def aux(rootdir, level=0):
pad = ' ' * level
dirpaths, filepaths = collect_dirs_and_files(rootdir)
filepaths_by_ext = sort_files_by_ext(filepaths)
if filepaths_by_ext:
for ext, filepaths in sorted(filepaths_by_ext.items()):
seq = FileSequence.load(filepaths)
if seq:
range_str = ', '.join(
['(%d-%d)' % (lo, hi) for lo, hi in seq.ranges])
print('%s %s | %4d | %s' %
(pad, ext.ljust(8), len(filepaths), range_str))
else:
print('%s %s | %4d ' %
(pad, ext.ljust(8), len(filepaths)))
elif not dirpaths:
print('%s (empty)' % pad)
for dirpath in dirpaths:
print('%s %s:' % (pad, os.path.basename(dirpath)))
aux(dirpath, level + 1)
def run(cls, args):
print('Collection: %s' % os.path.basename(args.collection))
print(' Subdir: %s' % (args.subdir or '<ROOT>'))
print('')
images_dir = os.path.normpath(
os.path.join(args.collection, args.subdir))
_, filepaths = collect_dirs_and_files(images_dir)
filepaths_by_ext = sort_files_by_ext(filepaths)
cr2_files = filepaths_by_ext.get('.cr2', [])
if cr2_files:
seq = FileSequence.load(cr2_files)
if seq:
range_str = ', '.join(
['(%d-%d)' % (lo, hi) for lo, hi in seq.ranges])
print('%d image files found: %s' % (len(cr2_files), range_str))
else:
print('%d image files found.' % len(cr2_files))
else:
raise RuntimeError('No .cr2 image files found')
print('Setting exposure delta to %+0.2f EV...' % args.ev_delta)
print('')
changed_count = 0
unchanged_count = 0
for image_filepath in sorted(cr2_files):
old_ev_delta = read_param(image_filepath, 'ev_delta', 0.0)
if old_ev_delta == args.ev_delta:
unchanged_count += 1
else:
print('%s: %+0.2f EV --> %+0.2f EV' %
(os.path.basename(image_filepath), old_ev_delta,
args.ev_delta))
write_param(image_filepath, 'ev_delta', args.ev_delta)
changed_count += 1
print('')
print('Updated params for %d images; left %d images unchanged.' %
(changed_count, unchanged_count))
if changed_count:
print('Run fma dt-apply to apply changes to .xmp files.')
def run(cls, args):
print('Collection: %s' % os.path.basename(args.collection))
print(' Subdir: %s' % (args.subdir or '<ROOT>'))
print('')
images_dir = os.path.normpath(os.path.join(args.collection, args.subdir))
_, filepaths = collect_dirs_and_files(images_dir)
xmp_files = sort_files_by_ext(filepaths).get('.cr2.xmp', [])
if xmp_files:
seq = FileSequence.load(xmp_files)
if seq:
range_str = ', '.join(['(%d-%d)' % (lo, hi) for lo, hi in seq.ranges])
print('%d sidecar files found: %s' % (len(xmp_files), range_str))
else:
print('%d sidecar files found.' % len(xmp_files))
if not args.force:
print('')
print('These existing sidecar files contain edits made in darktable.')
print('Clearing these files will DELETE these previously-made edits.')
print('If you\'re sure you want to do that, re-run with -f.')
return
else:
print('No .xmp sidecar files found.')
return
print('')
print('Deleting %d sidecar files...' % len(xmp_files))
num_deleted = 0
for filepath in xmp_files:
print('DELETE %s' % os.path.basename(filepath))
os.remove(filepath)
num_deleted += 1
print('')
print('Deleted %d files.' % num_deleted)
print('Regenerating .xmp sidecar files...')
