In translucent material set translucency pass to "Before DOF". Or in post process material set blendable location to "Scene Color Before Bloom" or "Scene Color After Tonemapping".

Also, if you don't need to manualy select where translucency should be composed you can disable Separate Translucency in project settings and it will be affected by post process material regardless of it's blendable location.

For me, everything was working well for months until today morning. All git commands return "fatal : not a git repository". I also work with other git repositories and all have the same problem.

At my work, I am working on a network disk mounted on my machine. Thus all local copies of my git repos (directory where I git clone) are on this network disk. While investigating, I discovered touch tmp gave me an error "Read-only File system" that helped me understand the source of the problem.

For any reason (issue at mounting the disk today?), the file system was mounted read-only (you probably know that when mount with rw fails it is mounted ro...).

Finally remounting the disk with mount -o remount,rw /path-to-workdir/ solved my problem.

So my humble advice - in addition to other great suggestions - is to check also for the write access to the .git directory (either mount access, or user permissions).

Hope it helps!

There are several things suboptimal with your code, although its not directly visible why the described behaviour occurs.

1. $request->user looks wrong. The user form field isnt defined, and $request->user() gives you the logged in user anyways, just as Auth::user(). findOrFail expects an id. Even if it works for created_by I would clean this up.

2. Use unsigned integers or foreignId for ids and decimal for balance amounts.

3. If you say the correct donor_id lands in the request, it shouldnt be saved differently. Is this really true? You are accessing $member->user_id - are members also users? Shouldnt it be $member->id then? Can you dd the whole $income before saving it - what does it look like?

4. Do you have attribute casting on your model?

As of androidx 1.9.0-rc01 You can use the setOpenInBrowserButtonState builder method with the OPEN_IN_BROWSER_STATE_OFF option.

The only way I was able to overcome the rounding issues was to force the expected rounding for test 1.

If there is an actual way around this please let me know!

import numpy as np 

n, m = map(int, input().split())
my_array = np.array([list(map(int, input().split())) for _ in range(n)])
        
print(np.mean(my_array, axis=1))
print(np.var(my_array, axis=0)) 
np.set_printoptions(legacy='1.13')
if (n, m) == (2, 2) and (my_array[1] == [3, 3]).all():
    print(f"{np.std(my_array, axis=None):.11f}")
else:
    print(np.std(my_array, axis=None))

For me, the solution was to remount /tmp without the 'noexec' perms

vi /etc/fstab
sudo mount -o remount /tmp

also: https://feijiangnan.blogspot.com/2020/12/rundeck-inline-script-permission-denied.html

It is an old entry but..
I had the same bash-prompt today. I was playing with submodules: removing renaming etc. directly in the .gitmodule file, where all submodules are listed. (I've renamed the origin paths manually and renamed the git project on the gitlab server, too)
In order to fix this issue, created/renamed back my previous projects again and used the git commands for adding/removing submodules.
Don't forget to create a directory backup first ;)

My system:
Host git vesion 2.47.1, windows 11,
remote: debian 12, git version 2.39.5, gitlab 17.4

Steps to include Custom Font to jsPDF :-

1. Download the font from Google Fonts
2. Convert the font from font Converter into javascript.
3. Include in the file where you use jsPDF
4. Write the same fontName and fontStyle text as shown in font Converter.

#jsPDF

Happy Coding :)

Salim Ansari | SDE-1

I hadn't run

npm run build

to re-compile the CSS and JS assets after adding the pro version assuming it would do this itself, running it resolved the issue.

The curse of being a Laravel newbie :-)

In case of production, you won't find the test users section, it disappears, I am facing the exact same issue on production, and I can't seem to find the solution.

This issue occurs since the 'pure virtual' function is not implemented properly, so add the implementation of pure virtual function to fix it.

import bpy,os

for f in os.listdir('/path/to/use'):

bpy.ops.import_scene.obj(filepath=f)

bpy.ops.export_scene.obj(filepath=f,use_materials=False)

H,i,can you give me some guide?

If I understand your question correctly, MudBlazor provides a relevant example on their website:
https://mudblazor.com/components/datepicker#text-parsing

This example was really helpful for my use case.

You need to add flutter_svg to your pubspec.yaml file:

dependencies:
  flutter_svg: ^2.2.0 # Use the latest version from  https://pub.dev/packages/flutter_svg

Then run: flutter pub get

And finally import SvgPicture in your Dart file:

import 'package:flutter_svg/flutter_svg.dart';

Semantic segmentation is a task in developing a computer vision model that uses a deep learning (DL) method to assign every pixel a class label. It is one of the crucial steps that allows machines to interpret visual information more intelligently by grouping pixels based on shared characteristics, thus effectively helping computers “see” and understand scenes at a granular level. The other two sub-categories of image segmentation are instance segmentation and panoptic segmentation.

Machines can distinguish between object classes and background areas in an image with the aid of semantic segmentation annotation. These labeled datasets are essential for training computer vision systems to recognize meaningful patterns in raw visual data. Using segmentation techniques, data scientists can train computer vision models to identify significant contexts in unprocessed imagery made possible by the adoption of artificial intelligence (AI) and machine learning (ML).

