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# Filmgrainer - by Lars Ole Pontoppidan - MIT License
from PIL import Image, ImageFilter
import os
import tempfile
import numpy as np
import filmgrainer.graingamma as graingamma
import filmgrainer.graingen as graingen
def _grainTypes(typ):
# After rescaling to make different grain sizes, the standard deviation
# of the pixel values change. The following values of grain size and power
# have been imperically chosen to end up with approx the same standard
# deviation in the result:
if typ == 1:
return (0.8, 63) # more interesting fine grain
elif typ == 2:
return (1, 45) # basic fine grain
elif typ == 3:
return (1.5, 50) # coarse grain
elif typ == 4:
return (1.6666, 50) # coarser grain
else:
raise ValueError("Unknown grain type: " + str(typ))
# Grain mask cache
MASK_CACHE_PATH = os.path.join(tempfile.gettempdir(), "mask-cache")
def _getGrainMask(img_width:int, img_height:int, saturation:float, grayscale:bool, grain_size:float, grain_gauss:float, seed):
if grayscale:
str_sat = "BW"
sat = -1.0 # Graingen makes a grayscale image if sat is negative
else:
str_sat = str(saturation)
sat = saturation
filename = MASK_CACHE_PATH + "grain-%d-%d-%s-%s-%s-%d.png" % (
img_width, img_height, str_sat, str(grain_size), str(grain_gauss), seed)
if os.path.isfile(filename):
# print("Reusing: %s" % filename)
mask = Image.open(filename)
else:
mask = graingen.grainGen(img_width, img_height, grain_size, grain_gauss, sat, seed)
# print("Saving: %s" % filename)
if not os.path.isdir(MASK_CACHE_PATH):
os.mkdir(MASK_CACHE_PATH)
mask.save(filename, format="png", compress_level=1)
return mask
def process(image:Image, scale:float, src_gamma:float, grain_power:float, shadows:float,
highs:float, grain_type:int, grain_sat:float, gray_scale:bool, sharpen:int, seed:int):
# image = np.clip(image, 0, 1) # Ensure the values are within [0, 1]
# image = (image * 255).astype(np.uint8)
# img = Image.fromarray(image).convert("RGB")
img = image
org_width = img.size[0]
org_height = img.size[1]
if scale != 1.0:
# print("Scaling source image ...")
img = img.resize((int(org_width / scale), int(org_height / scale)),
resample = Image.LANCZOS)
img_width = img.size[0]
img_height = img.size[1]
# print("Size: %d x %d" % (img_width, img_height))
# print("Calculating map ...")
map = graingamma.Map.calculate(src_gamma, grain_power, shadows, highs)
# map.saveToFile("map.png")
# print("Calculating grain stock ...")
(grain_size, grain_gauss) = _grainTypes(grain_type)
mask = _getGrainMask(img_width, img_height, grain_sat, gray_scale, grain_size, grain_gauss, seed)
mask_pixels = mask.load()
img_pixels = img.load()
# Instead of calling map.lookup(a, b) for each pixel, use the map directly:
lookup = map.map
if gray_scale:
# print("Film graining image ... (grayscale)")
for y in range(0, img_height):
for x in range(0, img_width):
m = mask_pixels[x, y]
(r, g, b) = img_pixels[x, y]
gray = int(0.21*r + 0.72*g + 0.07*b)
#gray_lookup = map.lookup(gray, m)
gray_lookup = lookup[gray, m]
img_pixels[x, y] = (gray_lookup, gray_lookup, gray_lookup)
else:
# print("Film graining image ...")
for y in range(0, img_height):
for x in range(0, img_width):
(mr, mg, mb) = mask_pixels[x, y]
(r, g, b) = img_pixels[x, y]
r = lookup[r, mr]
g = lookup[g, mg]
b = lookup[b, mb]
img_pixels[x, y] = (r, g, b)
if scale != 1.0:
# print("Scaling image back to original size ...")
img = img.resize((org_width, org_height), resample = Image.LANCZOS)
if sharpen > 0:
# print("Sharpening image: %d pass ..." % sharpen)
for x in range(sharpen):
img = img.filter(ImageFilter.SHARPEN)
return np.array(img).astype('float32') / 255.0 |