regenerate_xmps(images_dir)
def run(cls, args):
print('Collection: %s' % os.path.basename(args.collection))
print(' Subdir: %s' % (args.subdir or '<ROOT>'))
print('')
images_dir = os.path.normpath(os.path.join(args.collection, args.subdir))
_, filepaths = collect_dirs_and_files(images_dir)
filepaths_by_ext = sort_files_by_ext(filepaths)
cr2_files = filepaths_by_ext.get('.cr2', [])
if cr2_files:
seq = FileSequence.load(cr2_files)
if seq:
range_str = ', '.join(['(%d-%d)' % (lo, hi) for lo, hi in seq.ranges])
print('%d image files found: %s' % (len(cr2_files), range_str))
else:
print('%d image files found.' % len(cr2_files))
else:
raise RuntimeError('No .cr2 image files found')
print('')
print('Launching darktable...')
run_darktable([images_dir])
def run(cls, args):
print('Collection: %s' % os.path.basename(args.collection))
print(' Subdir: %s' % (args.subdir or '<ROOT>'))
print('')
images_dir = os.path.normpath(
os.path.join(args.collection, args.subdir))
_, filepaths = collect_dirs_and_files(images_dir)
cr2_files = sort_files_by_ext(filepaths).get('.cr2', [])
seq = FileSequence.load(cr2_files) if cr2_files else None
if not seq:
raise RuntimeError('No .cr2 image sequence found')
print('Generating image cache...')
generate_cache(images_dir)
tmp_dirpath = os.path.join(images_dir, '.temp-sides')
with temporary_directory(tmp_dirpath):
os.startfile(tmp_dirpath)
backs_dirpath = os.path.join(tmp_dirpath, 'backs')
os.makedirs(backs_dirpath)
cr2_filepath_lookup = {}
for image_filepath, cached_filepath in image_iterator(images_dir):
short_filename = os.path.basename(cached_filepath)
cr2_filepath_lookup[short_filename] = image_filepath
img = cv2.imread(cached_filepath)
img = cv2.resize(img, (img.shape[1] // 4, img.shape[0] // 4))
is_back = None
image_params = read_params(image_filepath)
if image_params.get('side') in ('front', 'back'):
is_back = image_params.get('side') == 'back'
print('%s -- loaded -- %s' %
(short_filename, 'back' if is_back else 'FRONT'))
if is_back is None:
corner_size_factor = image_params.get(
'crop_corner_size_factor', CORNER_SIZE_FACTOR)
key_range_h = image_params.get('crop_key_range_h',
KEY_RANGE_HSV[0])
key_range_s = image_params.get('crop_key_range_S',
KEY_RANGE_HSV[1])
key_range_v = image_params.get('crop_key_range_v',
KEY_RANGE_HSV[2])
erosion_size = image_params.get('crop_erosion_size',
EROSION_SIZE)
dilation_size = image_params.get('crop_dilation_size',
DILATION_SIZE)
mask = get_background_mask(
img, corner_size_factor,
[key_range_h, key_range_s, key_range_v], erosion_size,
dilation_size)
alpha = cv2.erode(~mask,
np.ones((5, 5), np.uint8),
iterations=5)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
res = cv2.adaptiveThreshold(gray, 255,
cv2.ADAPTIVE_THRESH_MEAN_C,
cv2.THRESH_BINARY_INV, 7, 5.0)
res = cv2.bitwise_and(res, res, mask=alpha)
percentage = np.count_nonzero(res) / np.count_nonzero(
alpha)
is_back = percentage < args.threshold
print('%s -- % 5.1f%% -- %s' %
(short_filename, percentage * 100.0,
'back' if is_back else 'FRONT'))
dst_dirpath = backs_dirpath if is_back else tmp_dirpath
dst_filepath = os.path.join(dst_dirpath, short_filename)
cv2.imwrite(dst_filepath, img)
print('')
print(
'Please check the .temp-sides directory and move any back images to backs folder.'
)
print(
'Then check the backs folder and make sure it doesn\'t contain any front images.'