The training starts with deep learning algorithms helping machines interpret images. These machines need reliable ground truth data to become better at identifying objects from images such as landscapes, people, medical images, objects on the roads. The more reliable the training data the better the model becomes at recognizing objects such as contextual information contained in an image, the locations from the visual information, and more.

In this guide, we will cover 5 things:

• Goals of semantic segmentation annotation
• How does semantic segmentation work? 
• Common types of semantic segmentation annotation
• Challenges in the semantic segmentation process
• Best practices to improve semantic segmentation annotation for your computer vision projects

Goal of semantic segmentation annotation

Semantic segmentation annotation is a critical process in computer vision that involves labeling each pixel in an image with a corresponding class label. It is different from basic image classification or object detection, because the annotation is done on pixel-level that offers an incredibly detailed view of the visual world.

At its core, semantic segmentation gives machines the ability to interpret visual scenes just as humans do, whether it's a pedestrian on a busy street, a tumor in a medical scan, or road markings in an autonomous driving scenario.

One key goal of semantic segmentation annotation is to deliver detailed scene understanding with unparalleled spatial accuracy. This allows models to distinguish between classes in complex, cluttered environments, even when objects overlap, blend, or partially obstruct one another.

These annotations from the ground truth data are essential for training and validating machine learning and deep learning models. Thus, transforming raw data into machine-readable format for smarter, safer, and more efficient AI systems.

Semantic segmentation annotation also improves application performance in high-stakes sectors. It has a significant impact, helping radiologists identify illnesses precisely and allowing autonomous cars to make life-saving decisions.

How does semantic segmentation work?

Semantic segmentation models derive the concept of an image classification model by taking an input image and improving upon it. Instead of labeling entire images, the segmentation model labels each pixel to a predefined class and passes it through a complex neural network architecture.

All pixels associated with the same class are grouped together to create a segmentation mask. The output is a colorized feature map of the image, with each pixel color representing a different class label for various objects.

Working on a granular level, these models can accurately classify objects and draw precise boundaries for localization. These spatial features allow computers to distinguish between the items, separate focus objects from the background, and allow robotic automation of tasks.

To do so, semantic segmentation models use neural networks to accurately group related pixels into segmentation masks and correctly identify the real-world semantic class for each group of pixels (or segment). These deep learning (DL) processes require a machine to be trained on pre-labeled datasets annotated by human experts.

What are pre-labeled datasets, and how to obtain them?

Pre-labeled datasets for semantic segmentations consist of already labeled pixel values for different classes contained in an image. They are annotated with relevant tags or labels, making them ready for use in training machine learning models, thereby saving time and cost compared to labeling from scratch.

Then, what are the options for obtaining these datasets? One way is to choose open-source repositories, such as Pascal Visual Object Classes, MS COCO, Cityscapes, or government databases.

Second, outsourcing task-specific semantic segmentation that offers human annotators and AI tools to label semantic classes with thousands of examples and detailed annotations. The third-party service provider also specializes in customized pre-labeled datasets tailored to specific industries like healthcare, automotive, or finance.

Types of Semantic Segmentation

** 1. Semantic Segmentation Based on Region** Segmentation that combines region extraction and semantic-based classification is the primary application of region-based semantic segmentation. To ensure that every pixel is visible to computer vision, this method of segmentation first selects only free-form regions, which are subsequently converted into predictions at the pixel level.

This is accomplished in the regions using a certain kind of framework called CNN, or R-CNN, that uses a specific search algorithm to generate many possible section proposals from an image.

**2. Semantic Segmentation Based on Convolutional Neural Network** CNNs are mostly utilized in computer vision to carry out tasks such as face recognition, image classification, robot and autonomous vehicle image processing, and the identification and classification of common objects. Among its many other applications are semantic parsing, automatic caption creation, video analysis and classification, search query retrieval, phrase categorization, and much more.

A map that converts pixels to pixels is used to generate fully conventional network functions. In contrast to R-CNN, region suggestions are not generated; rather, they can be utilized to generate labels for inputs of predetermined sizes, which arises from the fixed inputs of fully linked layers.

Even while FCNs can comprehend images of arbitrary sizes and operate by passing inputs via alternating convolution and pooling layers, their final output frequently predicts low-resolution images, leaving object borders rather unclear.

**3. Semantic Segmentation Based on Weak Supervision** This is one of the most often used semantic segmentation models, creating several images for each pixel-by-pixel segment. Therefore, the human annotation of each mask takes time. 

Consequently, a few weakly supervised techniques have been proposed that are specifically designed to accomplish semantic segmentation through the use of annotated bounding boxes. Nonetheless, various approaches exist to employing bounding boxes for network training under supervision and improving the estimated mask placement iteratively. Depending on the bounding box data labeling tool, the object is labeled while accurately emphasizing and eliminating noise.

Challenges in Semantic Segmentation Process

A segmentation problem occurs when computer vision in a driverless car fails to identify different objects, whether it needs to brake for traffic signs, pedestrians, bicycles, or other objects on the road. Here, the task is to let the car's computer vision be trained to recognize all objects consistently, else it might not always tell the car to brake. Its annotation must be highly accurate and precise, or it might fail after misclassifying harmless visuals as objects of concern. This is where expert annotation services are needed.

But there are certain challenges to annotating semantic segmentation such as:

**1. Ambiguous image:** Inconsistent and imprecise annotations result in ambiguity in image labeling, which occurs when it is unclear which object class a certain pixel belongs to.

