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path: root/utils/raspberrypi/ctt
AgeCommit message (Expand)Author
2024-06-13utils: raspberrypi: ctt: Add a maximum gain parameter for LSCDavid Plowman
2024-06-13utils: raspberrypi: ctt: Add option to convert between vc4/pisp targetsNaushir Patuck
2024-06-13utils: raspberrypi: ctt: Update tuning tool for HDRDavid Plowman
2024-06-13utils: raspberrypi: ctt: Changed CTT handling of VC4 and PiSPBen Benson
2024-06-13utils: raspberrypi: ctt: Added CAC support to the CTTBen Benson
2024-06-13utils: raspberrypi: ctt: Adapt tuning tool for both VC4 and PiSPDavid Plowman
2024-05-08libcamera: Drop file name from header comment blocksLaurent Pinchart
2024-04-20libcamera: Fix output spelling errorUmang Jain
2024-01-09utils: raspberrypi: ctt: Improve the Macbeth Chart search reliabilityDavid Plowman
2023-07-28utils: raspberrypi: ctt: Code tidyingBen Benson
2023-07-28utils: raspberrypi: ctt: Improved color matrix fittingBen Benson
2022-10-20utils: raspberrypi: ctt: Fix alsc green averagingPaul Elder
2022-08-03utils: raspberrypi: ctt: dng_load_image: Work with DNG files from Picamera2William Vinnicombe
2022-08-02utils: raspberrypi: ctt: Add alsc_only methodWilliam Vinnicombe
2022-07-28utils: raspberrypi: Add tuning file conversion scriptNaushir Patuck
2022-07-28utils: raspberrypi: ctt: Output version 2.0 format tuning filesNaushir Patuck
2022-07-27raspberrypi: Update Copyright statement in all Raspberry Pi source filesNaushir Patuck
2022-07-06utils: raspberrypi: ctt: load_image: Ignore JPEG files with no raw dataWilliam Vinnicombe
2021-08-03utils: raspberrypi: ctt: Fix namespace for sklearn NearestCentroid functionDavid Plowman
2021-08-02utils: raspberrypi: ctt: Fix usage of findHomography functionDavid Plowman
2020-11-20src: ipa: raspberrypi: Change 'sport' exposure mode name to 'short'David Plowman
2020-07-03utils: raspberrypi: ctt: json_pretty_print: Add newline at end of outputLaurent Pinchart
2020-07-03utils: raspberrypi: ctt: json_pretty_print: Avoid spaces at end of linesLaurent Pinchart
2020-07-03utils: raspberrypi: ctt: json_pretty_print: Collapse newlinesLaurent Pinchart
2020-07-03utils: raspberrypi: ctt: json_pretty_print: Fix indentation handlingLaurent Pinchart
2020-07-03utils: raspberrypi: ctt: json_pretty_print: Add character write methodLaurent Pinchart
2020-07-03utils: raspberrypi: ctt: json_pretty_print: Skip all spacesLaurent Pinchart
2020-07-03utils: raspberrypi: ctt: json_pretty_print: Make test output to stdoutLaurent Pinchart
2020-07-03utils: raspberrypi: ctt: json_pretty_print: Make output file a class memberLaurent Pinchart
2020-07-03utils: raspberrypi: ctt: json_pretty_print: Turn printer into a classLaurent Pinchart
2020-07-03utils: raspberrypi: ctt: json_pretty_print: Fix printer testLaurent Pinchart
2020-06-29utils: raspberrypi: ctt: Fix pycodestyle W605Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E302Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E305Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E741Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle W504Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E722Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E721Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E713Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E116 and E117Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E123 and E126Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E711 and E712Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E222Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E261 and E262Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E303Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E701Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E228Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E225Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E128Laurent Pinchart
2020-05-13utils: raspberrypi: ctt: Fix pycodestyle E251Laurent Pinchart
generated by cgit v1.2.1 (git 2.18.0) at 2025-02-11 18:40:11 +0000
- 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) ''' def load_image(Cam, im_str, mac_config=None, show=False, mac=True, show_meta=False): """ check image is correct filetype """ if '.jpg' in im_str or '.jpeg' in im_str or '.brcm' in im_str or '.dng' in im_str: if '.dng' in im_str: Img = dng_load_image(Cam, im_str) else: Img = brcm_load_image(Cam, im_str) if show_meta: Img.print_meta() if mac: """ find macbeth centres, discarding images that are too dark or light """ av_chan = (np.mean(np.array(Img.channels), axis=0)/(2**16)) av_val = np.mean(av_chan) # print(av_val) if av_val < Img.blacklevel_16/(2**16)+1/64: macbeth = None print('\nError: Image too dark!') Cam.log += '\nWARNING: Image too dark!' else: macbeth = find_macbeth(Cam, av_chan, mac_config) """ if no macbeth found return error """ if macbeth is None: print('\nERROR: No macbeth chart found') return 0 mac_cen_coords = macbeth[1] # print('\nMacbeth centres located successfully') """ obtain image patches """ # print('\nObtaining image patches') Img.get_patches(mac_cen_coords) if Img.saturated: print('\nERROR: Macbeth patches have saturated') Cam.log += '\nWARNING: Macbeth patches have saturated!' return 0 """ clear memory """ Img.buf = None del Img.buf # print('Image patches obtained successfully') """ optional debug """ if show and __name__ == '__main__': copy = sum(Img.channels)/2**18 copy = np.reshape(copy, (Img.h//2, Img.w//2)).astype(np.float64) copy, _ = reshape(copy, 800) represent(copy) return Img """ return error if incorrect filetype """ else: # print('\nERROR:\nInvalid file extension') return 0 """ bytearray splice to number little endian """ def ba_to_b(b): total = 0 for i in range(len(b)): total += 256**i * b[i] return total
generated by cgit v1.2.1 (git 2.18.0) at 2025-02-11 18:40:10 +0000