626172a16b
Source files in libcamera start by a comment block header, which
includes the file name and a one-line description of the file contents.
While the latter is useful to get a quick overview of the file contents
at a glance, the former is mostly a source of inconvenience. The name in
the comments can easily get out of sync with the file name when files
are renamed, and copy & paste during development have often lead to
incorrect names being used to start with.
Readers of the source code are expected to know which file they're
looking it. Drop the file name from the header comment block.
The change was generated with the following script:
----------------------------------------
dirs="include/libcamera src test utils"
declare -rA patterns=(
['c']=' \* '
['cpp']=' \* '
['h']=' \* '
['py']='# '
['sh']='# '
)
for ext in ${!patterns[@]} ; do
files=$(for dir in $dirs ; do find $dir -name "*.${ext}" ; done)
pattern=${patterns[${ext}]}
for file in $files ; do
name=$(basename ${file})
sed -i "s/^\(${pattern}\)${name} - /\1/" "$file"
done
done
----------------------------------------
This misses several files that are out of sync with the comment block
header. Those will be addressed separately and manually.
Signed-off-by: Laurent Pinchart <laurent.pinchart@ideasonboard.com>
Reviewed-by: Daniel Scally <dan.scally@ideasonboard.com>
454 lines
15 KiB
Python
454 lines
15 KiB
Python
# SPDX-License-Identifier: BSD-2-Clause
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#
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# Copyright (C) 2019-2020, Raspberry Pi Ltd
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#
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# camera tuning tool image loading
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from ctt_tools import *
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from ctt_macbeth_locator import *
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import json
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import pyexiv2 as pyexif
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import rawpy as raw
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"""
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Image class load image from raw data and extracts metadata.
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Once image is extracted from data, it finds 24 16x16 patches for each
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channel, centred at the macbeth chart squares
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"""
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class Image:
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def __init__(self, buf):
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self.buf = buf
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self.patches = None
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self.saturated = False
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'''
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obtain metadata from buffer
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'''
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def get_meta(self):
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self.ver = ba_to_b(self.buf[4:5])
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self.w = ba_to_b(self.buf[0xd0:0xd2])
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self.h = ba_to_b(self.buf[0xd2:0xd4])
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self.pad = ba_to_b(self.buf[0xd4:0xd6])
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self.fmt = self.buf[0xf5]
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self.sigbits = 2*self.fmt + 4
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self.pattern = self.buf[0xf4]
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self.exposure = ba_to_b(self.buf[0x90:0x94])
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self.againQ8 = ba_to_b(self.buf[0x94:0x96])
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self.againQ8_norm = self.againQ8/256
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camName = self.buf[0x10:0x10+128]
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camName_end = camName.find(0x00)
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self.camName = self.buf[0x10:0x10+128][:camName_end].decode()
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"""
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Channel order depending on bayer pattern
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"""
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bayer_case = {
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0: (0, 1, 2, 3), # red
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1: (2, 0, 3, 1), # green next to red
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2: (3, 2, 1, 0), # green next to blue
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3: (1, 0, 3, 2), # blue
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128: (0, 1, 2, 3) # arbitrary order for greyscale casw
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}
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self.order = bayer_case[self.pattern]
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'''
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manual blacklevel - not robust
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'''
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if 'ov5647' in self.camName:
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self.blacklevel = 16
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else:
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self.blacklevel = 64
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self.blacklevel_16 = self.blacklevel << (6)
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return 1
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'''
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print metadata for debug
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'''
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def print_meta(self):
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print('\nData:')
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print(' ver = {}'.format(self.ver))
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print(' w = {}'.format(self.w))
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print(' h = {}'.format(self.h))
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print(' pad = {}'.format(self.pad))
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print(' fmt = {}'.format(self.fmt))
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print(' sigbits = {}'.format(self.sigbits))
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print(' pattern = {}'.format(self.pattern))
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print(' exposure = {}'.format(self.exposure))
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print(' againQ8 = {}'.format(self.againQ8))
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print(' againQ8_norm = {}'.format(self.againQ8_norm))
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print(' camName = {}'.format(self.camName))
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print(' blacklevel = {}'.format(self.blacklevel))
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print(' blacklevel_16 = {}'.format(self.blacklevel_16))
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return 1
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"""
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get image from raw scanline data
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"""
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def get_image(self, raw):
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self.dptr = []
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"""
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check if data is 10 or 12 bits
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"""
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if self.sigbits == 10:
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"""
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calc length of scanline
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"""
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lin_len = ((((((self.w+self.pad+3)>>2)) * 5)+31)>>5) * 32
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"""
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stack scan lines into matrix
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"""
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raw = np.array(raw).reshape(-1, lin_len).astype(np.int64)[:self.h, ...]
