aboutsummaryrefslogtreecommitdiff
path: root/file-tagger.py
blob: 6a602eb68d189628ea6732fe136ca4d04a0305b4 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
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

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

def dir_path(string):
    if os.path.isdir(string):
        return string
    else:
        raise NotADirectoryError(string)

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))

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

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

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")

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)

        mime_type = mime.from_file(file_path)

        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)