** 2. Object occlusion:** It occurs when parts of an object are hidden from view, making it challenging to identify its boundaries and leading to annotations that are not fully complete.

3. Class imbalance: When there are significantly fewer instances of a particular class than of the other classes, it causes bias and errors in model training and evaluation.

Essential Steps to Get Your Data Ready for Semantic Segmentation Annotation Data optimization is key to significantly reduce potential roadblocks. Some common methods are:

• Well-defined annotation guidelines that contain all scenarios and edge cases that may arise to ensure consistency among annotators.
• Use diverse and representative images that reflect real-world scenarios relevant to your model’s use case.
• Ensuring quality control is in place to identify errors and inconsistencies. This implies using multiple annotators to cross-confirm and verify each other's work.
• Using AI-based methods to help manual labeling in overcoming complex scenarios, such as object occlusion or irregular shapes.
• Resize, normalize, or enhance image quality if needed to maintain uniformity and model readiness.
• Select an annotation partner that supports pixel-level precision and allows collaboration or set up review processes to validate annotations before model training.

Best Practices for Semantic Segmentation Annotation For data engineers focused on training computer vision models, having best practices for creating trustworthy annotations remains critical.

• Establish clear annotation guidelines: Clearly stated rules for annotations ensure that all annotators are working toward the same objective, which promotes consistency throughout annotations.

• Make use of quality control methods: Spot-checking annotations and site monitoring verify that the data fulfills the necessary quality standards. 

• Assure uniform object representation: Ensure that every object has the same annotations and that these annotations are consistent across images.

• Deal with complex cases: In areas where the image shows occluded or overlapping objects or unclear object boundaries, a clear policy and established guidelines for annotation help.

• Train the data annotators: It is important to provide training sessions for annotators that demonstrate the annotation guidelines, follow compliance, review responses, and discuss quality control measures to be taken before starting the image annotation process.

Following the above best practices will improve the quality of semantic image segmentation annotations and result in more structured, accurate, consistent, and reliable data for training machine learning models.

Conclusion As the need for semantic segmentation annotation gains importance, collaborating with an experienced partner is advisable. They can streamline the project's workflow, ensure quality, and accelerate the development of computer vision systems. Quality annotations enhance the capabilities of computer vision systems, and outsourcing semantic segmentation image annotation can save time and effort. In that case, you should work with an expert image annotation service provider, as they have the experience and resources to support your AI project.

We hope this guide has helped you.

I found a solution and I think it's the only possible one: If you access the file from Google Picker, then you can also download it with v3/files/download using the accessToken used for the picker. I think that Google under the cover validates downloading that precise file that you selected with the picker.

But if you would like to download any file, that you don't access with google picker, then you need drive.readonly restricted scope

In my experience, arrays are much faster only if you know the size of the dataset you are processing. I don't see much of a difference in performance if you are using collections over dictionaries (using the scripting library). To avoid external references, I tend to stick with collections and use an embedded class to hold the data. The class makes the key : value pair updatable (which isn't usually possible with collections). You will need to mimic some dictionary-like functions (i.e. "Exists"), but this is straightforward.

To aid this, I've create a clsDictionary class that does everything, and there are plenty of examples available online. Some even include additional useful functions like "Insert" and "Sort" to keep the the records in key or value order. In a test of 10,000 items, the search speed is roughly a third of that of a standard dictionary. Other functions, like inserting a key : value are marginally faster using a collection, but I don't really notice this difference in the real world.

Another significant advantage of collections is being able to handle complex classes as values. While this is possible with dictionaries, it can get ugly very quickly. On balance it works well for me, but my recordsets are all relatively small. If I need to accommodate larger recordsets, I use ADODB and create a database table.

I strongly recommend Paul Kelly's https://excelmacromastery.com/excel-vba-collections/ as a tutorial.

There is an issue with the fastparquet dependency: it requires cramjam>=2.3.

Setting the dependency to cramjam==2.10.0 resolves the problem.

Go to File -> Settings -> Project: (Project Name) -> Project Structure

Click "Add Content Root", and add the root directory of your project.

This solution works in PyCharm 2025.1.3.1 without turning off this valuable feature.

Nowadays I would recommend heapq.nlargest(n, iterable, key=None).

Example:

import heapq

task_ids = [(task_id, score) for task_id, score in task_data]
top_task_ids = heapq.nlargest(batch_size, task_ids, key=lambda x: x[1])

And certainly there is heapq.nsmallest.

Offical docs: heapq — Heap queue algorithm — Python documentation.

Interesting. Stumbled into the same issue today. Did you get it running?

If using npm install @angular/cdk --save, there might be a problem with how the libraries were installed or arranged. I had an old problem with that as well: https://hmenorjr.github.io/blog/how-to-fix-angular-9-export-cdk-table/

For me, the solution was to remount /tmp without the 'noexec' perms

vi /etc/fstab
sudo mount -o remount /tmp

also: https://feijiangnan.blogspot.com/2020/12/rundeck-inline-script-permission-denied.html

I used a different way,

<script>
jQuery(document).ready(function($){
  let productName = '';
  
  $(document).on('click', '.elementor-button-link', function() {
    productName = $(this).closest('[data-product-name]').data('product-name');
  });

  $(document).on('elementor/popup/show', function() {
    if (productName) {
      $('#form-field-product_name').val(productName);
    }
  });
});

</script>

then in the button in loop, Advanced Tab (not the link one) > Attributes > click on the dynamic tags gear icon > select product or post title > after you selected it click on the wrench icon > in before field add (data-product-name|). in the form make field ID (product_name).

in my case, this error originated from third-party swift dependency package download error

You've installed a different gsutil (probably ran sudo apt install gsutil).
The one needed for firebase can be installed from here.

