from matplotlib import pyplot as plt
import numpy as np
import imageio
import exifread
import rawpy
file_path = "nikond7000_iso100/nikond7000_iso100.NEF"
"""
https://www.techtalk7.com/raw-image-processing-with-rawpy/
"""
# calculation of white-balance and brightness with ColorChecker
def wb_raw(file_path):
with rawpy.imread(file_path) as raw:
opts = rawpy.Params(output_color=rawpy.ColorSpace.raw, four_color_rgb=True, no_auto_bright=True,
user_wb=[1.0, 1.0, 1.0, 1.0], gamma=(1, 1), output_bps=8, bright=1)
rgb_base = raw.postprocess(opts)
raw.close()
# mapping intensity
map_i = np.mean(rgb_base, axis=2).astype(float) / (2 ** 8 - 1)
# detection of white patch of ColorChecker with thresholding
map_i[np.logical_or(map_i <= 0.25, map_i >= 0.8)] = float('nan')
mp_coo = np.where(~np.isnan(map_i))
quick_rgb = rgb_base[mp_coo[0], mp_coo[1]].copy()
# white balance - ratio
avgR = np.mean(quick_rgb[..., 0])
avgG = np.mean(quick_rgb[..., 1])
avgB = np.mean(quick_rgb[..., 2])
a = avgG / avgR
b = avgG / avgB
wb_mult = [a, 1, b, 1]
B = 200 / avgG
return wb_mult, B
wb, b = wb_raw(file_path)
print("wb", wb)
print("b", b)
print()
"""
Exemples : wb = (0,0,0,0) b = 100
"""
def postProcessing(file_path, save, wb, b):
with rawpy.imread(file_path) as raw:
rgb = raw.postprocess(
# demosaic_algorithm = rawpy.DemosaicAlgorithm.AHD,
# half_size = False,
# four_color_rgb = False,
# use_camera_wb = False,
# use_auto_wb = False,
user_wb = list(wb),
# output_color = rawpy.ColorSpace.raw,
# output_bps = 16,user_flip=None,
# user_black = None,
# user_sat = None,
# no_auto_bright = False,
# auto_bright_thr = 0.01,
# adjust_maximum_thr = 0,
bright = b,
# highlight_mode = rawpy.HighlightMode.Ignore,
# exp_shift = None,
# exp_preserve_highlights = 0.0,
# no_auto_scale = True,
# gamma = (2.222, 4.5),
# chromatic_aberration = None,
# bad_pixels_path = None
)
print(f'raw type: {raw.raw_type}') # raw type (flat or stack, e.g., Foveon sensor)
print(f'number of colors: {raw.num_colors}') # number of different color components, e.g., 3 for common RGB Bayer sensors with two green identical green sensors
print(f'color description: {raw.color_desc}') # describes the various color components
print(f'raw pattern: {raw.raw_pattern}') # decribes the pattern of the Bayer sensor
print(f'black levels: {raw.black_level_per_channel}') # black level correction
print(f'white level: {raw.white_level}') # camera white level
print(f'color matrix: {raw.color_matrix.tolist()}') # camera specific color matrix, usually obtained from a list in rawpy (not from the raw file)
print(f'XYZ to RGB conversion matrix: {raw.rgb_xyz_matrix.tolist()}') # camera specific XYZ to camara RGB conversion matrix
print(f'camera white balance: {raw.camera_whitebalance}') # the picture's white balance as determined by the camera
print(f'daylight white balance: {raw.daylight_whitebalance}') # the camera's daylight white balance
print()
with open(file_path, 'rb') as f:
tags = exifread.process_file(f)
for key, value in tags.items():
if key != 'JPEGThumbnail': # do not print (uninteresting) binary thumbnail data
print(f'{key}: {value}')
print()
rgb_uint8 = rgb
rgb_uint8 = rgb_uint8.astype(np.uint8)
plt.imshow(rgb_uint8)
plt.axis('off')
plt.title('rgb (raw)')
plt.show()
bw = (0.21 * rgb[:,:,0]) + (0.72 * rgb[:,:,0]) + (0.07 * rgb[:,:,0])
plt.imshow(bw, 'gray')
plt.axis('off')
plt.title('bw (raw)')
plt.show()
if save == 1:
imageio.imsave('output.tiff', rgb)
return rgb
postProcessing(file_path, 0, wb, b)
