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74 lines
2.8 KiB
Python
Executable File
74 lines
2.8 KiB
Python
Executable File
#!/usr/bin/env python3
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import PIL.Image # https://pillow.readthedocs.io/
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import util
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# snowflake.png is the source image. The source image MUST have a white background,
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# but other colors and pixel depth are irrelevant. This one is black & white.
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# Due to the Apple II pixel aspect ratio, we do a 1-time aspect-ratio-losing resize
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# to squash the image to 87% height.
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#
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# $ gm convert snowflake.png -resize "100%x87%!" squash.png
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# (Depending on your shell, you may need to escape the exclamation point. Grr.)
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#
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# Now we can create individual images for each "frame" of the animation, by
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# resizing the (squashed) source image and putting it in a 280x192 frame.
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#
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# $ for w in `seq 1 500`; do \
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# gm convert -size 280x192 squash.png \
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# -resize "$w" \
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# -background white \
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# -compose Copy \
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# -gravity center \
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# -extent 280x192 thumb"$w".png; \
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# done
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#
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# Depending on the source image, you may need more or fewer than 500 frames. This
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# number is duplicated below in the |frames| variable. Sorry.
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#
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# Now we have 500 (or so) PNG images of what the HGR screen should look like at
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# each stage. Despite each frame being 280x192 and in the correct aspect ratio,
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# only coordinates
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# - on every 3rd row
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# - on even columns
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# are included in the final data set.
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#
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# X coordinates are converted to byte+bitmask (but see notes below).
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# Y coordinates are flipped (so 0,0 ends up on the bottom left) then
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# divided by 3.
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#
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# 6502 code will be responsible for plotting each of these coordinates
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# in a 2x3 block. The bitmask usually includes 2 adjacent pixels;
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# the code will also plot the same 2 adjacent pixels in the next two rows.
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#
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# Unfortunately, since bytes are 7 pixels across, some of the 2-pixel-wide
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# blocks will cross a byte boundary. To simplify the 6502 code, these are
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# simply listed as separate coordinate pairs, each with a bitmask that
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# includes 1 pixel instead of 2.
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frames = 1000 # number of "thumbN.png" files
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coords = []
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for i in range(5, frames, 5):
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p = PIL.Image.open("snowflake/thumb%s.png" % i)
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for x in range(0, 280//2):
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for y in range(0, 192//2, 2):
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if p.getpixel((x,191-y))[0] != 255:
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coords.append((x,y))
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unique_coords = util.unique(coords)
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unique_vals = util.vals_1bit(unique_coords)
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with open("../../../src/fx/fx.hgr.snowflake.data.a", "w") as f:
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for aval, bval in unique_vals:
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f.write(" !byte %s,%s\n" % (aval, bval))
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ripple_vals = util.ripple(unique_vals)
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with open("../../../src/fx/fx.hgr.snowflake.ripple.data.a", "w") as f:
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for aval, bval in ripple_vals:
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f.write(" !byte %s,%s\n" % (aval, bval))
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unique_vals.reverse()
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with open("../../../src/fx/fx.hgr.snowflake.in.data.a", "w") as f:
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for aval, bval in unique_vals:
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f.write(" !byte %s,%s\n" % (aval, bval))
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