def fetch(self):
for data in self.slack_client.rtm_read():
if data.get('type') == 'message':
if self.botid == data.get('user'):
# Do not reply on answers by the Bot
continue
if not self._is_direct(data.get('text')):
# Skip the message if bot is not mentioned
continue
request_data = {
'id': str(uuid4()),
'message': data.get('text')
}
logger.log_it(json.dumps(request_data))
response_data = self._on_direct_message(request_data)
logger.log_it(response_data)
if response_data is not None:
message = response_data['response'].encode('ascii',
'ignore')
message = "{}".format(message)
self.slack_client.api_call('chat.postMessage',
text=message,
as_user="******",
token=self.token,
channel=data.get('channel'))
def start(self):
self.connect()
while True:
try:
self.fetch()
except:
logger.log_it('OOPS', log_type='exception')
self.ping()
time.sleep(.1)
def produce_shifted_tonemap(rawfile, base_ISO, base_Ev, Ev_shift):
# Produce a TIFF-format tonemap of RAWFILE at a given EV_SHIFT relative to
# BASE_ISO. Return the name of the TIFF file so produced.
log_it("INFO: creating, tagging, and testing a file for Ev_shift %d" % Ev_shift, 2)
outfile = os.path.splitext(rawfile)[0] + ("+" if Ev_shift >= 0 else "") + str(Ev_shift) + ".jpg"
command = 'dcraw -c -v -w -W -b %s %s | cjpeg -quality 100 -dct float > %s' % (2 ** Ev_shift, rawfile, outfile)
subprocess.call(command, shell=True)
# OK, we've produced a file. Let's give it EXIF data, then adjust that data
try:
ISO = int(base_ISO) * (2 ** Ev_shift)
except BaseException as e:
ISO = 100 * (2 ** Ev_shift) # Pick a plausible value for the base
log_it("WARNING: unable to calculate real ISO because %s; using dummy ISO value %d" % (e, ISO), 3)
try:
Ev = int(base_Ev) + Ev_shift
except BaseException as e:
Ev = 8 + Ev_shift # Pick a plausible value for the base
log_it("WARNING: unable to calculate real Ev because %s; using dummy Ev value %d" % (e, Ev), 3)
command = 'exiftool -overwrite_original -tagsfromfile %s %s' % (rawfile, outfile)
subprocess.call(command, shell=True)
command = 'exiftool -overwrite_original -ISO=%d -AutoISO=%d -BaseISO=%d -MeasuredEV=%d, -MeasuredEV2=%d "%s"'
command = command % (ISO, ISO, ISO, Ev, Ev, outfile)
subprocess.call(command, shell=True)
return outfile
def hdr_script_generator(rawfile):
# Create a series of EV-shifted versions of RAWFILE, then produce a script that
# will tonemap them. Returns the filename of the script.
log_it("INFO: creating an HDR tonemapping script for raw file '%s'" % rawfile)
olddir = os.getcwd()
try:
head, tail = os.path.split(rawfile)
if head: # If we're passed in a full path to a file ...
os.chdir(os.path.dirname(rawfile))
rawfile = tail
files_to_merge = [][:]
selected_files, shift_mappings = {}.copy(), {}.copy()
original_ISO = fu.get_value_from_any_tag(fu.find_alt_version(rawfile, fu.jpeg_extensions), ['ISO', 'AutoISO', 'BaseISO'])
original_Ev = fu.get_value_from_any_tag(fu.find_alt_version(rawfile, fu.jpeg_extensions), ['MeasuredEV', 'MeasuredEV2'])
for shift_factor in shifts: # Create individual ISO-shifted files
outfile = produce_shifted_tonemap(rawfile, original_ISO, original_Ev, shift_factor)
shift_mappings[shift_factor] = outfile
# OK, let's trim the list to actually useful images
# First, start at the top and move downwards, seeking the darkest useful image.
current_shift, found_beginning, found_end = max(shifts), False, False
while current_shift >= min(shifts):
h = get_smoothed_image_histogram(shift_mappings[current_shift])
if found_end: # If we've already found the bottom image ...
os.unlink(shift_mappings[current_shift])# ... delete this image, which is past it ...
del(shift_mappings[current_shift]) # ... and track that we don't have it.
elif found_beginning: # Otherwise, check if this is the last image, i.e. 1st one w/o right-edge clipping.
if is_left_edge_clipping(h):
found_end = True
os.unlink(shift_mappings[current_shift])
del(shift_mappings[current_shift])
else:
found_beginning = not is_right_edge_clipping(h)
current_shift -= 1
# Now, start at the bottom, and find the lightest useful image
current_shift, found_beginning, found_end = min(shift_mappings.keys()), False, False
while current_shift <= max(shifts):
h = get_smoothed_image_histogram(shift_mappings[current_shift])
if found_end:
os.unlink(shift_mappings[current_shift])
del(shift_mappings[current_shift])
elif found_beginning:
if is_right_edge_clipping(h):
found_end = True
os.unlink(shift_mappings[current_shift])
del(shift_mappings[current_shift])
else:
found_beginning = not is_left_edge_clipping(h)
current_shift += 1
selected_files = list(shift_mappings.values())
selected_files = massage_file_list(selected_files)
files_to_merge = sorted(selected_files)
# Now move the non-EV-shifted file to the front of the list, because create_script_from_file_list assumes precisely that.
try: # If the unshifted image appears in the file list, use that for the base exposure
files_to_merge.insert(0, files_to_merge.pop(files_to_merge.index(os.path.splitext(rawfile)[0] + "+0.jpg")))
except ValueError: # Otherwise, just sort the list, which does a fairly good job of picking a low value for the front.
files_to_merge.sort()
chs.create_script_from_file_list(files_to_merge, delete_originals=True, suppress_align=True)
return os.path.abspath(os.path.splitext(files_to_merge[0])[0] + '_HDR.SH')
finally:
os.chdir(olddir)