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"""
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separate 5 bits in each package, stopping when w is satisfied
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"""
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ba0 = raw[..., 0:5*((self.w+3)>>2):5]
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ba1 = raw[..., 1:5*((self.w+3)>>2):5]
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ba2 = raw[..., 2:5*((self.w+3)>>2):5]
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ba3 = raw[..., 3:5*((self.w+3)>>2):5]
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ba4 = raw[..., 4:5*((self.w+3)>>2):5]
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"""
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assemble 10 bit numbers
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"""
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ch0 = np.left_shift((np.left_shift(ba0, 2) + (ba4 % 4)), 6)
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ch1 = np.left_shift((np.left_shift(ba1, 2) + (np.right_shift(ba4, 2) % 4)), 6)
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ch2 = np.left_shift((np.left_shift(ba2, 2) + (np.right_shift(ba4, 4) % 4)), 6)
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ch3 = np.left_shift((np.left_shift(ba3, 2) + (np.right_shift(ba4, 6) % 4)), 6)
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"""
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interleave bits
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"""
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mat = np.empty((self.h, self.w), dtype=ch0.dtype)
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mat[..., 0::4] = ch0
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mat[..., 1::4] = ch1
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mat[..., 2::4] = ch2
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mat[..., 3::4] = ch3
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"""
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There is som eleaking memory somewhere in the code. This code here
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seemed to make things good enough that the code would run for
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reasonable numbers of images, however this is techincally just a
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workaround. (sorry)
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"""
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ba0, ba1, ba2, ba3, ba4 = None, None, None, None, None
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del ba0, ba1, ba2, ba3, ba4
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ch0, ch1, ch2, ch3 = None, None, None, None
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del ch0, ch1, ch2, ch3
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"""
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same as before but 12 bit case
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"""
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elif self.sigbits == 12:
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lin_len = ((((((self.w+self.pad+1)>>1)) * 3)+31)>>5) * 32
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raw = np.array(raw).reshape(-1, lin_len).astype(np.int64)[:self.h, ...]
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ba0 = raw[..., 0:3*((self.w+1)>>1):3]
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ba1 = raw[..., 1:3*((self.w+1)>>1):3]
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ba2 = raw[..., 2:3*((self.w+1)>>1):3]
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ch0 = np.left_shift((np.left_shift(ba0, 4) + ba2 % 16), 4)
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ch1 = np.left_shift((np.left_shift(ba1, 4) + (np.right_shift(ba2, 4)) % 16), 4)
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mat = np.empty((self.h, self.w), dtype=ch0.dtype)
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mat[..., 0::2] = ch0
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mat[..., 1::2] = ch1
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else:
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"""
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data is neither 10 nor 12 or incorrect data
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"""
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print('ERROR: wrong bit format, only 10 or 12 bit supported')
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return 0
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"""
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separate bayer channels
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"""
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c0 = mat[0::2, 0::2]
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c1 = mat[0::2, 1::2]
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c2 = mat[1::2, 0::2]
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c3 = mat[1::2, 1::2]
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self.channels = [c0, c1, c2, c3]
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return 1
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"""
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obtain 16x16 patch centred at macbeth square centre for each channel
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"""
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def get_patches(self, cen_coords, size=16):
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"""
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obtain channel widths and heights
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"""
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ch_w, ch_h = self.w, self.h
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cen_coords = list(np.array((cen_coords[0])).astype(np.int32))
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self.cen_coords = cen_coords
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"""
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squares are ordered by stacking macbeth chart columns from
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left to right. Some useful patch indices:
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white = 3
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black = 23
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'reds' = 9, 10
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'blues' = 2, 5, 8, 20, 22
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'greens' = 6, 12, 17
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greyscale = 3, 7, 11, 15, 19, 23
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"""
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all_patches = []
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for ch in self.channels:
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ch_patches = []
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for cen in cen_coords:
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'''
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macbeth centre is placed at top left of central 2x2 patch
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to account for rounding
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Patch pixels are sorted by pixel brightness so spatial
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information is lost.
