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import numpy as np
import argparse
import os, sys
from gui import GuiMain, GuiImage, GuiTag
import cv2
import logging
import magic
import subprocess
import re
import platform
import readline
'''
Fetch input prompt with prefilled text.
Parameters:
prompt: Prompt message.
text: Prefilled input.
'''
def input_with_prefill(prompt, text):
def hook():
readline.insert_text(text)
readline.redisplay()
readline.set_pre_input_hook(hook)
result = input(prompt)
readline.set_pre_input_hook()
return result
'''
Checks if the given string is a valid path.
Parameters:
string: String to be checked.
'''
def dir_path(string):
if os.path.isdir(string):
return string
else:
raise NotADirectoryError(string)
'''
Opens the given file with the platform default handler.
Parameters:
file: Path to the file.
'''
def open_system(file):
if platform.system() == 'Darwin': # macOS
subprocess.call(('open', file))
elif platform.system() == 'Windows': # Windows
os.startfile(file)
else: # linux variants
subprocess.call(('xdg-open', file))
'''
Initializes TMSU in a given directory.
Does nothing, if it is already initialized.
Parameters:
base: Directory to initialize.
'''
def tmsu_init(base):
logger = logging.getLogger(__name__)
if not os.path.exists(os.path.join(base, ".tmsu")):
logger.info("TMSU database does not exist, creating ...")
proc = subprocess.Popen(["tmsu", "init"], cwd=base)
proc.wait()
logger.debug("TMSU returncode: {}".format(proc.returncode))
if proc.returncode != 0:
logger.error("Could not initialize TMSU database.")
return False
return True
'''
Reads the tags for the specified file.
Parameters:
base: Base directory for the database.
file: File to get the tags for.
'''
def tmsu_tags(base, file):
logger = logging.getLogger(__name__)
logger.debug("Getting existing tags for file {}".format(file))
tags = set()
proc = subprocess.Popen(["tmsu", "tags", os.path.relpath(file, base)], cwd=base, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
proc.wait()
logger.debug("TMSU returncode: {}".format(proc.returncode))
if proc.returncode == 0:
ret = proc.stdout.read().decode()
logger.debug("Raw TMSU tags: {}".format(ret))
tags.update(re.split("\s", ret.split(":")[1])[1:-1])
else:
logger.error("Could not get tags for file {}".format(file))
return tags
'''
Sets tags for the specified file.
Parameters:
base: Base directory for the database.
file: File to set the tags for.
tags: Tags to set.
untag: If True, it will remove all existing tags first. If False, it will just append new tags.
'''
def tmsu_tag(base, file, tags, untag=True):
logger = logging.getLogger(__name__)
if untag:
logger.debug("Untagging file")
proc = subprocess.Popen(["tmsu", "untag", "--all", os.path.relpath(file, base)], cwd=base, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
proc.wait()
if proc.returncode != 0:
logger.error("Could not untag file {}".format(file))
if tags:
logger.debug("Writing tags {}".format(tags))
proc = subprocess.Popen(["tmsu", "tag", os.path.relpath(file, base)] + list(tags), cwd=base, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
proc.wait()
if proc.returncode != 0:
logger.error("Could not write tags to file {}".format(file))
else:
logger.info("Tags are empty, ignoring")
'''
Walk over all files for the given base directory and all subdirectories recursively.
Parameters:
args: Argument dict.
'''
def walk(args):
logger = logging.getLogger(__name__)
logger.info("Walking files ...")
mime = magic.Magic(mime=True)
files = [os.path.abspath(os.path.join(dp, f)) for dp, dn, filenames in os.walk(args["file_dir"]) for f in filenames]
logger.debug("Files: {}".format(files))
logger.info("Number of files found: {}".format(len(files)))
if args["index"] >= len(files):
logger.error("Invalid start index. index = {}, number of files = {}".format(args["index"], len(files)))
return
if args["predict_images"]:
from tensorflow.keras.applications.resnet50 import ResNet50, preprocess_input, decode_predictions
from tensorflow.keras.preprocessing import image
from tensorflow.keras.models import Model
model = ResNet50(weights="imagenet")
for i in range(args["index"], len(files)):
file_path = files[i]
logger.info("Handling file {}, {}".format(i, file_path))
tags = tmsu_tags(args["base"], file_path)
not_empty = bool(tags)
logger.info("Existing tags: {}".format(tags))
if args["open_system"]:
open_system(file_path)
# Detect MIME-type for file
mime_type = mime.from_file(file_path)
# Handle images
if mime_type.split("/")[0] == "image":
logger.debug("File is image")
img = cv2.imread(file_path)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img = cv2.resize(img, dsize=(800, 800), interpolation=cv2.INTER_CUBIC)
if args["predict_images"]:
logger.info("Predicting image tags ...")