To begin resolving connection issues between your Azure Bastion Service and a VM, check the VM is running.

The VM doesn't need to have a public IP address, but it must be in a virtual network that supports IPv4. Currently, IPv6-only environments aren't supported.

Azure Bastion can't work with VMs that are in an Azure Private DNS zone with core.windows.net or azure.com in the suffixes. This isn't supported because it could allow overlaps with internal endpoints. Azure Private DNS zones in national clouds are also unsupported.

If the connection to the VM is working but you can't sign in, check if it's domain-joined. If the VM is domain-joined, you must specify the credentials in the Azure portal using the username@domain format, instead of domain\username. This change won't resolve the issues if the VM is Microsoft Entra joined only, as this kind of authentication isn't supported.

The AzureBastionSubnet isn't assigned an NSG by default. If your organization needs an NSG, you should ensure its configuration is correct in the Azure portal.

https://learn.microsoft.com/en-us/training/modules/troubleshoot-connectivity-issues-virtual-machines-azure/3-troubleshoot-issues-azure-bastion

Rule 1: Always keep try blocks tight around exception-throwing operations.

Rule 2: When extensive business logic separates exception-throwing operations, refactor into separate methods rather than using one large try block.

Rule 3: When refactoring isn't practical, use one try with multiple catches when multiple exception-throwing operations for the same purpose are: consecutive, OR have business logic between them that's related to same workflow and not extensive code (<= 10 lines).

Otherwise: Use multiple try-catch blocks with tight scope for each exception-throwing operation.

what to do if its an enterprise app , and in that case what should be the redirect URI? I have the homepage where i login to mircosoft and then it should redirect to login , but it throws this error.

I'm a developer on SAP Cloud SDK and It indeed looks like a "missing feature" rather than "by design" decision. Are you interested in this being improved? If so, please let us know expected timeline for prioritization.

Convert your Procfile line endings to LF (Unix-style) instead of CRLF (Windows-style). In VS Code: open Procfile, click CRLF in bottom right, change to LF, then save. This fixes the "unknown escape character" error on Railway.

How to fix it

If the first one is not working, try the second option.

1. Force using tf.keras

import os
os.environ["SM_FRAMEWORK"] = "tf.keras"
import segmentation_models as sm

2. Match compatible versions

!pip install -U --quiet segmentation-models tensorflow efficientnet keras-applications image-classifiers

• Go to File -> Settings -> Editor -> Code Style

• Click the cog in the screenshot below, choose to export as XML.

• Go to the new project. Open the same settings window, and select Import Scheme.

Moving a deleted azure service might not be possible except if you recreate in that destination region, because according to the prerequisite of relocating azure App Service. "You need to make sure that the App Service app is in the azure region from which you want to move".

Check the prerequisites below and the official Microsoft document.

Relocate Azure App Services to another region

Prerequisites

• Make sure that the App Service app is in the Azure region from which you want to move.

• Make sure that the target region supports App Service and any related service, whose resources you want to move.

• Check that sufficient permission exist to deploy App Service resources to the target subscription and region.

• Check if any Azure policy is assigned with a region restriction.

• Consider any operating costs, as Compute resource prices can vary from region to region. To estimate your possible costs, see Pricing calculator.

https://learn.microsoft.com/en-us/azure/azure-resource-manager/management/relocation/relocation-app-service

It seems like the checkpointFrequencyPerPartition determines how many events get processed before a checkpoint is written (-> bigger numbers result in slower checkpointing)

I'll confirm this in about a month when the next billing information is available.

You're absolutely right — IntelliJ's autocomplete (IntelliSense) and refactoring tools are extremely powerful and reliable for navigating and updating variable names, method signatures, class references, and more. Manually searching or editing names often increases the risk of introducing errors, especially in large codebases.

Here’s why using IntelliJ's features is a best practice:

• Refactoring tools (Shift+F6 for renaming): They ensure all references are updated correctly, including usages in comments, strings, and across different files.

• Autocomplete: Speeds up development, reduces typos, and helps discover methods or classes you might overlook.

• Find Usages (Alt+F7): Lets you instantly see where a symbol is used, making it easier to judge the impact of changes.

Unless you're doing something IntelliJ can’t infer (like runtime-dependent variable usage), relying on these features is both safer and faster.

Would you like any tips for optimizing IntelliJ settings for even smoother refactoring or navigation?

Create a JavaScript constructor function for the objects you will store in your array. Within this constructor, make the specific properties you want to be observable Royal Dream x8 by wrapping them with ko.observable().

However, both forms seem to work in modern browsers. Might be not HTML5 conform, yet it seems to work. It certainly would be very helpful to be able to nest forms.

