FidelityFX-FSR2 | FidelityFX Super Resolution | Computer Vision library

by GPUOpen-Effects C Version: v2.2.0a License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | FidelityFX-FSR2 Summary

FidelityFX-FSR2 is a C library typically used in Artificial Intelligence, Computer Vision applications. FidelityFX-FSR2 has no bugs, it has no vulnerabilities and it has medium support. However FidelityFX-FSR2 has a Non-SPDX License. You can download it from GitHub.

FidelityFX Super Resolution 2 (or FSR2 for short) is a cutting-edge upscaling technique developed from the ground up to produce high resolution frames from lower resolution inputs. FSR2 uses temporal feedback to reconstruct high-resolution images while maintaining and even improving image quality compared to native rendering. FSR2 can enable “practical performance” for costly render operations, such as hardware ray tracing.

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FidelityFX-FSR2 has a medium active ecosystem.

It has 1588 star(s) with 147 fork(s). There are 42 watchers for this library.

It had no major release in the last 12 months.

There are 71 open issues and 16 have been closed. On average issues are closed in 17 days. There are 10 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of FidelityFX-FSR2 is v2.2.0a

Quality

FidelityFX-FSR2 has no bugs reported.

Security

FidelityFX-FSR2 has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

FidelityFX-FSR2 has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

FidelityFX-FSR2 releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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FidelityFX-FSR2 Key Features

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FidelityFX-FSR2 Examples and Code Snippets

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Community Discussions

Trending Discussions on Computer Vision

Image similarity in swift

When using pandas_profiling: "ModuleNotFoundError: No module named 'visions.application'"

Classify handwritten text using Google Cloud Vision

cv2 findChessboardCorners does not detect corners

Fastest way to get the RGB average inside of a non-rectangular contour in the CMSampleBuffer

UIViewController can't override method from it's superclass

X and Y-axis swapped in Vision Framework Swift

Swift's Vision framework not recognizing Japanese characters

Boxing large objects in image containing both large and small objects of similar color and in high density from a picture

Create a LabVIEW IMAQ image from a binary buffer/file with and without NI Vision

QUESTION

Image similarity in swift

Asked 2022-Mar-25 at 11:42

The swift vision similarity feature is able to assign a number to the variance between 2 images. Where 0 variance between the images, means the images are the same. As the number increases this that there is more and more variance between the images.

What I am trying to do is turn this into a percentage of similarity. So one image is for example 80% similar to the other image. Any ideas how I could arrange the logic to accomplish this:

...

ANSWER

Answered 2022-Mar-25 at 10:26

It depends on how you want to scale it. If you just want the percentage you could just use Float.greatestFiniteMagnitude as the maximum value.

Source https://stackoverflow.com/questions/71615277

QUESTION

When using pandas_profiling: "ModuleNotFoundError: No module named 'visions.application'"

Asked 2022-Mar-22 at 13:26

import numpy as np
import pandas as pd
from pandas_profiling import ProfileReport

...

ANSWER

Answered 2022-Mar-22 at 13:26

It appears that the 'visions.application' module was available in v0.7.1

https://github.com/dylan-profiler/visions/tree/v0.7.1/src/visions

But it's no longer available in v0.7.2

https://github.com/dylan-profiler/visions/tree/v0.7.2/src/visions

It also appears that the pandas_profiling project has been updated, the file summary.py no longer tries to do this import.

In summary: use visions version v0.7.1 or upgrade pandas_profiling.

Source https://stackoverflow.com/questions/71568414

QUESTION

Classify handwritten text using Google Cloud Vision

Asked 2022-Mar-01 at 00:36

I'm exploring Google Cloud Vision to detect handwriting in text. I see that the model is quite accurate in read handwritten text.

I'm following this guide: https://cloud.google.com/vision/docs/handwriting

Here is my question: is there a way to discover in the responses if the text is handwritten or typed?

A parameter or something in the response useful to classify images?

Here is the request:

...

ANSWER

Answered 2022-Mar-01 at 00:36

It seems that there's already an open discussion with the Google team to get this Feature Request addressed:

https://issuetracker.google.com/154156890

I would recommend you to comment on the Public issue tracker and indicate that "you are affected to this issue" to gain visibility and push for get this change done.

Other that that I'm unsure is that can be implemented locally.

Source https://stackoverflow.com/questions/71296897

QUESTION

cv2 findChessboardCorners does not detect corners

Asked 2022-Jan-29 at 23:59

I want to try out this tutorial and therefore used the code from here in order to calibrate my camera. I use this image:

The only thing I adapted was chessboard_size = (14,9) so that it matches the corners of my image. I don't know what I do wrong. I tried multiple chessboard pattern and cameras but still cv2.findChessboardCorners always fails detecting corners. Any help would be highly appreciated.

