Customize the density and scale to fit your desired resolution, often lowering the resolution of the pre-comp to get larger, more prominent pixels. Conclusion
python pixdither.py photo.jpg --no-dither -o quantized.png
images = [] base_img = Image.open(input_path).convert('RGB')
# Add text overlay draw = ImageDraw.Draw(img) try: font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", 20) except: font = ImageFont.load_default() draw.text((10, 10), f"{bits} bits/channel", fill=(255, 255, 255), font=font) pixdither
One of the most popular and "natural-looking" algorithms, it diffuses error among neighboring pixels, creating organic, noisy gradients.
class PixDither: def __init__(self, image_path, output_path=None, bits_per_channel=1, palette_type="monochrome", dither_algorithm="floyd-steinberg"): """ Initialize dithering processor
What is the name of the effect which produces this type of image? : r/vfx Customize the density and scale to fit your
# Distribute error to neighboring pixels if x + 1 < self.width: result[y, x + 1] += error * 7/16 if y + 1 < self.height: if x > 0: result[y + 1, x - 1] += error * 3/16 result[y + 1, x] += error * 5/16 if x + 1 < self.width: result[y + 1, x + 1] += error * 1/16
PixDither is an After Effects plugin that acts as a color quantization and dithering engine. It works by reducing the color depth of 8-bit or 16-bit per channel video footage down to a severely restricted, classic color palette, similar to what vintage hardware could display.
Args: image_path: Path to input image output_path: Path for output image (optional) bits_per_channel: Color depth (1-8 bits per channel) palette_type: "monochrome", "grayscale", "rgb", or custom dither_algorithm: "floyd-steinberg", "atkinson", or "none" """ self.image_path = Path(image_path) self.output_path = output_path self.bits = bits_per_channel self.palette_type = palette_type self.algorithm = dither_algorithm : r/vfx # Distribute error to neighboring pixels
def atkinson(self): """Apply Atkinson dithering""" result = self.pixels.copy()
return np.clip(result, 0, 255).astype(np.uint8)