how can I convert pix_buffer into a numpy array format?

leo_cy

pix_buffer = lv.get_pixels_with_options(w, h, 0, 0, 0, db.DBox(x1, y1, x2, y2)) I want to save this buffer and transfer it to another function.

sekigawa

I played with ChatGPT-4o.

from klayout import lay

inputgds  = "ringo.gds"
#inputlyp  = "ringo.lyp"
inputlyp  = "invKazzzS.lyp"
outputpng = "f2625-ringo.png"

layoutview = lay.LayoutView()
cvIdx      = layoutview.load_layout( inputgds, add_cellview=True )
cellview   = layoutview.cellview(cvIdx)
layout     = cellview.layout()
topcell    = layout.top_cell()
topcellIdx = topcell.cell_index()
layoutview.load_layer_props( inputlyp )
#layoutview.set_config('background-color', '#4d4d4d')
layoutview.set_config('background-color', '#dddddd')
layoutview.max_hier_levels = layout.cell(topcellIdx).hierarchy_levels() + 1
layoutview.zoom_fit()

dbbox  = topcell.dbbox()
scale  = 0.01 # [um/pix]
width  = int(dbbox.width()/scale)
height = int(dbbox.height()/scale)
target = dbbox.enlarged(0.2, 0.5)
print( f"TopCell={topcell.name} width={width} height={height} CellBBox={dbbox} TargetBox={target}" )
print( f"" )

pix_buffer = layoutview.get_pixels_with_options(width, height, 0, 0, 0, target)
pix_buffer.write_png(outputpng)

"""
[ChatGPT 4o]
<Q> How to pass the PNG byte stream to numpy?

<A> You can use PIL (Python Imaging Library) and io to convert a PNG byte stream to a NumPy array.
    Here is how to do it:
      First, make sure you have PIL installed. You can install it using pip install pillow
      if you haven't already.
    Here's how to pass the PNG byte stream to NumPy:
    ```
    import io
    import numpy as np
    from PIL import Image

    # Assuming png_bytes is your PNG byte stream
    png_bytes = b"..."

    # Convert the byte stream to a PIL Image
    image = Image.open(io.BytesIO(png_bytes))

    # Convert the PIL Image to a NumPy array
    np_array = np.array(image)

    print(np_array)
    ```
"""

#--------------------------------------------------------------------------------------
# Class PixelBuffer
#       Signature: [const] bytes to_png_data
#       Description: Converts the pixel buffer to a PNG byte stream
#       This method may not be available if PNG support is not compiled into KLayout.
#
#   see https://www.w3.org/TR/png-3/#4Concepts.Format
#       for 4.8 PNG datastream (I have not read it!)
#--------------------------------------------------------------------------------------
import io
import numpy as np
from   PIL import Image

png_bytes = pix_buffer.to_png_data()
image     = Image.open(io.BytesIO(png_bytes))
np_array  = np.array(image)
print(np_array)

% ./F2625-KazzzS.py
TopCell=RINGO width=2580 height=800 CellBBox=(0,0;25.8,8) TargetBox=(-0.2,-0.5;26,8.5)

[[[221 221 221]
  [221 221 221]
  [221 221 221]
  ...
  [221 221 221]
  [221 221 221]
  [221 221 221]]

 [[221 221 221]
  [221 221 221]
  [221 221 221]
  ...
  [221 221 221]
  [221 221 221]
  [221 221 221]]

 [[221 221 221]
  [221 221 221]
  [221 221 221]
  ...
  [221 221 221]
  [221 221 221]
  [221 221 221]]

 ...

 [[221 221 221]
  [221 221 221]
  [221 221 221]
  ...
  [221 221 221]
  [221 221 221]
  [221 221 221]]

 [[221 221 221]
  [221 221 221]
  [221 221 221]
  ...
  [221 221 221]
  [221 221 221]
  [221 221 221]]

 [[221 221 221]
  [221 221 221]
  [221 221 221]
  ...
  [221 221 221]
  [221 221 221]
  [221 221 221]]]

I guess these 221s are related to the background color.

leo_cy

Thank you for your reply. However, I feel that this conversion process is a bit inefficient. Is it possible to directly convert the pixel buffer to an array without converting it to PNG data, or to avoid using the layoutview.get_pixels_with_options function to obtain the specified region's buffer? For example, can I use the Image class from KLayout to directly obtain the array?

Matthias

Hi @leo_cy,

You can use PixelBuffer#pixel to get the value for a specific pixel. You can iterate over the x/y range to get the values for a range of pixels.

There is no direct way to obtain the data from PIxelBuffer as a NumPy array. Image is something different - it is a class intended to represent images overlaid on your layout.

I repeat a warning here: do not use screenshot data for manufacturing or analysis purposes! It does not have the quality needed for this purpose and you may find unexpected artefacts. Region#rasterize (https://www.klayout.de/doc-qt5/code/class_Region.html#method202) is a quality renderer that delivers grayscale values as a NumPy-compatible array. However, it is much slower than the screen renderer.

Matthias

leo_cy

"Like this function, pix_buffer = layoutview.get_pixels_with_options(width, height, 0, 0, 0, target), how can I use the rasterize function to obtain the rendering effect and array values for the target area, perhaps assuming a pixel size of 10 and a spacing of 15?" .
Your meaning is that the function layoutview.get_pixels_with_options(width, height, 0, 0, 0, target) retrieves screenshot data, which does not meet the purposes of manufacturing and analysis?

Matthias

Maybe you could explain what you are trying to do and it will be easier to discuss.

leo_cy

Hi Matthias,
I would like to use the GDS rendering method to achieve high-precision graphic rendering based on physical dimensions (such as nm), which will be used for production or analysis purposes.

First, I want to render a specified area.
Second, I need to obtain the image buffer of this area.
Third, I need to consider the rendering efficiency.
Can you recommend a method or example?

Thank you very much！

Matthias

I replied to your other post. Will that answer this question?

Thanks,

Matthias