Trending March 2024 # Roblox Decals And Image Id Codes Guide # Suggested April 2024 # Top 7 Popular

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One of the best things about ROBLOX is just how customizable it is. It’s a space where you can express yourself from server to server. One of the best ways to do that is to use decals to assign custom images to objects in the world. You can change a boring wall to a wall with a picture of your favorite sci-fi spaceship or a cute and cuddly kitten.

ROBLOX decals are images that you can apply to many surfaces in ROBLOX. They help you create the world you want to be in and are used in almost every game aspect. You can search for decals in the library by typing a keyword in the “Search for decal” field. There are many available to use right away, with everything from designs to pop media to celebrities. 

Each object in the world that you can edit has six parts to it. You can apply a decal on any of these six parts. You can combine different ones to create a variety of effects beyond what a single decal could achieve. 

ROBLOX images ID codes also called asset IDs are the unique codes assigned to each decal available on ROBLOX. When you go into the library of assets in Roblox Studio to search for decals, you must take note of the asset ID. You will use it when you apply the decal to a surface. 

For example, a Pikachu decal ID you can use is 46059313.

You can apply a ROBLOX decal to any part of an object that accepts it. You adjust which decal is on a part in Roblox Studio. 

You can create your own ROBLOX decals and use them on servers that let you change the way objects look. However, you can’t just upload it and use it right away. ROBLOX is a moderated platform, and ROBLOX must first approve anything you add to the landscape. In this way, the community is kept safe and appropriate for all users. 

Images shouldn’t be larger than 1024×1024, or else they will be scaled down. 

Once you’ve created a decal you want to use, upload it from your profile page. It will be checked automatically and in most cases, quickly approved.  

When you’ve created a decal and are ready to seek approval, upload it to get the process started. 

Your decal will be available once it’s approved.

The time varies depending on what you uploaded and how it’s processed. Most players say the initial check doesn’t take more than 20 minutes most of the time and speculate that AI does it. However, it can take longer to check specific images and approve them. Some people have said their decals have taken more than a day to gain approval. 

Sometimes ROBLOX will choose not to approve your decal. This is often because it violates the community standards or their terms of use.

Community Standards

Roblox values four specific community standards: safety; civility and respect; fairness and transparency; security and privacy. Keep these in mind when you create your decal. Remember that there are lots of children on ROBLOX, and everything should be family-friendly. It’s also important to remember that kindness matters a lot in the game. If you keep it clean and kind, you won’t have a problem getting approval. 

Terms of Use

If you’re concerned that your images might violate the Terms of Use, read through the agreement before submitting your decal. People upload all kinds of decals, and as long as you follow the Community Standards, it seems unlikely that it would violate the Terms of Use. 

If you’re experiencing an issue with your decals, the fix is probably pretty simple.

If all the decals on a server appear blurry, it’s probably a connection issue. Try logging off, resetting your network, and then logging back in to see whether the decals look clearer. If you see blurry images throughout Roblox, consider doing some troubleshooting. 

You shouldn’t upload an image that you find through a search. Instead, it needs to be something you’ve changed and made your own. If you just grabbed an image from a search engine, it might not be approved. 

Other than that, it might just be a matter of time. All you can do if your decal isn’t being approved is wait to hear from the moderators. If more than a week has gone by without a message, you could try reaching out to ROBLOX support. 

Explain the issue and consider linking to a copy of the decal on Imgur or a similar site. That way, it’s easy for the moderator to find the image you’re asking about. 

You can use the Spray Paint device to add decals to areas that allow them easily. You have to use the asset ID to apply them. You can buy the Spray Paint device from the shop. 

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Novel Ai Image Generation Guide

See More : How To Use NovelAI Image Generation Free

In today’s digital age, visual content plays a crucial role in capturing attention and conveying messages effectively. Whether you are an artist, designer, marketer, or content creator, having the ability to generate compelling images is a valuable skill. This is where NovelAI steps in, offering a user-friendly platform that harnesses the power of artificial intelligence to generate stunning visuals that match your creative vision.

To embark on your image generation journey with NovelAI, the first step is to subscribe to their platform. By becoming a NovelAI member, you gain access to their extensive suite of tools and features, including the highly acclaimed image generation feature. Subscribe today and unlock the full potential of your creative prowess.

