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AgeCommit message (Expand)Author
2022-11-29ipa: raspberrypi: agc: Fix digital gain calculation for manual modeNaushir Patuck
2022-11-29pipeline: ipa: raspberrypi: Use IPA cookiesNaushir Patuck
2022-11-29ipa: raspberrypi: Use an array of RPiController::Metadata objectsNaushir Patuck
2022-11-29ipa: raspberrypi: Add RPiController::Metadata::mergeCopyNaushir Patuck
2022-11-29pipeline: raspberrypi: delayed_controls: Add user cookie to DelayedControlsNaushir Patuck
2022-11-29pipeline: raspberrypi: delayed_controls: Template the ControlRingBuffer classNaushir Patuck
2022-11-29pipeline: raspberrypi: Switch to RPi::DelayedControlsNaushir Patuck
2022-11-29pipeline: raspberrypi: Fork DelayedControlsNaushir Patuck
2022-11-28libcamera: v4l2_device: Workaround faulty control menusKieran Bingham
2022-11-28libcamera: framebuffer_allocator: Avoid double map lookupBarnabás Pőcze
2022-11-25cam: capture_script: Support parsing array controlsJacopo Mondi
2022-11-25pipeline: rkisp1: Support raw Bayer capture configurationFlorian Sylvestre
2022-11-25pipeline: rkisp1: Support raw Bayer capture at runtimeFlorian Sylvestre
2022-11-25pipeline: rkisp1: Fix stream size validationLaurent Pinchart
2022-11-25pipeline: rkisp1: Query the driver for formatsPaul Elder
2022-11-25ipa: rkisp1: agc: Support raw captureLaurent Pinchart
2022-11-25ipa: rkisp1: Add support for manual gain and exposurePaul Elder
2022-11-25ipa: rkisp1: Support raw capture in IPA operationsLaurent Pinchart
2022-11-25libcamera: stream: Turn StreamRole into scoped enumerationLaurent Pinchart
2022-11-25libcamera: stream: Add operator<<() to print StreamRole as a stringLaurent Pinchart
2022-11-25utils: tuning: Add tuning script for rkisp1Paul Elder
2022-11-25utils: tuning: Add alsc-only libtuning raspberrypi tuning scriptPaul Elder
2022-11-25utils: libtuning: generators: Add yaml outputPaul Elder
2022-11-25utils: libtuning: parsers: Add yaml parserPaul Elder
2022-11-25utils: libtuning: generators: Add raspberrypi outputPaul Elder
2022-11-25utils: libtuning: parsers: Add raspberrypi parserPaul Elder
2022-11-25utils: libtuning: modules: alsc: Add rkisp1 LSC modulePaul Elder
2022-11-25utils: libtuning: modules: alsc: Add raspberrypi ALSC modulePaul Elder
2022-11-25utils: libtuning: modules: Add base LSC modulePaul Elder
2022-11-25utils: tuning: libtuning: Implement extensible components of libtuningPaul Elder
2022-11-25utils: tuning: libtuning: Implement math helpersPaul Elder
2022-11-25utils: tuning: libtuning: Implement the core of libtuningPaul Elder
2022-11-24libcamera: tracing: fix header generation when built as subprojectBarnabás Pőcze
2022-11-24libcamera: Test sensor's ability to discover ancillary devicesYunke Cao
2022-11-23ipa: rkisp1: add FrameDurationLimits controlNicholas Roth
2022-11-23ipa: rkisp1: Fail hard on empty CameraSensorInfoJacopo Mondi
2022-11-23ipa: rkisp1: Use IPAConfig in IPA::configure()Jacopo Mondi
2022-11-23libcamera: Move IPA sensor controls validation to CameraSensorJacopo Mondi
2022-11-23pipeline: raspberrypi: Remove enum BuffferMask from the mojom interfaceNaushir Patuck
2022-11-21ipa: raspberrypi: Remove generic "pause" mechanism from AlgorithmNick Hollinghurst
2022-11-21pipeline: imx8-isi: Set SensorTimestamp metadataLaurent Pinchart
2022-11-21libcamera: imx8-isi: Enumerate supported stream formatsJacopo Mondi
2022-11-21gstreamer: Do not lookup controls by idJacopo Mondi
2022-11-19apps: cam: kms: Avoid 'unused-parameter' warningsChristian Rauch
2022-11-18libcamera v0.0.2v0.0.2Kieran Bingham
2022-11-17libcamera: pipeline: Add IMX8 ISI pipelineJacopo Mondi
2022-11-14libcamera: pipeline: raspberrypi: Free buffers when a camera is releasedDavid Plowman
2022-11-14libcamera: Add a PipelineHandler::releaseDevice methodDavid Plowman
2022-11-14Revert "pipeline: raspberrypi: Do not unconditionally free buffers on close"David Plowman
2022-11-14libcamera: v4l2_videodevice: Reduce zero sequence warning log levelKieran Bingham
generated by cgit v1.2.1 (git 2.18.0) at 2025-02-13 11:01:26 +0000
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# SPDX-License-Identifier: BSD-2-Clause
#
# Copyright (C) 2019-2020, Raspberry Pi (Trading) Limited
#
# ctt_image_load.py - camera tuning tool image loading

