Vern  Greenholt

Vern Greenholt

1596687780

Neural Style Transfer for Audio in Pytorch

They’ve been some really interesting applications of style transfer. It basically aims to take the ‘style’ from one image and change the ‘content’ image to meet that style.

But so far it hasn’t really been applied to audio. So I explored the idea of applying neural style transfer to audio. To be frank, the results were less than stellar but I’m going to keep working on this in the future.

For this exercise, I’m going to be using clips from the joe rogan podcast. I’m trying to make Joe Rogan, from the Joe Rogan Experience, sound like Joey Diaz, from the Church of Whats Happening Now. Joe Rogan already does a pretty good impression of joey diaz. But I’d like to improve his impression using deep learning.

Image for post

First I’m going to download the youtube videos. There’s a neat trick mentioned on github that allows you to download small segments of youtube videos. That’s handy cause I don’t want to download the entire video. You’ll need youtube-dl and ffmpeg for this step.

import os

# download youtube url using ffmpeg
# adapted from: https://github.com/ytdl-org/youtube-dl/issues/622#issuecomment-162337869
def download_from_url_ffmpeg(url, output, minute_mark = 1):

	try:
		os.remove(output)
	except:
		pass

	# cmd = 'ffmpeg -loglevel warning -ss 0 -i $(youtube-dl -f 22 --get-url https://www.youtube.com/watch?v=mMZriSvaVP8) -t 11200 -c:v copy -c:a copy react-spot.mp4'
	cmd = 'ffmpeg -loglevel warning -ss 0 -i $(youtube-dl -f bestaudio --get-url '+str(url)+') -t '+str(minute_mark*60)+' '+str(output)
	os.system(cmd)

	return os.getcwd()+'/'+output

url = 'https://www.youtube.com/watch?v=-xY_D8SMNtE'
content_audio_name = download_from_url_ffmpeg(url, 'jre.wav')
url = 'https://www.youtube.com/watch?v=-l88fMJcvWE'
style_audio_name = download_from_url_ffmpeg(url, 'joey_diaz.wav')

Loss Functions

There are two types of loss for this

  1. Content loss. Lower values for this means that the output audio sounds like joe rogan.
  2. Style loss. Lower values for this means that the output audio sounds like joey diaz.

Ideally we want both content and style loss to be minimised.

Content loss

The content loss function takes in an input matrix and a content matrix. The content matrix corresponds to joe rogan’s audio. Then it returns the weighted content distance: between the input matrix and the content matrix. This is implemented using a torch module. It can be calculated using nn.MSELoss.

#pytorch #deep-learning #neural-style-transfer #deep learning

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Buddha Community

Neural Style Transfer for Audio in Pytorch

Art Style Transfer using Neural Networks

Introduction

Art Style Transfer consists in the transformation of an image into a similar one that seems to have been painted by an artist.

If we are Vincent van Gogh fans, and we love German Shepherds, we may like to get a picture of our favorite dog painted in van Gogh’s Starry Night fashion.

german shepherd

Image by author

van gogh starry night

Starry Night by Vincent van Gogh, Public Domain

The resulting picture can be something like this:

german shepherd with a starry night style

Image by author

Instead, if we like Katsushika Hokusai’s Great Wave off Kanagawa, we may obtain a picture like this one:

the great wave

The Great wave of Kanagawa by Katsushika Hokusai, Public Domain

german shepherd with the great wave style

Image by author

And something like the following picture, if we prefer Wassily Kandinsky’s Composition 7:

wassily kandinsky composition 7

Compositions 7 by Wassily Kandinsky, Public Domain

german shepherd with composition 7 style

Image by author

These image transformations are possible thanks to advances in computing processing power that allowed the usage of more complex neural networks.

The Convolutional Neural Networks (CNN), composed of a series of layers of convolutional matrix operations, are ideal for image analysis and object identification. They employ a similar concept to graphic filters and detectors used in applications like Gimp or Photoshop, but in a much powerful and complex way.

A basic example of a matrix operation is performed by an edge detector. It takes a small picture sample of NxN pixels (5x5 in the following example), multiplies it’s values by a predefined NxN convolution matrix and obtains a value that indicates if an edge is present in that portion of the image. Repeating this procedure for all the NxN portions of the image, we can generate a new image where we have detected the borders of the objects present in there.

condor photo plus edge detector equals condor borders

Image by author

The two main features of CNNs are:

  • The numeric values of the convolutional matrices are not predefined to find specific image features like edges. Those values are automatically generated during the optimization processes, so they will be able to detect more complex features than borders.
  • They have a layered structure, so the first layers will detect simple image features (edges, color blocks, etc.) and the latest layers will use the information from the previous ones to detect complex objects like people, animals, cars, etc.