Once you have subscribed to NovelAI, it’s time to dive into the world of image generation. Start by figuring out your prompt—a concise description of the image you envision. Whether it’s a majestic landscape, a mythical creature, or a futuristic cityscape, clearly define your prompt to guide the AI in generating the desired visuals.

NovelAI offers the flexibility to pick your favorite prompts and experiment with various editing options. Tweak, refine, and enhance your prompts to achieve the perfect balance between imagination and reality. Let your creativity run wild as you explore the possibilities that NovelAI has to offer.

To fine-tune your image generation process, NovelAI provides you with the option to adjust your text prompt and generation settings. The Edit Image canvas allows you to make precise modifications, ensuring that the generated images align with your creative vision.

Experiment with different parameters such as strength, noise, and resolution aspects to refine your results further. Refocus your text prompt to emphasize specific visual characteristics or let the AI interpret your words and create stunning compositions that surpass your expectations.

In the realm of image generation, NovelAI empowers users to define the visual characteristics of their creations in two distinct ways. You can either use tags to specify the desired attributes of your character or composition, or you can let the AI interpret your words and generate visuals based on its understanding.

By using tags such as {detailed}, {ornate}, {realistic}, or {photorealistic}, you can add intricate details to objects or clothing and steer the image away from a flat 2D anime style. These tags provide you with granular control over the final output, allowing you to bring your creative vision to life.

NovelAI’s cutting-edge technology is driven by their custom NovelAI Diffusion Models, built on the foundation of Stable Diffusion. This unique approach ensures the generation of high-quality images with remarkable realism and artistic appeal.

Also Read : How To Create NSFW AI Art?

After generating the initial set of images, NovelAI offers a range of powerful image editing and refinement tools to further enhance and customize your visuals. These tools allow you to fine-tune various aspects of the image, such as color, lighting, composition, and more.

With NovelAI’s intuitive interface, you can easily navigate through the editing tools and make adjustments in real-time. Experiment with different filters, effects, and adjustments to add your personal touch and make the images truly unique.

Through this collaborative process, NovelAI becomes a creative partner that evolves alongside your artistic vision, continually improving its ability to generate images that align with your unique style and preferences.

Once you are satisfied with the generated and refined images, it’s time to save and export your masterpieces. NovelAI allows you to download the images in high-resolution formats, ensuring that you can showcase your artwork in all its glory.

Whether you plan to use the images for personal projects, commercial endeavors, or sharing on social media, NovelAI provides the flexibility to export your creations in various file formats, including JPEG, PNG, and TIFF.

Q: Can I use the images generated by NovelAI for commercial purposes?

A: Yes, you can use the images generated by NovelAI for both personal and commercial purposes. However, it’s always a good practice to review and comply with NovelAI’s terms of service to ensure you are utilizing the images within the allowed guidelines.

Q: How long does it take to generate images with NovelAI?

A: The generation time for images with NovelAI may vary depending on factors such as complexity, resolution, and the number of iterations. Simple images can be generated within seconds, while more complex and high-resolution images may take a few minutes. The platform provides estimated generation times for each image, allowing you to plan your creative process accordingly.

Q: Can I collaborate with other artists or creators on NovelAI?

A: Currently, NovelAI focuses on providing individual creative experiences. While you cannot directly collaborate with other users within the platform, you can certainly share your generated images with fellow artists and collaborate outside of NovelAI using the exported files.

Q: Can I adjust the style or artistic elements of the generated images?

A: Yes, NovelAI offers a range of editing and refinement tools that allow you to adjust the style and artistic elements of the generated images. You can experiment with various filters, effects, and adjustments to achieve your desired look and make the images truly unique.

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Beginner’s Guide To Image Gradient

So, the gradient helps us measure how the image changes and based on sharp changes in the intensity levels; it detects the presence of an edge. We will dive deep into it by manually computing the gradient in a moment.

Why do we need an image gradient?

Image gradient is used to extract information from an image. It is one of the fundamental building blocks in image processing and edge detection. The main application of image gradient is in edge detection. Many algorithms, such as Canny Edge Detection, use image gradients for detecting edges.

