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 = 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", file], cwd=base, stdout=subprocess.PIPE, stderr=subprocess.PIPE) proc.wait() logger.debug("TMSU returncode: {}".format(proc.returncode)) if proc.returncode == 0: tags.update(re.split("\s", proc.stdout.read().decode())[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", file], 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", file] + 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["base"]) 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='./test', type=dir_path, help='Base 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, "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)