)
input('Once all images are sorted, press enter to proceed.')
for filename in os.listdir(tmp_dirpath):
cr2_filepath = cr2_filepath_lookup.get(filename)
if cr2_filepath:
print('%s - front' % filename)
write_param(cr2_filepath, 'side', 'front')
for filename in os.listdir(backs_dirpath):
cr2_filepath = cr2_filepath_lookup.get(filename)
if cr2_filepath:
print('%s - back' % filename)
write_param(cr2_filepath, 'side', 'back')
def run(cls, args):
print('Collection: %s' % os.path.basename(args.collection))
print(' Subdir: %s' % (args.subdir or '<ROOT>'))
print('')
images_dir = os.path.normpath(os.path.join(args.collection, args.subdir))
_, filepaths = collect_dirs_and_files(images_dir)
filepaths_by_ext = sort_files_by_ext(filepaths)
cr2_files = filepaths_by_ext.get('.cr2', [])
if cr2_files:
seq = FileSequence.load(cr2_files)
if seq:
range_str = ', '.join(['(%d-%d)' % (lo, hi) for lo, hi in seq.ranges])
print('%d image files found: %s' % (len(cr2_files), range_str))
else:
print('%d image files found.' % len(cr2_files))
else:
raise RuntimeError('No .cr2 image files found')
xmp_files = filepaths_by_ext.get('.cr2.xmp', [])
if xmp_files:
seq = FileSequence.load(xmp_files)
if seq:
range_str = ', '.join(['(%d-%d)' % (lo, hi) for lo, hi in seq.ranges])
print('%d sidecar files found: %s' % (len(xmp_files), range_str))
else:
print('%d sidecar files found.' % len(xmp_files))
if not args.force:
print('')
print('These existing sidecar files contain edits made in darktable.')
print('Applying these edits will DELETE these previously-made edits.')
print('If you\'re sure you want to do that, re-run with -f.')
return
print('')
print('Generating image cache...')
generate_cache(images_dir)
print('Regenerating .xmp sidecar files...')
regenerate_xmps(images_dir)
for image_filepath, cached_filepath in image_iterator(images_dir):
iops = []
image_params = read_params(image_filepath)
try:
crop_params = compute_crop_params(cached_filepath, image_params)
print ('%s -> %r' % (os.path.basename(image_filepath), crop_params))
iop_clipping = dt_iop_clipping_params_t()
iop_clipping.crop_auto = 0
iop_clipping.angle = crop_params['angle']
iop_clipping.cx = crop_params['cx']
iop_clipping.cy = crop_params['cy']
iop_clipping.cw = crop_params['cw']
iop_clipping.ch = crop_params['ch']
iops.append(iop_clipping)
except Exception as exc:
print('WARNING: Failed to crop %s: %s' % (os.path.basename(image_filepath), exc))
ev_delta = image_params.get('ev_delta')
if ev_delta:
iop_exposure = dt_iop_exposure_params_t()
iop_exposure.exposure = ev_delta
iops.append(iop_exposure)
xmp_filepath = image_filepath + '.xmp'
if iops:
edit_xmp(xmp_filepath, iops)
print('%s: %s' % (os.path.basename(xmp_filepath), ', '.join([iop.operation for iop in iops])))
else:
print('%s: <skipped>' % (os.path.basename(xmp_filepath)))
print('Launching darktable. Reimport all changed .xmp files when prompted.')
run_darktable([images_dir])
def run(cls, args):
print('Collection: %s' % os.path.basename(args.collection))
print(' Subdir: %s' % (args.subdir or '<ROOT>'))
print('')
images_dir = os.path.normpath(os.path.join(args.collection, args.subdir))
_, filepaths = collect_dirs_and_files(images_dir)
cr2_files = sort_files_by_ext(filepaths).get('.cr2', [])
seq = FileSequence.load(cr2_files) if cr2_files else None
if not seq:
raise RuntimeError('No .cr2 image sequence found')
cr2_filepath = seq.pattern % (args.image or seq.ranges[0][0])
if not os.path.isfile(cr2_filepath):
raise RuntimeError('No such file: %s' % cr2_filepath)
cached_filepath = get_cached_image_filepath(cr2_filepath)
if not os.path.isfile(cached_filepath):
print('Generating cached image...')