Mathematical Calculation of Image gradients

Enough talking about gradients, Let’s now look at how we compute gradients manually. Let’s take a 3*3 image and try to find an edge using an image gradient. We will start by taking a center pixel around which we want to detect the edge. We have 4 main neighbors of the center pixel, which are:

(iv) P(x,y+1) bottom pixel

We will subtract the pixels opposite to each other i.e. Pbottom – Ptop and Pright – Pleft , which will give us the change in intensity or the contrast in the level of intensity of the opposite the pixel.

Change of intensity in the X direction is given by:

Gradient in Y direction = PR - PL

Change of intensity in the Y direction is given by:

Gradient in Y direction = PB - PT

Gradient for the image function is given by:

𝛥I = [𝛿I/𝛿x, 𝛿I/𝛿y]

Let us find out the gradient for the given image function:

We can see from the image above that there is a change in intensity levels only in the horizontal direction and no change in the y direction. Let’s try to replicate the above image in a 3*3 image, creating it manually-

Let us now find out the change in intensity level for the image above

GX = PR - PL Gy = PB - PT GX = 0-255 = -255 Gy = 255 - 255 = 0

𝛥I = [ -255, 0]

Let us take another image to understand the process clearly.

Let us now try to replicate this image using a grid system and create a similar 3 * 3 image.

Now we can see that there is no change in the horizontal direction of the image

GX = PR - PL , Gy = PB - PT GX = 255 - 255 = 0 Gy = 0 - 255 = -255

𝛥I = [0, -255]

But what if there is a change in the intensity level in both the direction of the image. Let us take an example in which the image intensity is changing in both the direction

Let us now try replicating this image using a grid system and create a similar 3 * 3 image.

GX = PR - PL , Gy = PB - PT GX = 0 - 255 = -255 Gy = 0 - 255 = -255

𝛥I = [ -255, -255]

Now that we have found the gradient values, let me introduce you to two new terms:

Gradient magnitude

Gradient orientation

Gradient magnitude represents the strength of the change in the intensity level of the image. It is calculated by the given formula:

Gradient Magnitude: √((change in x)² +(change in Y)²)

The higher the Gradient magnitude, the stronger the change in the image intensity

Gradient Orientation represents the direction of the change of intensity levels in the image. We can find out gradient orientation by the formula given below:

Gradient Orientation: tan-¹( (𝛿I/𝛿y) / (𝛿I/𝛿x)) * (180/𝝅) Overview of Filters

We have learned to calculate gradients manually, but we can’t do that manually each time, especially with large images. We can find out the gradient of any image by convoluting a filter over the image. To find the orientation of the edge, we have to find the gradient in both X and Y directions and then find the resultant of both to get the very edge.

Different filters or kernels can be used for finding gradients, i.e., detecting edges.

3 filters that we will be working on in this article are

Roberts filter

Prewitt filter

Sobel filter

All the filters can be used for different purposes. All these filters are similar to each other but different in some properties. All these filters have horizontal and vertical edge detecting filters.

These filters differ in terms of the values orientation and size

Roberts Filter

Suppose we have this 4*4 image

Let us look at the computation

The gradient in x-direction =

Gx = 100 *1 + 200*0 + 150*0 - 35*1 Gx = 65

The gradient in y direction =

Gy = 100 *0 + 200*1 - 150*1 + 35*0 Gy = 50

Now that we have found out both these values, let us calculate gradient strength and gradient orientation.

Gradient magnitude = √(Gx)² + (Gy)² = √(65)² + (50)² = √6725 ≅ 82

We can use the arctan2 function of NumPy to find the tan-1 in order to find the gradient orientation

Gradient Orientation = np.arctan2( Gy / Gx) * (180/ 𝝅) = 37.5685 Prewitt Filter

Prewitt filter is a 3 * 3 filter and it is more sensitive to vertical and horizontal edges as compared to the Sobel filter. It detects two types of edges – vertical and horizontal. Edges are calculated by using the difference between corresponding pixel intensities of an image.

A working example of Prewitt filter

Suppose we have the same 4*4 image as earlier

Let us look at the computation

The gradient in x direction =

Gx = 100 *(-1) + 200*0 + 100*1 + 150*(-1) + 35*0 + 100*1 + 50*(-1) + 100*0 + 200*1 Gx = 100

The gradient in y direction =

Gy = 100 *1 + 200*1 + 200*1 + 150*0 + 35*0 +100*0 + 50*(-1) + 100*(-1) + 200*(-1) Gy = 150

Now that we have found both these values let us calculate gradient strength and gradient orientation.

