
"indexOf"
"lastIndexOf"
"every"
"some"
"forEach"
"map"
"filter"
"reduce"
"reduceRight"
-----------------------
// available as @ts-morph/bootstrap on npm
import { ts, createProjectSync } from "https://deno.land/x/ts_morph@13.0.3/bootstrap/mod.ts";

// setup code... you can use the vanilla ts compiler for this, but it's a lot of work
const project = createProjectSync();
const sourceCode = "type Foo = keyof Array<number>";
const sourceFile = project.createSourceFile("file.ts", sourceCode);
const typeChecker = project.createProgram().getTypeChecker();

// example use with the compiler API
const fooTypeAlias = sourceFile.statements[0] as ts.TypeAliasDeclaration;

const fooType = typeChecker.getTypeAtLocation(fooTypeAlias.name);
if (fooType.isUnion()) {
  for (const type of fooType.types) {
    console.log(typeChecker.typeToString(type, fooTypeAlias.name));
  }
}
number
"length"
"toString"
"toLocaleString"
"pop"
"push"
"concat"
"join"
"reverse"
"shift"
"slice"
"sort"
"splice"
"unshift"
"indexOf"
"lastIndexOf"
"every"
"some"
"forEach"
"map"
"filter"
"reduce"
"reduceRight"

Community Discussions

Trending Discussions on Morph
  • Detecting squares in a chessboard OpenCV
  • Find box in the image and save as an image cv2
  • Selecting a class within a used defs/symbol
  • RxJs listen to scroll and take first emit of both directions
  • getting notifiable and implementing custom morph relation in Laravel notification
  • Horizontal scroll bar appears
  • How to svg morph in ReactJs between two elements
  • Video Morph Between Two Images, FFMPEG/Minterpolate
  • Android Jetpack Compose (Composable) Change Image source with animation
  • How to get full AST representation of union type in typescript?
Trending Discussions on Morph

QUESTION

Detecting squares in a chessboard OpenCV

Asked 2022-Apr-15 at 07:30

I detected a chessboard using OpenCV in python using:

  • Computing the edge of the image
  • Computing the Hough transform
  • Finding the local maxima of Hough transform
  • Extracting the image lines

Then I used findContours and drawContours functions:

  im_gray = cv2.imread('redLines.png', cv2.IMREAD_GRAYSCALE)
  kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2))  
  morphed = cv2.dilate(im_gray, kernel, iterations=1)
  (ret, thresh) = cv2.threshold(morphed, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
  contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
  cv2.drawContours(thresh, contours, -1, (255, 255, 255), 3)

And it worked well, the last imshow looks something like this:

enter image description here

Now, I'm trying to detect each square in the grid and save its points in a unique index in a vector.

I know I can do it using the contours array. But when I print the length of the contours it keeps changing rapidly, from size 2 up to 112..

So I guess it's not recognizing the grids well.

Any help would be appreciated.

ANSWER

Answered 2022-Apr-15 at 07:30

An approach is to use contour area filtering + shape approximation. Since a square has 4 corners, we can assume a contour is a square if it has four vertices.

Detected squares in green

enter image description here

Isolated squares

enter image description here

import cv2
import numpy as np

# Load image, grayscale, Gaussian blur, Otsu's threshold
image = cv2.imread("1.png")
mask = np.zeros(image.shape, dtype=np.uint8)
original = image.copy()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (5,5), 0)
thresh = cv2.threshold(blur, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

# Remove noise with morph operations
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=1)
invert = 255 - opening

# Find contours and find squares with contour area filtering + shape approximation
cnts = cv2.findContours(invert, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
    area = cv2.contourArea(c)
    peri = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.02 * peri, True)
    if len(approx) == 4 and area > 100 and area < 10000:
        x,y,w,h = cv2.boundingRect(c)
        cv2.drawContours(original, [c], -1, (36,255,12), 2)
        cv2.drawContours(mask, [c], -1, (255,255,255), -1)

cv2.imshow("original", original)
cv2.imshow("mask", mask)
cv2.waitKey()

Source https://stackoverflow.com/questions/71879515

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

Vulnerabilities

No vulnerabilities reported

Install Morph

You can download it from GitHub.
You can use Morph like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the Morph component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

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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