This is the typical structure of a Convolutional Neural Network:

Image for post

Image by Aphex34 / CC BY-SA 4.0

Thanks to papers like “Visualizing and Understanding Convolutional Networks”[1] by Matthew D. Zeiler, Rob Fergus and “Feature Visualization”[12] by Chris Olah, Alexander Mordvintsev, Ludwig Schubert, we can visually understand what features are detected by the different CNN layers:

Image for post

Image by Matthew D. Zeiler et al. “Visualizing and Understanding Convolutional Networks”[1], usage authorized

The first layers detect the most basic features of the image like edges.

Image for post
Image by Matthew D. Zeiler et al. “Visualizing and Understanding Convolutional Networks”[1], usage authorized

The next layers combine the information of the previous layer to detect more complex features like textures.

Image for post

Image by Matthew D. Zeiler et al. “Visualizing and Understanding Convolutional Networks”[1], usage authorized

Following layers, continue to use the previous information to detect features like repetitive patterns.

Image for post

Image by Matthew D. Zeiler et al. “Visualizing and Understanding Convolutional Networks”[1], usage authorized

The latest network layers are able to detect complex features like object parts.

Image for post

Image by Matthew D. Zeiler et al. “Visualizing and Understanding Convolutional Networks”[1], usage authorized

The final layers are capable of classifying complete objects present in the image.

The possibility of detecting complex image features is the key enabler to perform complex transformations to those features, but still perceiving the same content in the image.

#style-transfer-online #artificial-intelligence #neural-style-transfer #art-style-transfer #neural networks

Vern  Greenholt

Vern Greenholt

1596687780

Neural Style Transfer for Audio in Pytorch

They’ve been some really interesting applications of style transfer. It basically aims to take the ‘style’ from one image and change the ‘content’ image to meet that style.

But so far it hasn’t really been applied to audio. So I explored the idea of applying neural style transfer to audio. To be frank, the results were less than stellar but I’m going to keep working on this in the future.

For this exercise, I’m going to be using clips from the joe rogan podcast. I’m trying to make Joe Rogan, from the Joe Rogan Experience, sound like Joey Diaz, from the Church of Whats Happening Now. Joe Rogan already does a pretty good impression of joey diaz. But I’d like to improve his impression using deep learning.

Image for post

First I’m going to download the youtube videos. There’s a neat trick mentioned on github that allows you to download small segments of youtube videos. That’s handy cause I don’t want to download the entire video. You’ll need youtube-dl and ffmpeg for this step.

import os

# download youtube url using ffmpeg
# adapted from: https://github.com/ytdl-org/youtube-dl/issues/622#issuecomment-162337869
def download_from_url_ffmpeg(url, output, minute_mark = 1):

	try:
		os.remove(output)
	except:
		pass

	# cmd = 'ffmpeg -loglevel warning -ss 0 -i $(youtube-dl -f 22 --get-url https://www.youtube.com/watch?v=mMZriSvaVP8) -t 11200 -c:v copy -c:a copy react-spot.mp4'
	cmd = 'ffmpeg -loglevel warning -ss 0 -i $(youtube-dl -f bestaudio --get-url '+str(url)+') -t '+str(minute_mark*60)+' '+str(output)
	os.system(cmd)

	return os.getcwd()+'/'+output

url = 'https://www.youtube.com/watch?v=-xY_D8SMNtE'
content_audio_name = download_from_url_ffmpeg(url, 'jre.wav')
url = 'https://www.youtube.com/watch?v=-l88fMJcvWE'
style_audio_name = download_from_url_ffmpeg(url, 'joey_diaz.wav')

Loss Functions

There are two types of loss for this

  1. Content loss. Lower values for this means that the output audio sounds like joe rogan.
  2. Style loss. Lower values for this means that the output audio sounds like joey diaz.

Ideally we want both content and style loss to be minimised.

Content loss

The content loss function takes in an input matrix and a content matrix. The content matrix corresponds to joe rogan’s audio. Then it returns the weighted content distance: between the input matrix and the content matrix. This is implemented using a torch module. It can be calculated using nn.MSELoss.

#pytorch #deep-learning #neural-style-transfer #deep learning

Agnes  Sauer

Agnes Sauer

1598035200

Slow and Arbitrary Style Transfer

Introduction

Style transfer is the technique of combining two images, a content image and a **_style _**image, such that the **_generated _**image displays the properties of both its constituents. The goal is to generate an image that is similar in style (e.g., color combinations, brush strokes) to the style image and exhibits structural resemblance (e.g., edges, shapes) to the content image.