...

ANSWER

Answered 2022-Jan-29 at 23:59

Finally I could do it. I had to set chessboard_size = (12,7) then it worked. I had to count the internal number of horizontal and vertical corners.

Source https://stackoverflow.com/questions/70907902

QUESTION

Fastest way to get the RGB average inside of a non-rectangular contour in the CMSampleBuffer

Asked 2022-Jan-26 at 02:12

I am trying to get the RGB average inside of a non-rectangular multi-edge (closed) contour generated over a face landmark region in the frame (think of it as a face contour) from AVCaptureVideoDataOutput. I currently have the following code,

...

ANSWER

Answered 2022-Jan-26 at 02:12

If you could make all pixels outside of the contour transparent then you could use CIKmeans filter with inputCount equal 1 and the inputExtent set to the extent of the frame to get the average color of the area inside the contour (the output of the filter will contain 1-pixel image and the color of the pixel is what you are looking for).

Now, to make all pixels transparent outside of the contour, you could do something like this:

Create a mask image but setting all pixels inside the contour white and black outside (set background to black and fill the path with white).
Use CIBlendWithMask filter where:
- inputBackgroundImage is a fully transparent (clear) image
- inputImage is the original frame
- inputMaskImage is the mask you created above

The output of that filter will give you the image with all pixels outside the contour fully transparent. And now you can use the CIKMeans filter with it as described at the beginning.

BTW, if you want to play with every single of the 230 filters out there check this app out: https://apps.apple.com/us/app/filter-magic/id1594986951

UPDATE:

CIFilters can only work with CIImages. So the mask image has to be a CIImage as well. One way to do that is to create a CGImage from CAShapeLayer containing the mask and then create CIImage out of it. Here is how the code could look like:

Source https://stackoverflow.com/questions/70344336

QUESTION

UIViewController can't override method from it's superclass

Asked 2022-Jan-21 at 19:37

I am actually experimenting with the Vision Framework. I have simply an UIImageView in my Storyboard and my class is from type UIViewController. But when I try to override viewDidAppear(_ animated: Bool) I get the error message: Method does not override any method from its superclass Do anyone know what the issue is? Couldn't find anything that works for me...

...

ANSWER

Answered 2022-Jan-21 at 19:37

This is my complete code:

Source https://stackoverflow.com/questions/70804364

QUESTION

X and Y-axis swapped in Vision Framework Swift

Asked 2021-Dec-23 at 14:33

I'm using Vision Framework to detecting faces with iPhone's front camera. My code looks like

...

ANSWER

Answered 2021-Dec-23 at 14:33

For some reason, remove

Source https://stackoverflow.com/questions/70463081

QUESTION

Swift's Vision framework not recognizing Japanese characters

Asked 2021-Oct-12 at 23:37

I would like to read Japanese characters from a scanned image using swift's Vision framework. However, when I attempt to set the recognition language of VNRecognizeTextRequest to Japanese using

request.recognitionLanguages = ["ja", "en"]

the output of my program becomes nonsensical roman letters. For each image of japanese text there is unexpected recognized text output. However, when set to other languages such as Chinese or German the text output is as expected. What could be causing the unexpected output seemingly peculiar to Japanese?

I am building from the github project here.

...

ANSWER

Answered 2021-Oct-12 at 23:37

As they said in WWDC 2019 video, Text Recognition in Vision Framework:

First, a prerequisite, you need to check the languages that are supported by language-based correction...

Look at supportedRecognitionLanguages for VNRecognizeTextRequestRevision2 for “accurate” recognition, and it would appear that the supported languages are:

Source https://stackoverflow.com/questions/69546997

QUESTION

Boxing large objects in image containing both large and small objects of similar color and in high density from a picture

Asked 2021-Oct-12 at 10:58

For my research project I'm trying to distinguish between hydra plant (the larger amoeba looking oranges things) and their brine shrimp feed (the smaller orange specks) so that we can automate the cleaning of petri dishes using a pipetting machine. An example of a snap image from the machine of the petri dish looks like so:

I have so far applied a circle mask and an orange color space mask to create a cleaned up image so that it's mostly just the shrimp and hydra.

There is some residual light artifacts left in the filtered image, but I have to bite the cost or else I lose the resolution of the very thin hydra such as in the top left of the original image.

I was hoping to box and label the larger hydra plants but couldn't find much applicable literature for differentiating between large and small objects of similar attributes in an image, to achieve my goal.

I don't want to approach this using ML because I don't have the manpower or a large enough dataset to make a good training set, so I would truly appreciate some easier vision processing tools. I can afford to lose out on the skinny hydra, just if I can know of a simpler way to identify the more turgid, healthy hydra from the already cleaned up image that would be great.