regenerate_cached_image(cr2_filepath)
img = cv2.imread(cached_filepath)
img = cv2.resize(img, (img.shape[1] // 4, img.shape[0] // 4))
modes = ['original', 'color key', 'corners']
mode_index = len(modes) - 1
corner_size_factor = read_param(cr2_filepath, 'crop_corner_size_factor', 0.05)
key_range_h = read_param(cr2_filepath, 'crop_key_range_h', 4.0)
key_range_s = read_param(cr2_filepath, 'crop_key_range_s', 25.0)
key_range_v = read_param(cr2_filepath, 'crop_key_range_v', 25.0)
erosion_size = read_param(cr2_filepath, 'crop_erosion_size', 5)
dilation_size = read_param(cr2_filepath, 'crop_dilation_size', 0)
min_line_length_factor = read_param(cr2_filepath, 'crop_min_line_length_factor', 0.005)
max_line_gap_factor = read_param(cr2_filepath, 'crop_max_line_gap_factor', 0.001)
max_inclination_deg = read_param(cr2_filepath, 'crop_max_inclination_deg', 10.0)
line_exclusion_size_factor = read_param(cr2_filepath, 'crop_line_exclusion_size_factor', 0.1)
num_clusters = read_param(cr2_filepath, 'crop_num_clusters', 8)
cluster_merge_threshold_size_factor = read_param(cr2_filepath, 'crop_cluster_merge_threshold_size_factor', 0.025)
inset_interval = read_param(cr2_filepath, 'crop_inset_interval', 1.0)
inset_white_threshold = read_param(cr2_filepath, 'crop_inset_white_threshold', 0.0025)
extra_inset = read_param(cr2_filepath, 'crop_extra_inset', 8.0)
save_prompted = False
while True:
mode = modes[mode_index]
if mode_index >= modes.index('color key'):
mask = get_background_mask(img, corner_size_factor, [key_range_h, key_range_s, key_range_v], erosion_size, dilation_size)
if mode_index >= modes.index('corners'):
rect_corners = find_rectilinear_corners(mask, min_line_length_factor, max_line_gap_factor, max_inclination_deg, line_exclusion_size_factor, num_clusters, cluster_merge_threshold_size_factor)
corners = shrink_inside_mask(mask, rect_corners, inset_interval, inset_white_threshold, extra_inset * 0.25) if rect_corners else None
base = None
if mode == 'original':
base = img.copy()
elif mode == 'color key':
base = cv2.cvtColor(mask, cv2.COLOR_GRAY2RGB)
elif mode == 'corners':
base = img.copy()
if corners:
top_left = int(corners[Corner.top_left][0]), int(corners[Corner.top_left][1])
top_right = int(corners[Corner.top_right][0]), int(corners[Corner.top_right][1])
bottom_left = int(corners[Corner.bottom_left][0]), int(corners[Corner.bottom_left][1])
bottom_right = int(corners[Corner.bottom_right][0]), int(corners[Corner.bottom_right][1])
cv2.line(base, top_left, top_right, (255, 192, 192), 2)
cv2.line(base, top_right, bottom_right, (255, 192, 192), 2)
cv2.line(base, bottom_right, bottom_left, (255, 192, 192), 2)
cv2.line(base, bottom_left, top_left, (255, 192, 192), 2)
else:
raise RuntimeError('Unsupported mode: %s' % mode)
height, width = base.shape[0], base.shape[1]
long_side = height if height > width else width
short_side = width if height > width else height
size = min(short_side // 2, max(1, int(long_side * corner_size_factor)))
cv2.rectangle(base, (0, 0), (size, size), (255, 192, 128), 1)
cv2.rectangle(base, (base.shape[1] - size, 0), (base.shape[1], size), (255, 192, 128), 1)
cv2.rectangle(base, (0, base.shape[0] - size), (size, base.shape[0]), (255, 192, 128), 1)
cv2.rectangle(base, (base.shape[1] - size, base.shape[0] - size), (base.shape[1], base.shape[0]), (255, 192, 128), 1)
mode_labels = [('[%s]' % m) if m == mode else m for m in modes]
controls_label(0, 'MODE (,|.): %s' % ' | '.join(mode_labels), base)
controls_label(2, 'COLOR KEY:', base)