In this post, we describe an optimization-based approach proposed by Gatys et al. in their seminal work, “Image Style Transfer Using Convolutional Neural Networks”. But, let us first look at some of the building blocks that lead to the ultimate solution.

Image for post

Fig 1. Demonstration, Image taken from “[R2] Perceptual Losses for Real-Time Style Transfer and Super-Resolution”

What are CNNs learning?

At the outset, you can imagine low-level features as features visible in a **zoomed-in**image. In contrast, **high-level**features can be best viewed when the image is zoomed-out. Now, how does a computer know how to distinguish between these details of an image? CNNs, to the rescue.

Learned filters of pre-trained convolutional neural networks are excellent general-purpose image feature extractors. Different layers of a CNN extract the features at different scales. The hidden unit in shallow layers, which sees only a relatively small part of the input image, extracts **low-level**features like edges, colors, and simple textures. Deeper layers, however, with a wider receptive field tend to extract **high-level**features such as shapes, patterns, intricate textures, and even objects.

So, how can we leverage these feature extractors for style transfer?

#neural-style-transfer #digital-art #style-transfer #deep-learning #convolutional-network #deep learning

Oleta  Becker

Oleta Becker

1601442120

Fast and Less Restricted Style Transfer

Introduction

A pastiche is an artistic work that imitates the style of another one. Style transfer can be defined as finding a pastiche image **_p _**whose content is similar to that of a content image **_c _**but whose style is similar to that of a style image s.

Background

If you are familiar with optimization-based style transfer and feed-forward style transfer networks, feel free to skip this section.

The neural style transfer algorithm proposes the following definitions:

  1. Content Similarity: two images are similar in content if their high-level features as extracted by a trained classifier are close in Euclidean distance
  2. Style Similarity: two images are similar in style if their low-level features as extracted by a trained classifier share the same statistics.

#digital-art #deep-learning #neural-style-transfer #style-transfer #machine-learning

Why is my Cash App Transfer Failed [Solution 2021]?

Why is my Cash App Transfer Failed [Solution 2021]? yes sure you can use this app for online Payment Transfer, Call @+1 (855)698 5775 If you are facing any issues related with cash app transfer then you can contact on this number, If you are having trouble making any transfer on Cash App and your payment fails on Cash App then you need to first check if your Cash App is updated on your mobile or not. If not, then update the app to the latest version to make payments smoothly.Cash App transfers are almost always instantaneous. However, there are occasions when the app throws an exception, asking you to wait a little longer — aka 'Payment Pending. ’ It simply means the transfer has been initiated but cannot be fulfilled instantly

My Cash App Transfer Failed For My Protection

Cash App may fail your transaction to protect you from any fraud. Cash App monitors your account and if any suspicious activity takes place, it fails the transaction for your protection. This happens in order to save you from any scam and lose your money.

### Why would cash APP decline a payment for my protection?

Payments on Cash App with the error “failed for my Protection” may be declined for a few reasons. Some of the most common reasons include: Your bank or card issuer is declining the transaction, Incorrect details and the payment has triggered one of Cash App automated security flags.

How do I enable direct deposit on a cash App?

How do I enable direct deposit on a cash App? After successful activation, the employer will be able to pay your paycheck directly into your Cash App account. Follow these steps. Firstly, open the Cash App and click on the profile icon or Balance tab-present in the updated version of Cash App. After that, now navigate down to get the option “Direct Deposit”.

Relaated articles :- Why is my Cash App direct deposit failed ?

Why Cash App Transfer Failed For My Protection

How to Fix Cash App Payments for my protection? If you’re having trouble sending payment, make sure to check if you have added your correct credit or debit card to the Cash App, the best thing to do is double-check or reach out to your card issuer to confirm that there are no issues. If you’re waiting to receive more than $10,000 via direct deposit, your best bet is to request that the sender split the payment into two parts …

How to Fix Cash App Transfer Failed Earlier?

Cash App transfer failed for your security means that the transaction you are trying to make went unsuccessful. It might be any kind of transfer such as bank transfer, online or offline payment, cash withdrawal at an ATM and sending or receiving money to and from contacts.

### How do I fix my cash APP failed for my protection?

If you have got the Cash app Transfer failed error, then you have the option to raise a dispute for an unapproved transaction since you are a bank account holder. It is your right to dispute the unauthorized deductions made by the App

### How to Fix Cash App Transfer Failed ?

Cash app has witnessed considerable growth, with more than 30 million users. It is widely used in the US in order to make payments or transfer money to family and friends. The platform processes millions and millions of transactions on a daily basis. But this percentage is observed to have a huge drop due to Cash App transfer failed issues. About 10% of the total transactions are failing almost daily due to different reasons.
If you are having a similar sort of problem where the Cash App transaction failed, this article might be a useful one for you. It tells about the causes of the Cash app transfer failed error and mentions a few fixes that work for most of the causes as well. Hence, if you are encountering the same problem, read through this article to find your possible fix.