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'''
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patch = ch[cen[1]-7:cen[1]+9, cen[0]-7:cen[0]+9].flatten()
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patch.sort()
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if patch[-5] == (2**self.sigbits-1)*2**(16-self.sigbits):
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self.saturated = True
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ch_patches.append(patch)
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# print('\nNew Patch\n')
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all_patches.append(ch_patches)
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# print('\n\nNew Channel\n\n')
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self.patches = all_patches
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return 1
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def brcm_load_image(Cam, im_str):
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"""
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Load image where raw data and metadata is in the BRCM format
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"""
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try:
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"""
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create byte array
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"""
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with open(im_str, 'rb') as image:
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f = image.read()
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b = bytearray(f)
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"""
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return error if incorrect image address
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"""
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except FileNotFoundError:
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print('\nERROR:\nInvalid image address')
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Cam.log += '\nWARNING: Invalid image address'
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return 0
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"""
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return error if problem reading file
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"""
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if f is None:
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print('\nERROR:\nProblem reading file')
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Cam.log += '\nWARNING: Problem readin file'
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return 0
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# print('\nLooking for EOI and BRCM header')
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"""
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find end of image followed by BRCM header by turning
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bytearray into hex string and string matching with regexp
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"""
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start = -1
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match = bytearray(b'\xff\xd9@BRCM')
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match_str = binascii.hexlify(match)
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b_str = binascii.hexlify(b)
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"""
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note index is divided by two to go from string to hex
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"""
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indices = [m.start()//2 for m in re.finditer(match_str, b_str)]
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# print(indices)
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try:
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start = indices[0] + 3
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except IndexError:
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print('\nERROR:\nNo Broadcom header found')
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Cam.log += '\nWARNING: No Broadcom header found!'
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return 0
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"""
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extract data after header
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"""
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# print('\nExtracting data after header')
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buf = b[start:start+32768]
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Img = Image(buf)
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Img.str = im_str
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# print('Data found successfully')
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"""
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obtain metadata
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"""
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# print('\nReading metadata')
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Img.get_meta()
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Cam.log += '\nExposure : {} us'.format(Img.exposure)
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Cam.log += '\nNormalised gain : {}'.format(Img.againQ8_norm)
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# print('Metadata read successfully')
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"""
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obtain raw image data
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"""
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# print('\nObtaining raw image data')
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raw = b[start+32768:]
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Img.get_image(raw)
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"""
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delete raw to stop memory errors
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"""
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raw = None
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del raw
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# print('Raw image data obtained successfully')
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return Img
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def dng_load_image(Cam, im_str):
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try:
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Img = Image(None)
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# RawPy doesn't load all the image tags that we need, so we use py3exiv2
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metadata = pyexif.ImageMetadata(im_str)
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metadata.read()
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Img.ver = 100 # random value
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"""
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The DNG and TIFF/EP specifications use different IFDs to store the raw
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image data and the Exif tags. DNG stores them in a SubIFD and in an Exif
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IFD respectively (named "SubImage1" and "Photo" by pyexiv2), while
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TIFF/EP stores them both in IFD0 (name "Image"). Both are used in "DNG"
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files, with libcamera-apps following the DNG recommendation and
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applications based on picamera2 following TIFF/EP.
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This code detects which tags are being used, and therefore extracts the
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correct values.