Gradient magnitude = √(Gx)² + (Gy)² = √(100)² + (150)² = √32500 ≅ 180

We will use the arctan2 function of NumPy to find the gradient orientation

Gradient Orientation = np.arctan2( Gy / Gx) * (180/ 𝝅) = 56.3099 Sobel Filter

Sobel filter is the same as the Prewitt filter, and just the center 2 values are changed from 1 to 2 and -1 to -2 in both the filters used for horizontal and vertical edge detection.

A working example of Sobel filter

Suppose we have the same 4*4 image as earlier

Let us look at the computation

The gradient in x direction =

Gx = 100 *(-1) + 200*0 + 100*1 + 150*(-2) + 35*0 + 100*2 + 50*(-1) + 100*0 + 200*1 Gx = 50

The gradient in y direction =

Gy = 100 *1 + 200*2 + 100*1 + 150*0 + 35*0 +100*0 + 50*(-1) + 100*(-2) + 200*(-1) Gy = 150

Now that we have found out both these values, let us calculate gradient strength and gradient orientation.

Gradient magnitude = √(Gx)² + (Gy)² = √(50)² + (150)² = √ ≅ 58

Using the arctan2 function of NumPy to find the gradient orientation

Gradient Orientation = np.arctan2( Gy / Gx) * (180/ 𝝅) = 71.5650 Implementation using OpenCV

We will perform the program on a very famous image known as Lenna.

Let us start by installing the OpenCV package

#installing opencv !pip install cv2

After we have installed the package, let us import the package and other libraries

Using Roberts filter

Python Code:



Using Prewitt Filter #Converting image to grayscale gray_img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) #Creating Prewitt filter kernelx = np.array([[1,1,1],[0,0,0],[-1,-1,-1]]) kernely = np.array([[-1,0,1],[-1,0,1],[-1,0,1]]) #Applying filter to the image in both x and y direction img_prewittx = cv2.filter2D(img, -1, kernelx) img_prewitty = cv2.filter2D(img, -1, kernely) # Taking root of squared sum(np.hypot) from both the direction and displaying the result prewitt = np.hypot(img_prewitty,img_prewittx) prewitt = prewitt[:,:,0] prewitt = prewitt.astype('int') plt.imshow(prewitt,cmap='gray')

OUTPUT:

Using Sobel filter gray_img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) kernelx = np.array([[-1,0,1],[-2,0,2],[-1,0,1]]) kernely = np.array([[1, 2, 1],[0, 0, 0],[-1,-2,-1]]) img_x = cv2.filter2D(gray_img, -1, kernelx) img_y = cv2.filter2D(gray_img, -1, kernely) #taking root of squared sum and displaying result new=np.hypot(img_x,img_y) plt.imshow(new.astype('int'),cmap='gray')

OUTPUT:

Conclusion

This article taught us the basics of Image gradient and its application in edge detection. Image gradient is one of the fundamental building blocks of image processing. It is the directional change in the intensity of the image. The main application of image gradient is in edge detection. Finding the change in intensity can conclude that it can be a boundary of an object. We can compute the gradient, its magnitude, and the orientation of the gradient manually. We usually use filters, which are of many kinds and for different results and purposes. The filters discussed in this article are the Roberts filter, Prewitt filter, and Sobel filter. We implemented the code in OpenCV, using all these 3 filters for computing gradient and eventually finding the edges.

Some key points to be noted:

Image gradient is the building block of any edge detection algorithm.

We can manually find out the image gradient and the strength and orientation of the gradient.

We learned how to find the gradient and detect edges using different filters coded using OpenCV.

A Guide To Google’s Advanced Image Search

Searching for images on Google is a simple process.

Many of us can quickly find a picture of something we are searching for by performing a basic Google image search.

This is the standard image search functionality that most of us are used to seeing when we’re looking for a photo on Google.

It is an extremely common search result format, that clearly layouts and categorizes various types of image results.

Advanced Search Filters

By navigating to chúng tôi you can start to perform your standard image search.

The basic search bar appears for you to enter your query.