### Major Causes Behind Cash App Transfer Failed

  1. Improper internet connection
  2. Insufficient account balance
  3. Bank account fraud block
  4. Transaction blocked by Cash App

### How to Fix Cash App Transfer Failed

  1. Check a bank balance
  2. Using other bank accounts or cards
  3. Verifying the bank account details
  4. Contacting Cash app support team
  5. Contacting bank

### Major Causes Behind Cash App Transfer Failed

Although the number of causes behind a Cash app seems to be quite high, some of the key reasons are as mentioned:

Improper internet connection

Since all your transactions take place online, it requires a strong internet connection. Therefore, whenever you encounter a payment failure issue, the first thing is to check for your internet connectivity. For more efficient results, it is always better to connect your device to reliable Wi-Fi, if available.

Insufficient account balance

It happens quite often when users try to make a possible transaction without checking their account balance. If in case you don’t have enough amount in your cash app wallet or bank account, your transaction will fail.

Bank account fraud block

Whether you are having your account with Bank of America, PNC, or wherever, all these banks probably have their own fraud departments. These departments flag certain services as scams/ frauds. And since there are already a lot of scams operated on the Cash app these days, it adds up as a considerable reason for them to block transactions.

Transaction blocked by Cash App

Cash app has now grown into a billion-dollar company with around 30+ million users. Therefore, in order to maintain the security and privacy of its users, the Cash app has strict policies. So, if due to some reason, the application might have flagged the other person’s account as potential scam/ fraud, it might again cause a Cash app transfer failure.
These were some of the possible causes of Cash app transfer failed. However, most times, the following solutions might do a pretty good job of resolving your issues.

How do I fix my cash APP failed for my protection??

Since the whole thing is about transactions, there could be a bunch of other causes behind a failed transfer. These are just some basic fixes that actually work in most of the above-mentioned causes.

Related articles- How To Cash App Direct Deposit Failed ?SOlution | tranter-it

Check a bank balance

If your account balance is low in the case of the Cash app, it will eventually result in a failed transaction. However, to avoid such messages, it is a wise habit to always check your account balance or Cash app wallet balance before making a transfer.

Related article :- What happens when the cash app direct deposit failed? How to fix it?

Using other bank accounts or cards

Another primary reason behind encountering failed transactions is because of using blocked or rejected cards. Cash app often displays this error message basically due to server issues of the bank. To avoid such errors, you can try using a different credit/ debit card or bank account.

Verifying the bank account details

This is a very common mistake done by most users. Entering the wrong bank details will definitely lead to an cash app unsuccessful or failed transfer. Therefore, it is a good practice to be a little extra careful while entering such sensitive data.

Contacting Cash app support team

The Cash app might sometimes block your transactions, or it might flag the other person’s account as possible fraud in rare cases. In such situations, the wisest option is to contact the cash app’s support team and ask for assistance regarding the issue you are facing.

Contacting bank

If the bank itself terminates the transaction, contact your bank and ask for what reason the Cash app transfer failed through their system. They will inform you in case there are any serious issues and also advise the best way to overcome it.

Why is cash App declining my payment for my protection?

Cash App monitors your account for anything that looks out of the ordinary. If a potentially fraudulent payment occurs, we cancel it to prevent you from being charged. When this happens, your funds will instantly be returned to your Cash App balance or linked bank account.

Why does my Cash app keep saying Transfer failed?

Why does my Cash app keep saying Transfer failed?The reason why transfer fail every time can be because of the card which is updated on the account has expired or the details of the card are not correct. So, always you need to make sure that the card which is you are using is not expired and the details are correct.

##What does it mean when a cash app payment failed?

Cash App transfer failed for your security means that the transaction you are trying to make went unsuccessful. It might be any kind of transfer such as bank transfer, online or offline payment, cash withdrawal at ATM and sending or receiving money to and from contacts.

###Conclusion

Cash app has now grown quite popular with millions of users trusting its service. And undoubtedly, the application offers a great platform for easy transfer of money along with its other services. However, a lot of scams have already been reported regarding this application. So, if anyhow you face some sort of trouble and encounter the Cash app transfer failure, these tricks must help you find a way to resolve the problem and make efficient money transfer over the app. Let us know if this article helps you or if we missed out on something.

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