camera-trap-anomaly-detection/quick_label.py

import cv2
import argparse
import os

from py.Dataset import Dataset
from py.FileUtils import list_jpegs_recursive

def main():
    parser = argparse.ArgumentParser(description="BOW train script")
    parser.add_argument("dataset_dir", type=str, help="Directory of the dataset containing all session folders")
    parser.add_argument("session_name", type=str, help="Name of the session to use for Lapse images (e.g. marten_01)")
    parser.add_argument("--skip", type=int, help="Skip first n images", default=0)

    args = parser.parse_args()

    ds = Dataset(args.dataset_dir)
    session = ds.create_session(args.session_name)
    
    skip = args.skip
    if skip > 0:
        print(f"Skipping the first {skip} images...")
    normal = []
    anomalous = []
    motion_folder = session.get_motion_folder()
    quit = False
    print(list_jpegs_recursive(motion_folder), motion_folder)
    for img_file in sorted(list_jpegs_recursive(motion_folder)):
        if skip > 0:
            skip -= 1
            print(skip)
            continue
        img_nr = int(img_file[-9:-4])

        print(f"Labeling img #{img_nr}... ", end="")
        image = cv2.imread(os.path.join(motion_folder, img_file))
        cv2.imshow("labeler", image)
        while True:
            key = cv2.waitKey(0)
            if key == ord("1"):
                print("normal")
                normal.append(img_nr)
            elif key == ord("2"):
                print("anomalous")
                anomalous.append(img_nr)
            elif key == ord("x"):
                quit = True
            else:
                continue
            print(f"normal = {normal}")
            print(f"anomalous = {anomalous}")
            break
        if quit:
            break
    cv2.destroyAllWindows()
    print("Done.")
    print(f"normal = {normal}")
    print(f"anomalous = {anomalous}")

if __name__ == "__main__":
    main()