You can filter image results in the following ways:

Image Size

Here you can choose from large, medium, small, or an icon.

This can help to quickly locate an image based on the specific size you are after.

Whether it be a larger “hero” image or a smaller thumbnail, this feature can make it a speedier process to specify sizes.

Image Color

You have the option of black and white, transparent, or a specific color such as blue, red, yellow, etc.

This can help to easily narrow down an image search to pick up on any certain tones or colors you’re after.

Say you are writing a blog post on beach vacations, and want some images with light blue water, you can quickly find those using this filter.

Image Usage Rights

Labeled for reuse with modification, labeled for reuse, labeled for noncommercial reuse with modification, labeled for non-commercial reuse.

This is helpful in order to easily identify what photos are up for reuse and which ones are not.

Image Type

Options include clip art, line drawing, and GIF.

This can help to easily locate images based on animation or illustration type.

Time

Options include the past 24 hours, past week, past month, past year.

This can help to pin down more recent photos that may be more relevant, dependent on the topic you are after.

Google Advanced Image Search

Now, by navigating to Google’s Advanced Image Search, you will find that this tool uses all of the filters listed above, and then some.

If you still cannot find a specific image that you are after with the basic filters, this is a great tool to try.

This Exact Word or Phrase

This option lets you find images after inputting multiple keywords, to narrow down and specify your search further.

This is very similar to using quotes when searching for something online.

Aspect Ratio

This feature allows you to search specifically for certain image aspect ratios.

So, if you wanted to see an image that should be wide, tall, panoramic, etc., you can find those images here.

Region

This feature allows you to see which photos are public in a specific part of the world.

This makes it easy to pin down photos from places you plan to visit, etc.

Site or Domain SafeSearch

Enable or disable SafeSearch to block inappropriate content.

File Type

If you are after specific file types, you can pick which image file format Google should look for (e.g., JPG, PNG, SVG).

Reverse Image Search

By going to chúng tôi and then selecting “images” in the top right corner, you are brought to Google’s reverse image search.

Now, when you select the camera icon, you can then search for other images by uploading an image.

You can either place an image URL or upload your own specific image.

This is useful for a few different reasons.

Refine & Narrow Your Search

A reverse image search can help you find images that fit a granular set of search criteria, saving you time scrolling through hundreds of images to locate what you’re after.

It helps to refine and narrow your search, creating a better overall user experience.

Pinpoint Image Sources

Say you had saved an image of something when you were searching – for instance, an in-end table that you had been interested in.

You saved the image to your computer, however, cannot remember what website you had pulled it from.

Performing a reverse image search can help you to quickly pinpoint the source.

This can save you a lot of time and hassle, for various types of search results.

Integrate Advanced Image Search

There are billions of image searches happening every day.

Yet, many don’t know the full functionality and capabilities that Google offers for performing more robust image searches.

Utilizing these capabilities can help you save a significant amount of time, especially when searching for a specific image, or certain parameters that an image needs to meet.

More Resources:

Image Credits

All screenshots taken by author, July 2023

A Guide To Linkedin Single Image Ad Retargeting

LinkedIn has pleasantly surprised its users by steadily rolling out new features in recent years.

These audiences are currently built based on the campaign level, only including individuals who meet the targeting criteria within the campaign(s) you’ve selected to be a part of the audience.

There are a couple of options to go either wide or narrow with your audiences.

You can also select a timeframe of engagement to include people in your audience.

Options include 30, 60, 90, 180, and 365 days.

You’ll likely want to think through the potential size of your target audience from the original campaign and the length of your sales cycle when deciding what duration to choose.

You could also build audiences of various lengths to stagger various future retargeting messages based on the duration of their initial engagement with your ad.

Benefits Of Engagement-Based Retargeting

You’ve likely heard the acronyms from the progression toward a cookieless web – for example, GDPR, CCPA, and ITP.

Remember FLoC?

Pixel-based retargeting audiences continue to become less reliable as mobile OS and browser restrictions decrease the ability to track users.

On the flip side, first-party platform data has become more valuable.

By expanding opportunities for in-platform engagement retargeting, LinkedIn instantly offers a way to build audiences from individuals who otherwise might not enter pixel-based retargeting.