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"""
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try:
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Img.w = metadata['Exif.SubImage1.ImageWidth'].value
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subimage = "SubImage1"
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photo = "Photo"
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except KeyError:
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Img.w = metadata['Exif.Image.ImageWidth'].value
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subimage = "Image"
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photo = "Image"
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Img.pad = 0
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Img.h = metadata[f'Exif.{subimage}.ImageLength'].value
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white = metadata[f'Exif.{subimage}.WhiteLevel'].value
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Img.sigbits = int(white).bit_length()
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Img.fmt = (Img.sigbits - 4) // 2
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Img.exposure = int(metadata[f'Exif.{photo}.ExposureTime'].value * 1000000)
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Img.againQ8 = metadata[f'Exif.{photo}.ISOSpeedRatings'].value * 256 / 100
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Img.againQ8_norm = Img.againQ8 / 256
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Img.camName = metadata['Exif.Image.Model'].value
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Img.blacklevel = int(metadata[f'Exif.{subimage}.BlackLevel'].value[0])
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Img.blacklevel_16 = Img.blacklevel << (16 - Img.sigbits)
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bayer_case = {
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'0 1 1 2': (0, (0, 1, 2, 3)),
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'1 2 0 1': (1, (2, 0, 3, 1)),
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'2 1 1 0': (2, (3, 2, 1, 0)),
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'1 0 2 1': (3, (1, 0, 3, 2))
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}
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cfa_pattern = metadata[f'Exif.{subimage}.CFAPattern'].value
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Img.pattern = bayer_case[cfa_pattern][0]
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Img.order = bayer_case[cfa_pattern][1]
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# Now use RawPy tp get the raw Bayer pixels
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raw_im = raw.imread(im_str)
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raw_data = raw_im.raw_image
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shift = 16 - Img.sigbits
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c0 = np.left_shift(raw_data[0::2, 0::2].astype(np.int64), shift)
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c1 = np.left_shift(raw_data[0::2, 1::2].astype(np.int64), shift)
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c2 = np.left_shift(raw_data[1::2, 0::2].astype(np.int64), shift)
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c3 = np.left_shift(raw_data[1::2, 1::2].astype(np.int64), shift)
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Img.channels = [c0, c1, c2, c3]
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except Exception:
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print("\nERROR: failed to load DNG file", im_str)
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print("Either file does not exist or is incompatible")
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Cam.log += '\nERROR: DNG file does not exist or is incompatible'
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raise
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return Img
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'''
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load image from file location and perform calibration
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check correct filetype
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mac boolean is true if image is expected to contain macbeth chart and false
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if not (alsc images don't have macbeth charts)
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'''
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def load_image(Cam, im_str, mac_config=None, show=False, mac=True, show_meta=False):
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"""
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check image is correct filetype
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"""
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if '.jpg' in im_str or '.jpeg' in im_str or '.brcm' in im_str or '.dng' in im_str:
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if '.dng' in im_str:
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Img = dng_load_image(Cam, im_str)
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else:
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Img = brcm_load_image(Cam, im_str)
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"""
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handle errors smoothly if loading image failed
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"""
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if Img == 0:
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return 0
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if show_meta:
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Img.print_meta()
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if mac:
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"""
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find macbeth centres, discarding images that are too dark or light
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"""
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av_chan = (np.mean(np.array(Img.channels), axis=0)/(2**16))
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av_val = np.mean(av_chan)
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# print(av_val)
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if av_val < Img.blacklevel_16/(2**16)+1/64:
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macbeth = None
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print('\nError: Image too dark!')
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Cam.log += '\nWARNING: Image too dark!'
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else:
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macbeth = find_macbeth(Cam, av_chan, mac_config)
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"""
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if no macbeth found return error
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"""
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if macbeth is None:
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print('\nERROR: No macbeth chart found')
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return 0
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mac_cen_coords = macbeth[1]
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# print('\nMacbeth centres located successfully')
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"""
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obtain image patches
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"""
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# print('\nObtaining image patches')
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Img.get_patches(mac_cen_coords)
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if Img.saturated:
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print('\nERROR: Macbeth patches have saturated')
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Cam.log += '\nWARNING: Macbeth patches have saturated!'
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return 0
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"""
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clear memory
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"""
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Img.buf = None
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del Img.buf
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# print('Image patches obtained successfully')
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"""
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optional debug
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"""
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if show and __name__ == '__main__':
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copy = sum(Img.channels)/2**18
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copy = np.reshape(copy, (Img.h//2, Img.w//2)).astype(np.float64)
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copy, _ = reshape(copy, 800)
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represent(copy)
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return Img
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"""
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return error if incorrect filetype
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"""
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else:
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# print('\nERROR:\nInvalid file extension')
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return 0
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"""
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bytearray splice to number little endian
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"""
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def ba_to_b(b):
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total = 0
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for i in range(len(b)):
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total += 256**i * b[i]
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return total
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