# Remote URLs
REMOTE_IMAGE_URL_FILE = "https://requestor-proxy.figure-eight.com/figure_eight_datasets/open-images/train-images" \
"-boxable.csv "
REMOTE_GROUND_TRUTH_FILE = "https://requestor-proxy.figure-eight.com/figure_eight_datasets/open-images/train" \
"-annotations-bbox.csv "
if __name__ == "__main__":
# Load the project settings and required modules.
Logger.log_special("Running Sample Creator", with_gap=True)
settings = ProjectSettings("settings.yaml")
loader: Loader = Loader()
# Read in the source data, and create our own sample data.
Logger.log_special("Begin Sample Initialization", with_gap=True)
loader.check_and_load(settings.IMAGE_URL_FILE, REMOTE_IMAGE_URL_FILE)
samples = loader.create_samples(settings.IMAGE_URL_FILE)
# Now that we have sample IDs and URLs, we can associate them with the GT annotations.
Logger.log_special("Begin Sample Association", with_gap=True)
loader.check_and_load(settings.IMAGE_URL_FILE, REMOTE_GROUND_TRUTH_FILE)
loader.associate_boxes_with_samples(samples, settings.GROUND_TRUTH_FILE)
# Exporting the created samples.
Logger.log_special("Begin Sample Export", with_gap=True)
pather.create(settings.SAMPLES_DIRECTORY)
loader.export_samples(samples, path=settings.SAMPLES_DIRECTORY, size=5000)
# All done.
Logger.log_header("Sample Creation Completed", with_gap=True)
from modules.data.slide import Slide
from modules.scanner import Scanner
from tools.util import pather
from tools.util.logger import Logger
__author__ = "Jakrin Juangbhanich"
__email__ = "*****@*****.**"
__version__ = "0.0.0"
parser = argparse.ArgumentParser(description='<Script Info>')
parser.add_argument('-i', '--input', default='test', type=str, help="<help>")
parser.add_argument('-o', '--output', default='batch1', type=str, help="<help>")
parser.add_argument('-f', '--flag', action="store_true", help="<help>")
args = parser.parse_args()
if __name__ == "__main__":
input_path = os.path.join("input", args.input)
output_path = os.path.join("output", args.output)
pather.create(output_path, clear=True)
Logger.log_header("Running Scanner", with_gap=True)
Logger.log_field("Version", __version__)
Logger.log_field("Input Path", input_path)
Logger.log_field("Input Path", output_path)
scanner = Scanner(output_path=output_path)
slides: List[Slide] = loader.load_testing_slides(input_path)
scanner.process(slides)
"""
from __future__ import print_function
from __future__ import division
from __future__ import absolute_import
import argparse
import os
from modules.ai.single_cell_classifier.scc_trainer import SCCTrainer
from tools.util.logger import Logger
__author__ = "Jakrin Juangbhanich"
__email__ = "*****@*****.**"
__version__ = "0.0.1"
parser = argparse.ArgumentParser(description='<Script Info>')
parser.add_argument('-i', '--input', default='data', type=str, help="<help>")
parser.add_argument('-f', '--flag', action="store_true", help="<help>")
args = parser.parse_args()
if __name__ == "__main__":
input_path = os.path.join("input", args.input)
Logger.log_header("Running Cell-Scan Trainer", with_gap=True)
Logger.log_field("Version", __version__)
Logger.log_field("Input Folder", input_path)
scc_trainer = SCCTrainer()
scc_trainer.process(input_path)