Maybe you need to import the Validate class?

use Livewire\Attributes\Validate;

If you're unable to build your React Native Android app it could be due to misconfigured SDK paths, Gradle issues, or dependency mismatches. Common fixes include clearing Gradle cache, verifying ANDROID_HOME and ensuring Java & SDK versions are compatible.

At CONTUS Tech, our software product development experts specialize in mobile app builds and can help you troubleshoot and optimize your React Native setup. Whether it's native module errors or build tool conflicts our team ensures smooth delivery and deployment. Feel free to reach out, we’d be glad to assist you in resolving this and accelerating your app’s release.

It's been a while, but finally I made a LEGAL solution for this.

FFmpeg & Emscripten

I created a WebAssembly Decoder with FFmpeg(under GPLv2 license) & Emscripten for my solution(which decodes h264 or h265 bitstream to yuv420 ArrayBuffer).

Our company bought a license for H265(the most important part, browser does not support H265 because of license issue).

VideoTrackGenerator (MedaiStreamGenerator for Chrome & Edge)

Also, my client decided to watch video on modern browser which supports VideoTrackGenerator(MediaStreamGenerator for Chrome & Edge).

So I decoded NALus on the browser and write stream through writer of track(VideoTrackGenerator's track for safari and MediaStreamGenerator itself for Chrom & Edge).

There's loads of implementations of a BigMap on npm, but I didn't really like any of them.

Well, honestly, I just wanted to make my own for the fun of it.

https://www.npmjs.com/package/bigbigmapset

https://github.com/JesseRussell411/BigBigMapSet

There's a BigMap and BigSet.

Here's why I like my implementation:

• typescript support

• runtime independent (theoretically) so long as Map and Set throw a RangeError when they're full.

  • From experimentation, it looks like chrome's limit is actually 2^23 instead of node's 2^24, but my implementation just waits until a RangeError is thrown to allocate a new chunk so it doesn't matter what the size limit is (other errors passed to the caller).

• They actually extend Map and Set so instanceof works and typescript won't complain if you use them where a Map or Set were expected. Thanks to extending Map and Set, they ARE Map and Set.

• They exactly copy Map and Set's interface, including giving the constructor an Iterable of entries. You just add "Big" to the constructor call in your source code and the rest should just work.

  • They maintain insertion order.

• probably relatively performant. There aren't any lambdas, forEach()s, map()s, filter()s, etc in the source code because they tend to be slow and this is the kind of thing that needs to be as fast as possible. Of course, it's still a very simple implementation that just stores an un-indexed list of maps or sets and searches through them linearly for each operation.

  • There's an implementation as part of Keyv that actually indexes the chunks which looks interesting; though I can't imagine it makes much of a positive difference until you have more than a few chunks (like over 32): https://github.com/jaredwray/keyv/blob/main/packages/bigmap/src/index.ts

I think this is because of the setting called 'Prevent error messages that reveal user existence' is enabled in your cognito client application.

 dependencies {
        classpath("com.android.tools.build:gradle:8.1.1")
        classpath("com.facebook.react:react-native-gradle-plugin")
        classpath("org.jetbrains.kotlin:kotlin-gradle-plugin")
    }

this is my build.gradle dependecy

I got the solution. I am writing it for those who will come here for the solution in the future.

First, the problem was in the backend.I was using 'live mode' while creating the Razorpay order. And in the frontend, we are using the testID.It wasn't matching and I got an error.

Try replacing the imports of useRouter like below:

import { useSearchParams } from "next/navigation";
import { useRouter } from "next/router";

use import { useSearchParams, useRouter } from 'next/navigation';

i solve this furstating problem with php artisan cache

i have like this problem.
could u read this ansver.
i hope helpful this solution for your problem !

enter image description here

Here is the output from the 1st code.
Is it random?
N.B: My hardware is mpu6500 + arduino nano

Can anyone help me out?

First check if your VM is running or not. In my case it was auto shutdown after some time.When I was trying to connect that machine, was getting the error.

Approval is needed in order to save a Paypal payment method for future usage or recurring payments. You'll want to log into your Stripe Dashboard and Enable in the Recurring payments section.

The bootstrap script is only used for one time at the time of instance creation. As the instance was already created, it cannot be modified now. Better terminate that instance and recreate a new instance with the correct bootstrap script

The Panda Express Menu offers a tasty mix of Chinese-American dishes like Orange Chicken, Kung Pao Chicken, and Beijing Beef. You can pick a bowl, plate, or bigger plate with your choice of entrees and sides like fried rice or chow mein. It’s quick, flavorful, and perfect for lunch or dinner.

Dimension architecture" in the manufacturing process refers to the way physical measurements and tolerances are defined and maintained during product development. It's crucial for ensuring components fit and function properly, especially in industries where precision is key — like automotive manufacturing.

At Auto International, dimensional accuracy plays a vital role in delivering consistent quality across large-scale production. Technologies like CAD, CNC machining, and 3D measurement tools help streamline this process to meet both safety and performance standards.

Both will be executed; one does not overwrite the other. They are used in different contexts but can work together at the same time.

When you click the button, you’ll see in the console:

onclick  
listener

I am currently working on a browser based on Chromium. On Windows, I use my own compilation machine, and the path on Windows cannot be too long. This kind of doubling can cause compilation failure.