Additionally, paid search has become more focused on audiences, with loosened match types and increased machine learning, and less on targeting very specific keywords.

Supplementing a search with paid social becomes increasingly valuable to ensure you reach your target audience across multiple channels.

Effectively, you’ve now built yourself a list of people associated with your prime target accounts who are also interested in your content based on their behavior.

You can also either enlarge an audience by including multiple campaigns or stick to segmenting different audiences by individual campaigns, depending on how you’d like to set up future retargeting.

Full-Funnel Campaign Approach

For instance, a top-of-funnel campaign could contain sponsored content linking users to blog articles related to your industry.

Since you’ve already warmed them up with initial content, in theory, you can preselect individuals who have expressed some level of interest in your products.

At a minimum, even if you don’t have immediate plans to build a future campaign, set up a retargeting audience anytime you set up a single image ad campaign.

You’ll then have the audience ready to go if you want to use it in the future.

Audience Exclusions

Using engagement-based audiences directly for targeting can also be useful for exclusions.

Additionally, if you’re shifting people to a mid-funnel offer campaign such as an asset, you can avoid crossing wires by continuing to show them higher funnel content and focusing on keeping lead gen-focused messaging in their feed.

Exclude the ad engagers in the original campaign while targeting them in the lead gen-oriented campaign.

Start Targeting!

Now that you’re familiar with the ability to create single image ad retargeting audiences on LinkedIn start thinking of ways to implement it in your ad account.

Think through the persona you want to reach; you may want to cast a wide enough net to allow cost efficiency, knowing you can narrow it down to the individuals who directly express interest.

Create your audiences, let them start building, and begin retargeting them to take additional action.

More resources:

Featured Image: Abel Justin/Shutterstock

What Is A Roblox Slender And Who Created It?

It has been over a decade since the creepy Slender Man became an internet sensation. From scaring kids to inspiring Roblox horror games, it has played a variety of roles in the gaming community. But now, it’s making a comeback as a unique fashion statement in one of the most popular video games in the world. And unless you want to miss out on this trend, you must learn what is a Roblox Slender and how to make the most out of this in-game avatar. With that said, let’s dive into the world of Roblox Slender.

What is a Roblox Slender?

Slenderman from the 2023 Movie

Slender in Roblox refers to players that follow a goth-punk style with their characters alongside a thin and extra tall body. Most of the time, you will see Roblox Slender with a male body type, but female Slenders aren’t that rare either.

These players try to mimic the dark clothing style and the elongated body of Slender Man, often with long hair. But instead of copying the exact look of Slender Man, they also include elements from their personality to stand out.

Who Created Slenders in Roblox?

If we were to go into the specifics, the Roblox community speculates that a player named “3bwx” created the Slender trend to overshadow the Ro Gangsters trend in Roblox and gain popularity. Others, however, believe that it was the player “TheNarrowGate” who created the first Slender avatar and started the trend as others started copying them.

That’s not all. Some other player names that pop up in the discussion are “SharkBlox” (as per a Reddit discussion) and KhandyParker, who were using the Roblox Slender character before its widespread popularity.

Different Body Types in Roblox

Before we look at how to create and customize your Roblox character to look like a Slender Man, you first need to know about the different body types in the game. If you play the game regularly, you might already know that Roblox has two main types of body types:

R6: Classic blocky body made up of cubes and cuboids

R15: Realistic body with human-like features

In the R6 body type, you can only customize the limbs, torso, and head in a limited way. But R15 allows you to edit all parts of your limbs that can be moved or animated. With that, you can guess that the R15 is the perfect body type for creating your version of Roblox Slender.

Characteristics of Roblox Slender

Your Roblox body should have the following settings to turn it into a Slender:

Height: 105%

Width: 100%

Head: 100%

Proportions: 0

Body Type: 100%

If you don’t know how to customize your Roblox character, you can use our linked guide to get a quick tutorial. Moreover, in some versions of Roblox, you don’t get numerical toggles and sliders. There, you have to match the slider as per the following screenshot:

Your character’s body should be as thin and as tall as possible. Then, once the body is ready, you need to apply the right set of clothing and accessories and complete the look. We suggest the following accessories:

Plain Black Shirt

Plain Black Pants

Black High-Wested Sweats

Stitch Face

Short Layered Hair

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