from ctt_tools import *
from ctt_macbeth_locator import *
import json
import pyexiv2 as pyexif
import rawpy as raw


"""
Image class load image from raw data and extracts metadata.

Once image is extracted from data, it finds 24 16x16 patches for each
channel, centred at the macbeth chart squares
"""
class Image:
    def __init__(self, buf):
        self.buf = buf
        self.patches = None
        self.saturated = False

    '''
    obtain metadata from buffer
    '''
    def get_meta(self):
        self.ver = ba_to_b(self.buf[4:5])
        self.w = ba_to_b(self.buf[0xd0:0xd2])
        self.h = ba_to_b(self.buf[0xd2:0xd4])
        self.pad = ba_to_b(self.buf[0xd4:0xd6])
        self.fmt = self.buf[0xf5]
        self.sigbits = 2*self.fmt + 4
        self.pattern = self.buf[0xf4]
        self.exposure = ba_to_b(self.buf[0x90:0x94])
        self.againQ8 = ba_to_b(self.buf[0x94:0x96])
        self.againQ8_norm = self.againQ8/256
        camName = self.buf[0x10:0x10+128]
        camName_end = camName.find(0x00)
        self.camName = self.buf[0x10:0x10+128][:camName_end].decode()

        """
        Channel order depending on bayer pattern
        """
        bayer_case = {
            0: (0, 1, 2, 3),   # red
            1: (2, 0, 3, 1),   # green next to red
            2: (3, 2, 1, 0),   # green next to blue
            3: (1, 0, 3, 2),   # blue
            128: (0, 1, 2, 3)  # arbitrary order for greyscale casw
        }
        self.order = bayer_case[self.pattern]

        '''
        manual blacklevel - not robust
        '''
        if 'ov5647' in self.camName:
            self.blacklevel = 16
        else:
            self.blacklevel = 64
        self.blacklevel_16 = self.blacklevel << (6)
        return 1

    '''
    print metadata for debug
    '''
    def print_meta(self):
        print('\nData:')
        print('      ver = {}'.format(self.ver))
        print('      w = {}'.format(self.w))
        print('      h = {}'.format(self.h))
        print('      pad = {}'.format(self.pad))
        print('      fmt = {}'.format(self.fmt))
        print('      sigbits = {}'.format(self.sigbits))
        print('      pattern = {}'.format(self.pattern))
        print('      exposure = {}'.format(self.exposure))
        print('      againQ8 = {}'.format(self.againQ8))
        print('      againQ8_norm = {}'.format(self.againQ8_norm))
        print('      camName = {}'.format(self.camName))
        print('      blacklevel = {}'.format(self.blacklevel))
        print('      blacklevel_16 = {}'.format(self.blacklevel_16))

        return 1

    """
    get image from raw scanline data
    """
    def get_image(self, raw):
        self.dptr = []
        """
        check if data is 10 or 12 bits
        """
        if self.sigbits == 10:
            """
            calc length of scanline
            """
            lin_len = ((((((self.w+self.pad+3)>>2)) * 5)+31)>>5) * 32
            """
            stack scan lines into matrix
            """
            raw = np.array(raw).reshape(-1, lin_len).astype(np.int64)[:self.h, ...]
            """
            separate 5 bits in each package, stopping when w is satisfied
            """
            ba0 = raw[..., 0:5*((self.w+3)>>2):5]
            ba1 = raw[..., 1:5*((self.w+3)>>2):5]
            ba2 = raw[..., 2:5*((self.w+3)>>2):5]
            ba3 = raw[..., 3:5*((self.w+3)>>2):5]
            ba4 = raw[..., 4:5*((self.w+3)>>2):5]
            """
            assemble 10 bit numbers
            """
            ch0 = np.left_shift((np.left_shift(ba0, 2) + (ba4 % 4)), 6)
            ch1 = np.left_shift((np.left_shift(ba1, 2) + (np.right_shift(ba4, 2) % 4)), 6)
            ch2 = np.left_shift((np.left_shift(ba2, 2) + (np.right_shift(ba4, 4) % 4)), 6)
            ch3 = np.left_shift((np.left_shift(ba3, 2) + (np.right_shift(ba4, 6) % 4)), 6)
            """
            interleave bits
            """
            mat = np.empty((self.h, self.w), dtype=ch0.dtype)