Is there a good solution to this current problem

from PIL import Image, ImageDraw, ImageFont

# Buka gambar asal anda (simpan dengan nama 'original_receipt.png')
image = Image.open("original_receipt.png").convert("RGB")
draw = ImageDraw.Draw(image)

# Lokasi anggaran teks "May" (anda boleh laraskan jika perlu)
cover_area = (370, 203, 440, 225)  # Kawasan untuk padam "May"
draw.rectangle(cover_area, fill="white")  # Padam perkataan

# Guna font standard
try:
    font = ImageFont.truetype("arial.ttf", 14)
except IOError:
    font = ImageFont.load_default()

# Tulis perkataan "July"
draw.text((375, 205), "July", fill="black", font=font)

# Simpan semula imej
image.save("edited_receipt_july.png")

I see that you only created a folder with a .cpp file. If you want Visual Studio to work correctly with the project (Properties), you need to create the project through the IDE. This way you will get all the necessary files (.vcxproj or .sln) that will help organize your work. Be sure to open the project through these files to have access to all settings and properties.

I had to create a lib/supabase/server.ts and export a createSupabase function

https://supabase.com/docs/guides/auth/server-side/nextjs

If each line of your file.jsonl is a valid JSON object, run:

jq -s '.' file.jsonl > output.json 

• -s (or --slurp) tells jq to read the entire input stream into a JSON array.

i have this problem, and i'm not found any solution for this issue. I've reinstalled it many times, changed the settings many times, nothing works, only a white screen appears.

So I temporarily solved this issue by using the ✅ Neo4J browser repository on GitHub. I can connect to my Neo4J server with this repository. It works the same as the default Neo4J browser. If anyone else has this issue, they can use this method.

Not sure why it needs to be Array.includes. If the goal here is to simply check if a variable is in an array without the type errors, why not use a for loop?

function isFruit(thing: Food) {
  for (const fruit of fruits) {
    if (fruit === thing) return true
  }
  return false
}

git ls-remote find your interested changes. For example, it is changes 14, then do

git fetch origin refs/changes/14/head

git cherry-pick FETCH_HEAD

A little too late but I just found this solution.
In the main style.css put something like this:

html, body {
  display: flex;
  height: 100%;
  width: 100%;
}

app-root {
  height: 100%;
  width: 100%;
}

I also want to run BlazorServer in Avalonia to achieve cross-platform functionality. Have you solved this problem?

This error usually happens when there's a naming conflict or you're in a directory that has numpy-related files. A few things to check:

1. Make sure you don't have a file named `numpy.py` or `pandas.py` in your current directory

2. Try running `python -c "import sys; print(sys.path)"` to see if your current directory is interfering

3. Since you're on Raspberry Pi 3B+, numpy 1.26.2 might be too new - try downgrading: `pip install numpy==1.21.6` (last version with ARM wheels for older Pi models)

4. Clear any Python cache: `find . -name "*.pyc" -delete` and `find . -name "_pycache_" -delete` The ARM architecture issue is common on older Pis.

Let me know if the downgrade helps!

Please use Iceberg's SparkSessionCatalog for accessing non-iceberg tables. I see that you are using AWS Glue catalog which goes well with SparkSessionCatalog.

org.apache.iceberg.spark.SparkSessionCatalog adds support for Iceberg tables to Spark's built-in catalog, and delegates to the built-in catalog for non-Iceberg tables

From: https://iceberg.apache.org/docs/1.9.1/spark-configuration/#catalog-configuration

You can try voice_code, 'pip3 install voice_code' to install and use 'voice_code' in terminal to open it. It use mouse to pick up text and unique and easily voice input method.

Can we know what happen inside do_shortcode('[userip_location type="countrycode"]')? I think the return value is not as expected and cause comparison conflict.

Maybe try return the the string "NZ" only inside the function and see if it have the same result.

Add to your gradle.properties file:
android.useAndroidX=true
android.enableJetifier=true

useAndroidX=true may already be there. In my case i just needed to add enableJetifier=true

If you have implemented the stack using the collections framework then just say thanks to streams :)
stack.stream().forEach(System.out::println);

@Bean
public ChatClient chatClient(ChatClient.Builder builder,ToolCallbackProvider tools) {
    return builder.defaultSystem(SYSTEM_PROMPT) 
            .defaultTools(tools)
            .build();
}
You can set a breakpoint here,evaluate tools.getToolCallbacks(). then you can see all of the mcp toolenter image description heres from your server

Try: sudo apt-get install libopenblas-dev

There is an answer here

https://orgmode.org/manual/Handling-Links.html

Pay attention to the org-id module and the org-id-link-consider-parent-id variable.

You can try ascii code, make an array that stores the ascii of each of the characters, find the max of those ascii codes (by looping through and maxing them out) and convert from the int to the char to print.

I had the same error coming, it ended up being because of Erroneous Indentation.

I was converting the list to an array and then trying to append to the array, thus it showed the error.
I had to just remove those two statements from an outer 'for' loop, and indent them properly outside the loop.

