def main():
f = open('changedIPTCmeta.txt', 'w')
parser = argparse.ArgumentParser()
parser.add_argument("-image_path",
help='path to jpg images',
type=str,
required=True)
image_path = parser.parse_args()
data = pd.read_csv('iptcmeta.csv')
i = 0
for filename in data['fileName']:
info = IPTCInfo(join(image_path.image_path, filename))
oldKeywords = info['keywords']
oldObjName = info['object name']
oldCaption = info['caption/abstract']
newkey = data.at[i, 'keywords'].split(',')
info['object name'] = data.at[i, 'obj_name']
info['caption/abstract'] = data.at[i, 'caption']
info['keywords'] = newkey
f.write('В файле ' + str(filename) +
' значения keywords изменились с ' + str(oldKeywords) +
' на ' + str(newkey) + ' значения object_name изменились с ' +
str(oldObjName) + ' на ' + str(info['object name']) +
' значения caption изменились с ' + str(oldCaption) + ' на ' +
str(info['caption/abstract']) + '\n')
info.save()
print(filename)
i = i + 1
f.close()
def process_image(ifile:str, siteconfig, ofile:str=None):
'''resize an image and return the output file name and the exif and iptc meta data'''
try:
size = siteconfig.get('resize')
site_copyright_notice = siteconfig.get('copyright_notice')
im = Image.open(ifile)
im_xif = im.info.get('exif')
im_iptc = retrieve_copyright_notice(ifile)
dest = ofile if size and ofile else ifile #Target the input file if the output file is not provided
# Image resizing with exif preservation
if size:
im2 = im.resize(size)
params = dict(exif=im_xif) if im_xif else dict()
im2.save(dest, **params)
# IPTC data rewriting. IPTC are lost during the resize operation. We have to put them back manually
# If the inputfile contains a copyright notice, then use it instead of the siteconfig value
im_iptc['copyright notice'] = im_iptc.get('copyright notice', site_copyright_notice)
if im_iptc or site_copyright_notice:
iptc = IPTCInfo(dest)
for key in im_iptc:
iptc[key] = im_iptc[key]
iptc.save()
return (dest, im_xif, im_iptc)
except Exception as e:
printfailure('could not process image ', ifile, ' traceback ', str(e))
return (ifile, None, None)
def mutate(self, info, input):
abs_path = Path(BASE_DIR, input["path"])
if not abs_path.exists():
raise Exception("Image not found")
image = {"path": abs_path}
iptc_info = IPTCInfo(str(abs_path), inp_charset="utf_8")
if iptc_info["keywords"] == input["keywords"]:
return SetKeywordsPayload(image=image)
iptc_info["keywords"] = input["keywords"]
iptc_info.save()
return SetKeywordsPayload(image=image)
def mangle(file: IPTCInfo) -> int:
tracking: str = file['special instructions']
if tracking is not None:
if tracking.startswith(b'FBMD'):
print(
f'Old tracking: {file["special instructions"].decode("utf-8")}'
)
file[
'special instructions'] = f'FBMD{secrets.token_hex(int((len(tracking) - 4) / 2))}'
print(f'New tracking: {file["special instructions"]}')
file.save()
return 1
else:
return 0
else:
return 0
def process_file(filepath, random_replace=False, verbose=False):
img_type = imghdr.what(filepath)
if img_type is None:
if verbose:
print("Skipping).")
return
if verbose:
print(img_type, end='). ')
info = IPTCInfo(filepath, force=True)
special_instructions = info['special instructions']
if special_instructions is None:
if verbose:
print("FBMD not found")
return
fbmd_index = special_instructions.find(b'FBMD')
if fbmd_index < 0:
if verbose:
print("FBMD not found")
return
length_hex = special_instructions[fbmd_index + 6:fbmd_index + 6 + 4]
length = int(length_hex, 16)
info['special instructions'] = update_instructions(special_instructions,
fbmd_index,
length,
random=random_replace)
if verbose:
print(special_instructions[fbmd_index:fbmd_index + 6 + 4 +
(length + 1) * 8])
info.save()
os.remove(filepath + "~")
for key, value in data.items():
print(key)
print(value)
# get image path from resize method
new_key = resize(key)
# set recognition model
response = model.predict_by_filename(new_key)
# removing the resized image after it's being processed.
os.remove(new_key)
# append generated keywords in dictionary
for r in response['outputs'][0]['data']['concepts']:
data[key].append(r['name'])
print(r['name']) # for each element in response print key-words
# take the values from dictionary,
# match key value to a file path and append IPTC keywords to image file
for key, value in data.items():
# print(os.path.basename(key))
info = IPTCInfo(key)
for item in value:
newValue = item
info['keywords'].append(newValue)
info.save()
#--------------------------------------------------------------------#