Pix | Pix is an online pixel art community | Frontend Framework library

After further research, I've determined that the issue was the javascript method for the animation. Replacing requestAnimationFrame which was subtly mentioned in tungs' blog post regarding timecut. The following code works perfectly with timecut now:

You could try using round:

If I understand correctly, you are using QTableView to display a pandas dataframe. In this case it should be quite simple. You need to use the signal that comes from the QComboBox when an item is selected - probably currentIndexChanged(). You need to connect this to a function that will identify which items in your QComboBox are checked, and from this build the string that will go into the dataframe at the right place. Once the dataframe is updated, your QTableView should update to display the new cell of the dataframe. Without knowing more about your exact setup (the checkable combobox) I can't be more specific.

Edit: Here is a working solution. The first step was to make the combobox aware of what row it is in - in this case I just passed the row number as a variable to the combobox on creation. It's a quick and dirty way to do it - it would be better to find the row of the table that the widget is in dynamically. The second step is to define a custom signal which passes the row and the checked item list to a function in the main class which updates the dataframe at that row with the new checked list.

Just a simple configuration, Add the dpi option in get_pixmap()

You can most simply use f-strings to embed your values into a single string like this:

1. The missing versions are at least si128 and si64, used in bitwise operations and [e]pu{8,16,32,64} for unsigned operations.

2. epi and pi differ in e probably meaning extended; epi register target is an 128 bit xmm register, while pi targets 64-bit mmx registers.

3. pi64 does not exists, because the original mmx instruction set was limited to 32-bit elements; si64 is still available.

4. The main argument for using epi64x instead of epi64 needs to do with lack of function overloading in C. There was need to provide set/conversion methods both for __m128i _mm_set1_epi64(__m64) which moves from MMX to XMM and for __m128i _mm_set1_epi64x(int64_t) working with integers. Additionally it seems that in the rest of the cases the 64x suffix is reserved for modes requiring 64-bit architecture, as in movq between a register and low half of __m128i, which could be emulated by multiple instruction, and for something like __int64 _mm_cvtsd_si64x (__m128d a), which converts a double to 64-bit register target (not to memory directly).

What I would speculate, is that 'si64' and 'si128' mean scalar integer of width 64/128_, notice that there exists _mm_add_si64 (that is not original SSE intrinsic, that is SSE2 intrinsic extending the original MMX instruction set and using MMX registers). It's si64, not pi64, because only one element of the same size as the whole register is involved.

Lastly piN means packed integer of element size N targeting MMX (__m64) and epiN means packed integer of elements size N targeting XMM (__m128i).

I think this is what you are trying to do in Python/OpenCV. Python HSV hue is limited to range 0 to 180 so your angle needs to be scaled to that range. Similarly the magnitude is greater than 255 and also needs to be scaled to the range 0 to 255. The saturation you want would be a constant 255. I use Skimage to do the scaling. I have printed out the shape and min and max values at various places to show you these issues.

I believe the process is as follows:

• Read the input
• Convert it to gray
• Get the Sobel x and y derivatives
• Compute the magnitude and angle from the derivatives and scale mag to range 0 to 255 and angle to range 0 to 180
• Merge the angle, the magnitude and the magnitude into a 3 channel image as if HSV with angle first, then the magnitudes.
• Replace the second channel (channel 1) with 255 for the saturation
• Convert this HSV image to BGR as the result
• Save the result

Input:

If your program will be conducting a computation where you need a majority, if not all of the pixel data, then rgba.Pix() significantly outperforms img.At(). If you only need the pixel data of a single or few pixels in an image, use img.At() (the overhead of computing the rgba.Pix() prerequisite is too high in such cases).

Here are the results of various test loads, the durations of which are averaged over 10 samples each.

We can see how for the tiny 1x1 image and the image where we limit our for loops to upper bounds of 5, using img.At() results in faster execution time. However, for use cases where every pixel is fetched, rgba.Pix() results in better performance. This improvement in performance is less evident the more computation we do with every pixel, as the total time increases and the difference between img.At() and rgba.Pix() becomes less obvious, as seen in "1000x667 + computation" in the table above.

Here is the test code used:

Put a crossorigin attribute on the img tag in HTML to ensure the browser requests the image with headers for a CORS operation, such as