            mat[..., 0::4] = ch0
            mat[..., 1::4] = ch1
            mat[..., 2::4] = ch2
            mat[..., 3::4] = ch3

            """
            There is som eleaking memory somewhere in the code. This code here
            seemed to make things good enough that the code would run for
            reasonable numbers of images, however this is techincally just a
            workaround. (sorry)
            """
            ba0, ba1, ba2, ba3, ba4 = None, None, None, None, None
            del ba0, ba1, ba2, ba3, ba4
            ch0, ch1, ch2, ch3 = None, None, None, None
            del ch0, ch1, ch2, ch3

            """
        same as before but 12 bit case
        """
        elif self.sigbits == 12:
            lin_len = ((((((self.w+self.pad+1)>>1)) * 3)+31)>>5) * 32
            raw = np.array(raw).reshape(-1, lin_len).astype(np.int64)[:self.h, ...]
            ba0 = raw[..., 0:3*((self.w+1)>>1):3]
            ba1 = raw[..., 1:3*((self.w+1)>>1):3]
            ba2 = raw[..., 2:3*((self.w+1)>>1):3]
            ch0 = np.left_shift((np.left_shift(ba0, 4) + ba2 % 16), 4)
            ch1 = np.left_shift((np.left_shift(ba1, 4) + (np.right_shift(ba2, 4)) % 16), 4)
            mat = np.empty((self.h, self.w), dtype=ch0.dtype)
            mat[..., 0::2] = ch0
            mat[..., 1::2] = ch1

        else:
            """
            data is neither 10 nor 12 or incorrect data
            """
            print('ERROR: wrong bit format, only 10 or 12 bit supported')
            return 0

        """
        separate bayer channels
        """
        c0 = mat[0::2, 0::2]
        c1 = mat[0::2, 1::2]
        c2 = mat[1::2, 0::2]
        c3 = mat[1::2, 1::2]
        self.channels = [c0, c1, c2, c3]
        return 1

    """
    obtain 16x16 patch centred at macbeth square centre for each channel
    """
    def get_patches(self, cen_coords, size=16):
        """
        obtain channel widths and heights
        """
        ch_w, ch_h = self.w, self.h
        cen_coords = list(np.array((cen_coords[0])).astype(np.int32))
        self.cen_coords = cen_coords
        """
        squares are ordered by stacking macbeth chart columns from
        left to right. Some useful patch indices:
            white = 3
            black = 23
            'reds' = 9, 10
            'blues' = 2, 5, 8, 20, 22
            'greens' = 6, 12, 17
            greyscale = 3, 7, 11, 15, 19, 23
        """
        all_patches = []
        for ch in self.channels:
            ch_patches = []
            for cen in cen_coords:
                '''
                macbeth centre is placed at top left of central 2x2 patch
                to account for rounding
                Patch pixels are sorted by pixel brightness so spatial
                information is lost.
                '''
                patch = ch[cen[1]-7:cen[1]+9, cen[0]-7:cen[0]+9].flatten()
                patch.sort()
                if patch[-5] == (2**self.sigbits-1)*2**(16-self.sigbits):
                    self.saturated = True
                ch_patches.append(patch)
                # print('\nNew Patch\n')
            all_patches.append(ch_patches)
            # print('\n\nNew Channel\n\n')
        self.patches = all_patches
        return 1


def brcm_load_image(Cam, im_str):
    """
    Load image where raw data and metadata is in the BRCM format
    """
    try:
        """
        create byte array
        """
        with open(im_str, 'rb') as image:
            f = image.read()
            b = bytearray(f)
        """
        return error if incorrect image address
        """
    except FileNotFoundError:
        print('\nERROR:\nInvalid image address')
        Cam.log += '\nWARNING: Invalid image address'
        return 0