I have seen some content about using openCV findCountours? Am I on the right track?

Attached is the code I have so you know what datatypes I'm working with.

...

ANSWER

Answered 2021-Oct-12 at 10:58

You are on the right track, but I have to be honest. Without DeepLearning you will get good results but not perfect.

That's what I managed to get using contours:

Code:

Source https://stackoverflow.com/questions/69503515

QUESTION

Create a LabVIEW IMAQ image from a binary buffer/file with and without NI Vision

Asked 2021-Sep-30 at 13:54

Assume you have a binary buffer or file which represents a 2-dimensional image.

How can you convert the binary data into a IMAQ image for further processing using LabVIEW?

...

ANSWER

Answered 2021-Sep-30 at 13:54

With NI Vision

For LabVIEW users who have the NI vision library installed, there are VIs that allow for the image data of an IMAQ image to be copied from a 2D array.

For single-channel images (U8, U16, I16, float) the VI is

Vision and Motion >> Vision Utilites >> Pixel Manipulation >> IMAQ ArrayToImage.vi

For multichannel images (RGB etc) the VI is

Vision and Motion >> Vision Utilites >> Color Utilities >> IMAQ ArrayColorToImage.vi

Example 1

An example of using the IMAQ ArrayToImage.vi is shown in the snippet below where U16 data is read from a binary file and written to a Greyscale U16 type IMAQ image. Please note, if the file has been created by other software than LabVIEW then it is likely that it will have to be read in little-endian format which is specified for the Read From Binary File.vi

Example 2

A similar process can be used when some driver DLL call is used to get the image data as a buffer. For example, if the driver has a function capture(unsigned short * buffer) then the following technique could be employed where a correctly sized array is initialized before the function call using the initialize array primitive.

Source https://stackoverflow.com/questions/69380393

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

Vulnerabilities

No vulnerabilities reported

Install FidelityFX-FSR2

To use FSR2 you should follow the steps below:.
Double click GenerateSolutions.bat in the build directory.
Open the solution matching your API, and build the solution.
Copy the API library from bin/ffx_fsr2_api into the folder containing a folder in your project which contains third-party libraries.
Copy the library matching the FSR2 backend you want to use, e.g.: bin/ffx_fsr2_api/ffx_fsr2_api_dx12_x64.lib for DirectX12.
Copy the following core API header files from src/ffx-fsr2-api into your project: ffx_fsr2.h, ffx_types.h, ffx_error.h, ffx_fsr2_interface.h, ffx_util.h, shaders/ffx_fsr2_common.h, and shaders/ffx_fsr2_resources.h. Care should be taken to maintain the relative directory structure at the destination of the file copying.
Copy the header files for the API backend of your choice, e.g. for DirectX12 you would copy dx12/ffx_fsr2_dx12.h and dx12/shaders/ffx_fsr2_shaders_dx12.h. Care should be taken to maintain the relative directory structure at the destination of the file copying.
Include the ffx_fsr2.h header file in your codebase where you wish to interact with FSR2.
Create a backend for your target API. E.g. for DirectX12 you should call ffxFsr2GetInterfaceDX12. A scratch buffer should be allocated of the size returned by calling ffxFsr2GetScratchMemorySizeDX12 and the pointer to that buffer passed to ffxFsr2GetInterfaceDX12.
Create a FSR2 context by calling ffxFsr2ContextCreate. The parameters structure should be filled out matching the configuration of your application. See the API reference documentation for more details.
Each frame you should call ffxFsr2ContextDispatch to launch FSR2 workloads. The parameters structure should be filled out matching the configuration of your application. See the API reference documentation for more details, and ensure the frameTimeDelta field is provided in milliseconds.
When your application is terminating (or you wish to destroy the context for another reason) you should call ffxFsr2ContextDestroy. The GPU should be idle before calling this function.
Sub-pixel jittering should be applied to your application's projection matrix. This should be done when performing the main rendering of your application. You should use the ffxFsr2GetJitterOffset function to compute the precise jitter offsets. See Camera jitter section for more details.
For the best upscaling quality it is strongly advised that you populate the Reactive mask and Transparency & composition mask according to our guidelines. You can also use ffxFsr2ContextGenerateReactiveMask as a starting point.
Applications should expose scaling modes, in their user interface in the following order: Quality, Balanced, Performance, and (optionally) Ultra Performance.
Applications should also expose a sharpening slider to allow end users to achieve additional quality.

Support

High dynamic range images are supported in FSR2. To enable this, you should set the FFX_FSR2_ENABLE_HIGH_DYNAMIC_RANGE bit in the flags field of the FfxFsr2ContextDescription structure. Images should be provided to FSR2 in linear color space. Support for additional color spaces might be provided in a future revision of FSR2.

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