def test_define_float(self):
Config.clear()
Config.define_float("a", 5, "A test for float")
Config.define_float("b", 5., "A test for float with a float var")
Config.define_float("c", 5.6, "A test for float with a float var")
Config.define_float("d", "5.6", "A test for float with a str var")
with self.assertRaises(ValueError):
Config.define_float("e", "bob",
"A test for float with a unparsable str")
self.assertDictEqual(Config.get_dict(), {
'a': 5.0,
'b': 5.0,
'c': 5.6,
'd': 5.6
})
import cv2
import logging
import os
import coloredlogs
from distribute_config import Config
coloredlogs.install(level="DEBUG")
Config.define_str("file", "", "input file: video to read and split")
Config.define_float("extract_every", 100,
"Time in ms between two extracted images")
Config.define_str("prefix", "", "Prefix to the name of the images")
Config.define_str("outputdir", ".", "Where to save the pictures")
def main():
Config.load_conf("config_video_burst.yml")
config = Config.get_dict()
# check if the script can run
assert os.path.isfile(config["file"]), f"Option 'file' need to be provided"
os.makedirs(config["outputdir"], exist_ok=True)
if (config["prefix"] is ""):
config["prefix"] = get_prefix(config["file"])
logging.info(f'prefix: {config["prefix"]}')
frame_id = 0
last_save = -10000
video = cv2.VideoCapture(config["file"])
if not video.isOpened():
Config.define_str(
"model_path", "/opt/model/frozen_inference_graph.pb",
"Path of the model to load and execute, for instance"
"/opt/model/frozen_inference_graph.pb. If you're using docker-compose you shouldn't change this."
)
Config.define_str("input_dir", "",
"Path where the images to annotate are stored")
Config.define_str(
"output_dir", "",
"Path to store pre-annotations (model annotations to help human annotators)"
)
with Config.namespace("class"):
Config.define_str_list("names", [], "name of the classes to annotate")
with Config.namespace("object_detection"):
Config.define_float("threshold", 0.2,
"Discard boxes with score below this value")
Config.define_float(
"max_width", 1.0,
"Discard boxes with width upper this value because in some cases, very large detections are mostly false positives"
)
def main():
Config.load_conf()
config = Config.get_dict()
assert config["model_path"] != "", "model_path can't be empty"
assert config["input_dir"] != "", "input_dir can't be empty"
assert config["output_dir"] != "", "output_dir can't be empty"
os.makedirs(config["output_dir"], exist_ok=True)
images_list = os.listdir(config["input_dir"])