array_pre = cv2.resize(img, dsize=(224, 224), interpolation=cv2.INTER_CUBIC)
for _ in range(4):
array = np.expand_dims(array_pre, axis=0)
array = preprocess_input(array)
predictions = model.predict(array)
classes = decode_predictions(predictions, top=args["predict_images_top"])
logger.debug("Predicted image classes: {}".format(classes[0]))
tags.update([name for _, name, _ in classes[0]])
array_pre = cv2.rotate(array_pre, cv2.ROTATE_90_CLOCKWISE)
logger.info("Predicted tags: {}".format(tags))
if args["gui_tag"]:
while(True): # For GUI inputs (rotate, ...)
logger.debug("Showing image GUI ...")
ret = GuiImage(i, file_path, img, tags).loop()
tags = set(ret[1]).difference({''})
if ret[0] == GuiImage.RETURN_ROTATE_90_CLOCKWISE:
img = cv2.rotate(img, cv2.ROTATE_90_CLOCKWISE)
elif ret[0] == GuiImage.RETURN_ROTATE_90_COUNTERCLOCKWISE:
img = cv2.rotate(img, cv2.ROTATE_90_COUNTERCLOCKWISE)
elif ret[0] == GuiImage.RETURN_NEXT:
break
elif ret[0] == GuiImage.RETURN_ABORT:
return
else:
if args["gui_tag"]:
while(True):
logger.debug("Showing generic tagging GUI ...")
ret = GuiTag(i, file_path, tags).loop()
tags = set(ret[1]).difference({''})
if ret[0] == GuiTag.RETURN_NEXT:
break
elif ret[0] == GuiTag.RETURN_ABORT:
return
if not args["gui_tag"]:
tags = set(input_with_prefill("\nTags for file {}:\n".format(file_path), ','.join(tags)).split(","))
logger.info("Tagging {}".format(tags))
tmsu_tag(args["base"], file_path, tags, untag=not_empty)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Tag multiple files using TMSU.')
parser.add_argument('-b', '--base', nargs='?', default='.', type=dir_path, help='Base directory with database (default: %(default)s)')
parser.add_argument('-f', '--file-dir', nargs='?', default='.', type=dir_path, help='File directory for walking (default: %(default)s)')
parser.add_argument('-g', '--gui', nargs='?', const=1, default=False, type=bool, help='Show main GUI (default: %(default)s)')
parser.add_argument('--predict-images', nargs='?', const=1, default=False, type=bool, help='Use prediction for image tagging (default: %(default)s)')
parser.add_argument('--predict-images-top', nargs='?', const=1, default=10, type=int, help='Defines how many top prediction keywords should be used (default: %(default)s)')
parser.add_argument('--gui-tag', nargs='?', const=1, default=False, type=bool, help='Show GUI for tagging (default: %(default)s)')
parser.add_argument('--open-system', nargs='?', const=1, default=False, type=bool, help='Open all files with system default (default: %(default)s)')
parser.add_argument('-i', '--index', nargs='?', const=1, default=0, type=int, help='Start tagging at the given file index (default: %(default)s)')
parser.add_argument('-v', '--verbose', action="count", default=0, help="Verbosity level")
args = parser.parse_args()
if args.verbose == 0:
log_level = logging.WARNING
elif args.verbose == 1:
log_level = logging.INFO
elif args.verbose >= 2:
log_level = logging.DEBUG
logging.basicConfig(stream=sys.stdout, level=log_level)
logger = logging.getLogger(__name__)
args = {
"base": args.base,
"file_dir": args.file_dir,
"gui": args.gui,
"predict_images": args.predict_images,
"predict_images_top": args.predict_images_top,
"gui_tag": args.gui_tag,
"open_system": args.open_system,
"index": args.index,
"verbosity": args.verbose
}
logger.debug("args = {}".format(args))
if args["gui"]:
logger.debug("Starting main GUI ...")
args = GuiMain(args).loop()
if tmsu_init(args["base"]):
walk(args)
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