float_control(3, corner_size_factor, 'corner_size', base, 'C')
float_control(4, key_range_h, 'key_range_h', base, 'H')
float_control(5, key_range_s, 'key_range_s', base, 'S')
float_control(6, key_range_v, 'key_range_v', base, 'V')
int_control(7, erosion_size, 'erosion_size', base, 'E')
int_control(8, dilation_size, 'dilation_size', base, 'D')
controls_label(10, 'CORNERS:', base)
float_control(11, min_line_length_factor, 'min_line_length_factor', base, 'L')
float_control(12, max_line_gap_factor, 'max_line_gap_factor', base, 'G')
float_control(13, max_inclination_deg, 'max_inclination_deg', base, 'I')
float_control(14, line_exclusion_size_factor, 'line_exclusion_size_factor', base, 'X')
int_control(15, num_clusters, 'num_clusters', base, 'N')
float_control(16, cluster_merge_threshold_size_factor, 'cluster_merge_threshold', base, 'M')
float_control(17, inset_interval, 'inset_interval', base, 'T')
float_control(18, inset_white_threshold, 'inset_white_threshold', base, 'W')
float_control(19, extra_inset, 'extra_inset', base, 'Z')
if save_prompted:
draw_text(base, (400, 400), 'Press ENTER to save settings for all images in collection.')
draw_text(base, (500, 420), '(Press any other key to cancel.)')
cv2.imshow('image', base)
key = cv2.waitKeyEx(0)
if key in (27, ord('q'), ord('Q')):
break
if key == 13:
if save_prompted:
num_saved = 0
for num in seq.numbers:
filepath = seq.pattern % num
params = read_params(filepath)
params['crop_corner_size_factor'] = corner_size_factor
params['crop_key_range_h'] = key_range_h
params['crop_key_range_s'] = key_range_s
params['crop_key_range_v'] = key_range_v
params['crop_erosion_size'] = erosion_size
params['crop_dilation_size'] = dilation_size
params['crop_min_line_length_factor'] = min_line_length_factor
params['crop_max_line_gap_factor'] = max_line_gap_factor
params['crop_max_inclination_deg'] = max_inclination_deg
params['crop_line_exclusion_size_factor'] = line_exclusion_size_factor
params['crop_num_clusters'] = num_clusters
params['crop_cluster_merge_threshold_size_factor'] = cluster_merge_threshold_size_factor
params['crop_inset_interval'] = inset_interval
params['crop_inset_white_threshold'] = inset_white_threshold
params['crop_extra_inset'] = extra_inset
write_params(filepath, params)
num_saved += 1
print('Wrote crop params for %d images.' % num_saved)
save_prompted = False
else:
save_prompted = True
else:
save_prompted = False
if key == ord(','):
mode_index = (mode_index - 1) if mode_index > 0 else len(modes) - 1
elif key == ord('.'):
mode_index = (mode_index + 1) % len(modes)
elif is_key(key, 'C'):
incr = 0.01 if key == ord('c') else -0.01
corner_size_factor += incr
elif is_key(key, 'H'):
incr = 0.1 if key == ord('h') else -0.1
key_range_h += incr
elif is_key(key, 'S'):
incr = 0.1 if key == ord('s') else -0.1
key_range_s += incr
elif is_key(key, 'V'):
incr = 0.1 if key == ord('v') else -0.1
key_range_v += incr
elif is_key(key, 'E'):
incr = 1 if key == ord('e') else -1
erosion_size += incr
elif is_key(key, 'D'):
incr = 1 if key == ord('d') else -1
dilation_size += incr
elif is_key(key, 'L'):
incr = (1.0 if key == ord('l') else -1.0) * 0.001
min_line_length_factor += incr
elif is_key(key, 'G'):
incr = (1.0 if key == ord('g') else -1.0) * 0.0001
max_line_gap_factor += incr
elif is_key(key, 'I'):
incr = (1.0 if key == ord('i') else -1.0) * 1.0
max_inclination_deg += incr
elif is_key(key, 'X'):
incr = (1.0 if key == ord('x') else -1.0) * 0.1
line_exclusion_size_factor += incr
elif is_key(key, 'N'):
incr = (1 if key == ord('n') else -1)
num_clusters += incr