    """
    return error if problem reading file
    """
    if f is None:
        print('\nERROR:\nProblem reading file')
        Cam.log += '\nWARNING: Problem readin file'
        return 0

    # print('\nLooking for EOI and BRCM header')
    """
    find end of image followed by BRCM header by turning
    bytearray into hex string and string matching with regexp
    """
    start = -1
    match = bytearray(b'\xff\xd9@BRCM')
    match_str = binascii.hexlify(match)
    b_str = binascii.hexlify(b)
    """
    note index is divided by two to go from string to hex
    """
    indices = [m.start()//2 for m in re.finditer(match_str, b_str)]
    # print(indices)
    try:
        start = indices[0] + 3
    except IndexError:
        print('\nERROR:\nNo Broadcom header found')
        Cam.log += '\nWARNING: No Broadcom header found!'
        return 0
    """
    extract data after header
    """
    # print('\nExtracting data after header')
    buf = b[start:start+32768]
    Img = Image(buf)
    Img.str = im_str
    # print('Data found successfully')

    """
    obtain metadata
    """
    # print('\nReading metadata')
    Img.get_meta()
    Cam.log += '\nExposure : {} us'.format(Img.exposure)
    Cam.log += '\nNormalised gain : {}'.format(Img.againQ8_norm)
    # print('Metadata read successfully')

    """
    obtain raw image data
    """
    # print('\nObtaining raw image data')
    raw = b[start+32768:]
    Img.get_image(raw)
    """
    delete raw to stop memory errors
    """
    raw = None
    del raw
    # print('Raw image data obtained successfully')

    return Img


def dng_load_image(Cam, im_str):
    try:
        Img = Image(None)

        # RawPy doesn't load all the image tags that we need, so we use py3exiv2
        metadata = pyexif.ImageMetadata(im_str)
        metadata.read()

        Img.ver = 100  # random value
        Img.w = metadata['Exif.SubImage1.ImageWidth'].value
        Img.pad = 0
        Img.h = metadata['Exif.SubImage1.ImageLength'].value
        white = metadata['Exif.SubImage1.WhiteLevel'].value
        Img.sigbits = int(white).bit_length()
        Img.fmt = (Img.sigbits - 4) // 2
        Img.exposure = int(metadata['Exif.Photo.ExposureTime'].value*1000000)
        Img.againQ8 = metadata['Exif.Photo.ISOSpeedRatings'].value*256/100
        Img.againQ8_norm = Img.againQ8 / 256
        Img.camName = metadata['Exif.Image.Model'].value
        Img.blacklevel = int(metadata['Exif.SubImage1.BlackLevel'].value[0])
        Img.blacklevel_16 = Img.blacklevel << (16 - Img.sigbits)
        bayer_case = {
            '0 1 1 2': (0, (0, 1, 2, 3)),
            '1 2 0 1': (1, (2, 0, 3, 1)),
            '2 1 1 0': (2, (3, 2, 1, 0)),
            '1 0 2 1': (3, (1, 0, 3, 2))
        }
        cfa_pattern = metadata['Exif.SubImage1.CFAPattern'].value
        Img.pattern = bayer_case[cfa_pattern][0]
        Img.order = bayer_case[cfa_pattern][1]

        # Now use RawPy tp get the raw Bayer pixels
        raw_im = raw.imread(im_str)
        raw_data = raw_im.raw_image
        shift = 16 - Img.sigbits
        c0 = np.left_shift(raw_data[0::2, 0::2].astype(np.int64), shift)
        c1 = np.left_shift(raw_data[0::2, 1::2].astype(np.int64), shift)
        c2 = np.left_shift(raw_data[1::2, 0::2].astype(np.int64), shift)
        c3 = np.left_shift(raw_data[1::2, 1::2].astype(np.int64), shift)
        Img.channels = [c0, c1, c2, c3]

    except Exception:
        print("\nERROR: failed to load DNG file", im_str)
        print("Either file does not exist or is incompatible")
        Cam.log += '\nERROR: DNG file does not exist or is incompatible'
        raise

    return Img


'''
load image from file location and perform calibration
check correct filetype

mac boolean is true if image is expected to contain macbeth chart and false
if not (alsc images don't have macbeth charts)
'''