I am trying to optimize the size of my react app chunks. I analyzed them using:
source-map-explorer 'build/static/js/*.js
The result is the image below and it show that the tiny-invariant.js is taking 774KB of space. It doesn't make sense to me. How can a lib that takes 12.2kB unpacked show up as taking 774KB?
What can be wrong? Is source-map-explorer buggy? Right now that's my main explanation.
Related
So my goal is to add CVPixelBuffers into my AVAssetWriter / AVAssetWriterInputPixelBufferAdaptor with super high speed. My previous solution used CGContextDrawImage but it is very slow (0.1s) to draw. The reason seems to be with color matching and converting, but that's another question I think.
My current solution is trying to read the bytes of the image directly to skip the draw call. I do this:
CGImageRef cgImageRef = [image CGImage];
CGImageRetain(cgImageRef);
CVPixelBufferRef pixelBuffer = NULL;
CGDataProviderRef dataProvider = CGImageGetDataProvider(cgImageRef);
CGDataProviderRetain(dataProvider);
CFDataRef da = CGDataProviderCopyData(dataProvider);
CVPixelBufferCreateWithBytes(NULL,
CGImageGetWidth(cgImageRef),
CGImageGetHeight(cgImageRef),
kCVPixelFormatType_32BGRA,
(void*)CFDataGetBytePtr(da),
CGImageGetBytesPerRow(cgImageRef),
NULL,
0,
NULL,
&pixelBuffer);
[writerAdaptor appendPixelBuffer:pixelBuffer withPresentationTime:presentTime];
-- releases here --
This works fine on my simulator and inside an app. But when I run the code inside the SpringBoard process, it comes out as the images below. Running it outside the sandbox is a requirement, it is meant for jailbroken devices.
I have tried to play around with e.g. pixel format styles but it mostly comes out with differently corrupted images.
The proper image/video file looks fine:
But this is what I get in the broken state:
Answering my own question as I think I got the answer(s). The resolution difference was a simple code error, not using the device bounds on the latter ones.
The color issues. In short, the CGImages I got when running outside of the sandbox was using more bytes per pixel, 8 bytes. The images I get when running inside the sandbox was 4 bytes. So basically I was simply writing the wrong data into the buffer.
So, instead of simply slapping all of the bytes from the larger image into the smaller buffer. I loop through the pixel buffer row-by-row, byte-by-byte and I pick the RGBA values for each pixel. I essentially had to skip every other byte from the source image to get the right data into the right place within the buffer.
I am running the following simple line in a short script without any issues:
Python 3.5.2;
PIL 1.1.7;
OpenCV 2.4.9.1;
Matplotlib 3.0.1;
...
# for example:
img = plt.imread(i1)
...
However, if the size of a loaded .JP2 > ~500 MB, Python3 throws the following error when attempting to load an image:
"Segmentation Fault (core dumped)"
It should not be a RAM issue, as only ~40% of the available RAM is being used when the error occurs + the error remains the same when RAM is removed or added to the computer. The error also remains the same when using other ways to load the image, e.g. with PIL.
Is there a way to avoid this error or to work around it?
Thanks a lot!
Not really a solution, more of an idea that may work or help other folks think up similar or further developments...
If you want to do several operations or crops on each monster JP2 image, it may be worth paying the price up-front, just once to convert to a format that ImageMagick can subsequently handle more easily. So, your image is 20048x80000 of 2-byte shorts, so you can expand it out to a 16-bit PGM file like this:
convert monster.jp2 -depth 16 image.pgm
and that takes around 3 minutes. However, if you now want to extract part of the image some way down its height, you can now extract from the PGM:
convert image.pgm -crop 400x400+0+6000 tile.tif
in 18 seconds, instead of from the monster JP2:
convert monster.jp2 -crop 400x400+0+6000 tile.tif
which takes 153 seconds.
Note that the PGM will take lots of disk space.... I guess you could try the same thing with a TIFF which can hold 16-bit data too and could maybe be LZW compressed. I guess you could also use libvips to extract tiles even faster from the PGM file.
I'm creating a Raspberry Pi Zero W security camera and am attempting to integrate motion detection using Node.js. Images are being taken with Pi camera module at 8 Megapixels (3280x2464 pixels, roughly 5MB per image).
On a Pi Zero, resources are limited, so loading an entire image from file to Node.js may limit how fast I can capture then evaluate large photographs. Surprisingly, I capture about two 8MB images per second in a background time lapse process and hope to continue to capture the largest sized images roughly once per second at least. One resource that could help with this is extracting the embedded thumbnail from the large image (thumbnail size customizable in raspistill application).
Do you have thoughts on how I could quickly extract the thumbnail from a large image without loading the full image in Node.js? So far I've found a partial answer here. I'm guessing I would manage this through a buffer somehow?
Taking a very basic stock example such as the redify filter, with a large image (1200x1024) I was trying to determine why it takes (what I think) is too long. After some investigating, I find that the delay occurs in fabricjs::ApplyFilter, where replacement.src = canvasEl.toDataURL('image/png'); (line 17933 in 1.6.2). That take a long time, even compared to the complete pixel run through by the filter.
Is there some way around this? Can I do something differently to speed up the process? TIA
I want to grab a single frame from my webcam with node.js and OpenCV. The first frame captured is as expected. But if I move in front of the camera and take a second one, I get an image that was obviously taken quite after the first one and doesnt show my move. I have to take 5 pictures to see the move. Searching on the net gave me hint about a problem with the camera buffer that holds 4 images (OS depended).
Here is an example of someone having the same issue:
http://opencvarchive.blogspot.de/2010/05/opencv-arm-linux-servo-frame-delay.html
At the moment I'm doing a workaround and capture 5 images within a loop and then save the last image to disk. So the buffer is cleared and the really current image is taken.
Does anyone knows a better solution? Taking five images instead of one takes too much time for my application...
Thanks in advance! :)