elif is_key(key, 'M'):
incr = (1.0 if key == ord('m') else -1.0) * 0.025
cluster_merge_threshold_size_factor += incr
elif is_key(key, 'T'):
incr = (1.0 if key == ord('t') else -1.0) * 0.1
inset_interval += incr
elif is_key(key, 'W'):
incr = (1.0 if key == ord('w') else -1.0) * 0.001
inset_white_threshold += incr
elif is_key(key, 'Z'):
incr = (1.0 if key == ord('z') else -1.0)
extra_inset += incr
cv2.destroyAllWindows()
def run(cls, args):
print('Collection: %s' % os.path.basename(args.collection))
print(' Subdir: %s' % (args.subdir or '<ROOT>'))
print('')
output_dir = os.path.normpath(
os.path.join(args.collection, args.subdir))
start_num = 1
num_prefix = args.subdir[
0] if args.subdir and args.subdir != 'images' else ''
pattern = os.path.join(
output_dir, '%s_%s' %
(os.path.basename(args.collection), num_prefix)) + '%04d.CR2'
print("Writing to: %s" % output_dir)
_, filepaths = collect_dirs_and_files(output_dir)
existing_cr2_files = sort_files_by_ext(filepaths).get('.cr2')
if existing_cr2_files:
print('%d existing images:' % len(existing_cr2_files))
seq = FileSequence.load(existing_cr2_files)
for range in seq.ranges:
print(' - ranging from %d to %d' % range)
start_num = range[1] + 1
pattern = seq.pattern
else:
print('No existing images.')
print('')
prefix = os.path.basename(pattern[:pattern.rfind(r'%')])
print('Capture will start from:')
print(' - %s' % (pattern % start_num))
print('')
print('Pre-capture checklist:')
print('')
print(' 1. Arrange lights.')
print(' 2. Disable OIS in lens.')
print(' 3. Ensure that lens zoom is not extreme.')
print(' 4. Ensure that camera height exceeds minimum macro distance.')
print(' 5. Set shooting mode to full manual.')
print(' 6. Find appropriate exposure around f/5.6.')
print(' 7. Take full-frame photo of 18% gray card.')
print(' 8. Set that photo as source for custom white balance.')
print(' 9. Set white balance mode to Custom.')
print(' 10. Ensure that color-keyable background fills frame.')
print('')
if not args.force:
print('Proceed?')
choice = input('> ')
if choice.lower() not in ('y', 'yes'):
print("Abort.")
return
wait_for_device()
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
print("Created: %s" % output_dir)
close_eos_windows()
update_eos_config(output_dir, prefix, start_num)
activate_liveview()
print(
"escape: exit | up/down/left/right: capture | backspace: delete last"
)
print("Waiting for input...")
image_num = start_num
delete_prompted = False
for command in interactive_process(__shoot_keys__):
if delete_prompted:
if command == 'delete':
raw_filepath = pattern % (image_num - 1)
os.remove(raw_filepath)
print('Deleted %s' % raw_filepath)
xmp_filepath = raw_filepath + '.xmp'
if os.path.isfile(xmp_filepath):
os.remove(xmp_filepath)
print('Deleted %s' % xmp_filepath)
image_num -= 1
close_eos_windows()
update_eos_config(output_dir, prefix, image_num)
activate_liveview()
else:
print('Cancelled delete.')
delete_prompted = False
elif command == 'delete':
raw_filepath = pattern % (image_num - 1)
if os.path.isfile(raw_filepath):
print('Press backspace again to delete %s...' %
os.path.basename(raw_filepath))
delete_prompted = True
else:
print('No such file: %s' % raw_filepath)
elif command.startswith('capture'):
raw_filepath = pattern % image_num
top_edge = command.replace('capture_', '')
write_param(raw_filepath, 'top_edge', top_edge)
print('%s --> %s' % (raw_filepath, top_edge))
capture_liveview_photo()
image_num += 1
print('Finished.')
close_eos_windows()
print('Turn camera power off to conserve battery.')
