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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
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)
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