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#!/usr/bin/env python3
import glob
import os
from typing import Callable, List, NamedTuple, Set
import argparse_utils
import config
import input_utils
parser = config.add_commandline_args(
f"ML Quick Labeler ({__file__})",
"Args related to quick labeling of ML training data",
)
parser.add_argument(
"--ml_quick_label_skip_list_path",
default="./qlabel_skip_list.txt",
metavar="FILENAME",
type=argparse_utils.valid_filename,
help="Path to file in which to store already labeled data",
)
class InputSpec(NamedTuple):
image_file_glob: str
image_file_to_features_file: Callable[[str], str]
label: str
valid_keystrokes: List[str]
prompt: str
keystroke_to_label: Callable[[str], str]
def read_skip_list() -> Set[str]:
ret: Set[str] = set()
quick_skip_file = config.config['ml_quick_label_skip_list_path']
if not os.path.exists(quick_skip_file):
return ret
with open(quick_skip_file, 'r') as f:
lines = f.readlines()
for line in lines:
line = line[:-1]
line.strip()
ret.add(line)
return ret
def write_skip_list(skip_list) -> None:
quick_skip_file = config.config['ml_quick_label_skip_list_path']
with open(quick_skip_file, 'w') as f:
for filename in skip_list:
filename = filename.strip()
if len(filename) > 0:
f.write(f'{filename}\n')
def label(in_spec: InputSpec) -> None:
images = glob.glob(in_spec.image_file_glob)
skip_list = read_skip_list()
for image in images:
if image in skip_list:
continue
features = in_spec.image_file_to_features_file(image)
if features is None or not os.path.exists(features):
continue
# Render features and image.
with open(features, "r") as f:
lines = f.readlines()
skip = False
for line in lines:
line = line[:-1]
if in_spec.label in line:
skip = True
if skip:
skip_list.add(image)
continue
os.system(f'xv {image} &')
keystroke = input_utils.single_keystroke_response(
in_spec.valid_keystrokes,
prompt=in_spec.prompt,
)
os.system('killall xv')
label_value = in_spec.keystroke_to_label(keystroke)
with open(features, "a") as f:
f.write(f"{in_spec.label}: {label_value}\n")
skip_list.add(image)
write_skip_list(skip_list)
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