Apple-2-SW/ii-pix
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Optimize palette initialization and NTSC image conversion

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This commit is contained in:
kris 2023-02-25 23:56:52 +00:00
parent f8fbd768a5
commit 4091dd259c
2 changed files with 37 additions and 26 deletions
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15
palette.py
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@ -41,12 +41,19 @@ class Palette:
def __init__(self):
self.RGB = {}
for k, v in self.SRGB.items():
# Do a bulk conversion because it's much faster than doing it within the
# loop
srgb = np.stack(list(self.SRGB.values()))
with colour.utilities.suppress_warnings(colour_usage_warnings=True):
cam = colour.convert(srgb / 255, "sRGB", "CAM16UCS").astype(
np.float32)
for i, kv in enumerate(self.SRGB.items()):
k, v = kv
self.RGB[k] = (np.clip(image.srgb_to_linear_array(v / 255), 0.0,
1.0) * 255).astype(np.uint8)
with colour.utilities.suppress_warnings(colour_usage_warnings=True):
self.CAM16UCS[k] = colour.convert(
v / 255, "sRGB", "CAM16UCS").astype(np.float32)
self.CAM16UCS[k] = cam[i, :]
@staticmethod
def _pixel_phase_shifts(phase_3_srgb):

48
screen.py
View File

@ -139,10 +139,10 @@ class NTSCScreen:
x = pos % 12 + self.NTSC_PHASE_SHIFT * 3
return np.cos(x * 2 * np.pi / 12)
def _read(self, line, pos):
def _read(self, lines, pos):
if pos < 0:
return 0
return 1 if line[pos] else 0
return np.zeros(lines.shape[0], dtype=np.float32)
return lines[:, pos].astype(np.float32)
def bitmap_to_image_ntsc(self, bitmap: np.ndarray) -> np.ndarray:
y_width = 12
@ -177,26 +177,30 @@ class NTSCScreen:
out_rgb = np.empty((bitmap.shape[0], bitmap.shape[1] * 3, 3),
dtype=np.uint8)
for y in range(bitmap.shape[0]):
ysum = 0
usum = 0
vsum = 0
line = np.repeat(bitmap[y], 3)
ysum = np.zeros(bitmap.shape[0], dtype=np.float32)
usum = np.zeros(bitmap.shape[0], dtype=np.float32)
vsum = np.zeros(bitmap.shape[0], dtype=np.float32)
# Repeat each pixel 3 times so we can do sub-pixel colour sampling
lines = np.repeat(bitmap, 3, axis=1)
for x in range(bitmap.shape[1] * 3):
ysum += self._read(lines, x) - self._read(lines, x - y_width)
usum += self._read(lines, x) * self._sin(x) - self._read(
lines, x - u_width) * self._sin((x - u_width))
vsum += self._read(lines, x) * self._cos(x) - self._read(
lines, x - v_width) * self._cos((x - v_width))
rgb = np.matmul(
yuv_to_rgb, np.stack(
(ysum / y_width, usum / u_width,
vsum / v_width), axis=1).reshape(
(bitmap.shape[0], 3, 1))).reshape(
bitmap.shape[0], 3)
out_rgb[:, x, 0] = np.minimum(255, np.maximum(0, rgb[:, 0] * 255))
out_rgb[:, x, 1] = np.minimum(255, np.maximum(0, rgb[:, 1] * 255))
out_rgb[:, x, 2] = np.minimum(255, np.maximum(0, rgb[:, 2] * 255))
for x in range(bitmap.shape[1] * 3):
ysum += self._read(line, x) - self._read(line, x - y_width)
usum += self._read(line, x) * self._sin(x) - self._read(
line, x - u_width) * self._sin((x - u_width))
vsum += self._read(line, x) * self._cos(x) - self._read(
line, x - v_width) * self._cos((x - v_width))
rgb = np.matmul(
yuv_to_rgb, np.array(
(ysum / y_width, usum / u_width,
vsum / v_width)).reshape((3, 1))).reshape(3)
r = min(255, max(0, rgb[0] * 255))
g = min(255, max(0, rgb[1] * 255))
b = min(255, max(0, rgb[2] * 255))
out_rgb[y, x, :] = (r, g, b)
return out_rgb