import numpy as np import argparse import os, sys from gui import GuiMain, GuiImage, GuiTag import cv2 import logging import magic from tmsu import * from util import * ''' 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"]) and (not args["skip_prompt"])): 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('-s', '--skip-prompt', nargs='?', const=1, default=False, type=bool, help='Skip prompt for file tags (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, "skip_prompt": args.skip_prompt, "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)