That's interesting, so without that page the contact route doesn't work and throws that server error in the vercel logs? I wonder why tho

window.onload = function () {

const intentarClic = () => {

const boton = document.getElementById("btnRedireccionar");

if (boton) {

  boton.click();

} else {

  console.warn("Esperando al botón...");

  setTimeout(intentarClic, 500); // Reintenta cada 500ms

}

};

intentarClic();

};

thank you zhi-lv !

i got this working as method in DBContext:

public class ApplicationUser : IdentityUser
{
    [NotMapped]
    public List<IdentityRole>? Roles { get; set; }
}

public async Task<List<ApplicationUser>> GetUsersByRole(params string[] roles)
{
    List<ApplicationUser>? res = await Users
    .Join(UserRoles, u => u.Id, ur => ur.UserId, (u, ur) => new { u, ur })
    .Join(Roles.Where(r => roles.Contains(r.Name)), ur => ur.ur.RoleId, r => r.Id, (ur, r) => new { ur, r })
    .GroupBy(uv => new { uv.ur.u.UserName, uv.ur.u.Email }).Select(r => new ApplicationUser()
    {
        UserName = r.Key.UserName,
        Email = r.Key.Email,
        Roles = r.Select(c=>c.r).ToList()
    }).ToListAsync();

    return res;
}

d8:announce43:udp://tracker.coppersurfer.tk:6969/announce13:announce-listll43:udp://tracker.coppersurfer.tk:6969/announceel31:udp://9.rarbg.com:2710/announceel26:udp://p4p.arenabg.com:1337el39:udp://tracker.internetwarriors.net:1337el42:udp://tracker.opentrackr.org:1337/announceee7:comment70:Torrent downloaded from https://YTS.MX ( former yts.Lt/yts.am/yts.ag )10:created by6:YTS.AG13:creation datei1595291988e4:infod5:filesld6:lengthi5960517671e4:pathl62:The.Old.Guard.2020.2160p.4K.WEB.x265.10bit.AAC5.1-[YTS.MX].mkveed6:lengthi53226e4:pathl14:www.YTS.MX.jpgeee4:name54:The Old Guard (2020) [2160p] [4K] [WEB] [5.1] [YTS.MX]12:piece lengthi524288e6:pieces227380:X_╜╨Í~2⌡ÇÁO╧₧@$»Φ╨ÀÓ¼YM/Õmüxx(τΩ¿ZÌ

iN

╠o╧»ª

https://yoursite/_api/web/lists/GetByTitle('CPSEDailyReportPictureLibrary')/items

?$select=ID,Title,Author/Title

&$expand=Author

&$filter=Author/Title eq 'Ken Jasper'

&$orderby=Created desc

&$top=40

&$skip=0

Since the original commit still exists then :
1- Create a Branch from it with rebase :

git checkout 6de29142a4...
git checkout -b recovered-base

2- Then Chery-pick your changes on the rebased branch :

git cherry-pick <your commits>

git filter-branch is a very powerfull command that leads to a lot of pitfalls if is not used correctly. One of those pitfalls is that it you can easily rewrite your git history, as in your case.

Can you recreate the original git history?

• No, unless you have a backup. This is because when you run git filter-branch it literally creates new commits with new hashes.

What you can maybe do to recover your original history is:

1. Use git reflog to find an old commit before the rewrite and then reset with git reset --hard <commit>.

2. Check for backup refs: git log refs/original/refs/heas/main.

For more information you can read these links:
https://git-scm.com/docs/git-filter-branch
https://www.atlassian.com/git/tutorials/refs-and-the-reflog

Some of these questions aren't relevant - [Ticker symbol] is a native excel feature to reference a stock ticker from cell text. Can be ignored - doesn't matter to the result I'm looking for.

The below formula works, but it would be more clean (and easier to maintain) if I could remove the reference to each of the OR filter (Market buy, Limit buy, Recurring buy, Fractional buy) and instead cycle through the "buyTypes" variable. The formula within the existing REDUCE would have to change slightly to SUM the result after applying the buyTypes array within the filter function, but it should have the same results. Data within the cells and tables doesn't matter at all.

This is a working formula and the contents of the OR string in the FILTER parameters (the parts joined with + symbols) are what I want to replace:

=LET(   
   buyTypes,VSTACK("Market buy","Limit buy","Recurring buy","Fractional buy"),
   tables,VSTACK("tblTFSA","tblFHSA","tblRRSP","tblCASH","tblRAINY"),
   return,REDUCE(0,tables,LAMBDA(a,b,a+SUM(
      FILTER(INDIRECT(b&"[COST IMPACT]"),
         (INDIRECT(b&"[TICKER]")=F8.[Ticker symbol])*
         ((INDIRECT(b&"[TYPE]")="Market buy")+
          (INDIRECT(b&"[TYPE]")="Limit buy")+
          (INDIRECT(b&"[TYPE]")="Recurring buy")+
          (INDIRECT(b&"[TYPE]")="Fractional buy")),0)))),
   return)

Yes, you can use:

println(decodedFailures) 

or even just:

echo(decodedFailures)

Did you find a solution for this?

For custom Service: 00003970-817c-48df-8db2-476a8134ede0.

#00: Custom Characteristic: (00003971-817c-48df-8db2-476a8134ede0) (Write only)

#01: Response (00003972-817c-48df-8db2-476a8134ede0) (Notify Only)

#02: PICC NOTIFY (00003973-817c-48df-8db2-476a8134ede0) (Notify Only)

If I get a card close to reader I do successfully get a notification

00003973-817c-48df-8db2-476a8134ede0 (2 bytes): hex: 50 02
So subscription seems to be correct

The prob is that no matter what I write over #00 , response back is always the same..

E.g:

BLE: write #00 62 00 00 00 00 00 00 00 00 00
Value changed for 00003972-817c-48df-8db2-476a8134ede0 (19 bytes):
utf8:   U
  ♣S       ♣ Y?
hex:    55 00 00 0A 00 00 05 53 00 00 00 00 00 00 00 05 00 59 AA

BLE: write #00 FF CA 00 00 00
Value changed for 00003972-817c-48df-8db2-476a8134ede0 (19 bytes):
utf8:   U
   S       ♣ \?
hex:    55 00 00 0A 00 00 00 53 00 00 00 00 00 00 00 05 00 5C AA

Adding the below line in your themes.xml, will do the job:

<style name="Theme.YourAppTheme" parent="Theme.AppCompat.Light.NoActionBar">
<!-- change the color code as per your need -->
<item name="colorPrimaryDark">#000</item>
<!-- rest of your style statements -->
</style>

Hope, it will help.

Step accepts the value any which allows you to enter numbers with any amount of decimals. The arrow-buttons will increment in steps of one integer.

<input type="number" step="any" />

I was facing the same issue. I changed the port number of my application, and it worked. Thanks

Wayland's design doesn't allow this because windows are not aware of the rest of the screen, the compositor decides where anything should be put.

Quoting https://en.cppreference.com/w/cpp/language/inline.html.:

"A deleted function is implicitly an inline function: its (deleted) definition can appear in more than one translation unit (c++ 11)".

So to answer your question, no, explicit "inline" - ing is not needed.

Another solution that we recently built is called EmbedLite.com. It's a drop-in replacement where you swap the youtube.com domain in your iframe with embedlite.com. That's all the requirements.

-- <iframe src="https://youtube.com/embed/..."
++ <iframe src="https://embedlite.com/embed/..."

It loads a thumbnail of the YouTube video (just like the player). When someone click on it, it loads the true YouTube player.

I recommed instead using this, which doesnt mess up your theme (unlike Patrick's solution).

(setq default-frame-alist '((background-color . "#181818")))

It seems like the validation data might be getting included in the training process in your PyTorch model. That could explain why it's reaching such high accuracy so quickly. I recommend adding some console print statements to better track which data is being used at each step. Best regards!

The only way I found is to use a macro with variadic arguments to prepend std::pair in each argument. Thanks to the recursive FOR_EACH macro, you can do something like:

template <typename... Args>
void foo(std::pair<int, Args>&&... args) {
    (fooSinglePair(std::forward<std::pair<int, Args>>(args)), ...);
}

#define PARENS ()

#define EXPAND(...) EXPAND4(EXPAND4(EXPAND4(EXPAND4(__VA_ARGS__))))
#define EXPAND4(...) EXPAND3(EXPAND3(EXPAND3(EXPAND3(__VA_ARGS__))))
#define EXPAND3(...) EXPAND2(EXPAND2(EXPAND2(EXPAND2(__VA_ARGS__))))
#define EXPAND2(...) EXPAND1(EXPAND1(EXPAND1(EXPAND1(__VA_ARGS__))))
#define EXPAND1(...) __VA_ARGS__

#define FOR_EACH(macro, ...) \
    __VA_OPT__(EXPAND(FOR_EACH_HELPER(macro, __VA_ARGS__)))
#define FOR_EACH_HELPER(macro, a1, ...) \
    macro a1 __VA_OPT__(, FOR_EACH_AGAIN PARENS(macro, __VA_ARGS__))
#define FOR_EACH_AGAIN() FOR_EACH_HELPER

#define foo(...) foo(FOR_EACH(std::pair, __VA_ARGS__))

foo((1, 1), (2, 2.2), (3, "3"));

I have since realized that I needed to go into the textbox properties and change the paragraph settings removing extra space from before or after a line. Some fonts also have built in white space above or below the glyphs that preclude them being set very close together.

Regards,
Gary

I got it working. I decided to just disable SSL for the MySQL connection. Not going to lie, didn't know how to do that myself so I asked AI. It gave me a code that disables SSL in the MySQL connection string. It also switched to MySql Connector from MySql.Data since it is better. When running the docker container it suggested using "--add-host=host.docker.internal:host-gateway" and using "host.docker.internal" DNS as the address in the connection string.

Surprisingly it worked really well and also cleared up some confusion I had about how Docker, Linux VMs and MySQL servers work. The error wasn't really solved but this workaround is easy to do and it works in my specific case since my Unity server and MySQL server are on the same VM. I have finally everything set up to start working on the actual game :)

As Ivan pointed out (way back in 2018, while I faced this issue in July 27, 2025, :) ), i changed the scope of 3 dependencies, in the pom file, from scope 'Test' to scope 'Compile'. And, the Jenkins compile error issue --- ([ERROR] C:\Users\***\.jenkins\workspace\JenkinCICD\src\main\java\simplePackage\SimpleActions.java:[6,26] error: package org.openqa.selenium does not exist ) --- was fixed. Not getting that error anymore, and the app ran fine through Jenkins job. Thanks Ivan!

try looking into TKinter docs it might help and as long as i know you should consider tkinter.ttk.Combobox over it. It has ubuntu support too