def get_dst_folder_name(src_data_type, src_data_path):
    ''' Compute a output folder name based on data_type and data_path.
        The final output of this script looks like this:
            DST_FOLDER/folder_name/vidoe.avi
            DST_FOLDER/folder_name/skeletons/XXXXX.txt
    '''

    assert (src_data_type in ["video", "folder", "webcam"])

    if src_data_type == "video":  # /root/data/video.avi --> video
        folder_name = os.path.basename(src_data_path).split(".")[-2]

    elif src_data_type == "folder":  # /root/data/video/ --> video
        folder_name = src_data_path.rstrip("/").split("/")[-1]

    elif src_data_type == "webcam":
        # month-day-hour-minute-seconds, e.g.: 02-26-15-51-12
        folder_name = lib_commons.get_time_string()

    return folder_name
예제 #2
0
import os

sys.path.append("../")

import utils.lib_images_io as lib_images_io
import utils.lib_plot as lib_plot
import utils.lib_commons as lib_commons
from utils.lib_openpose import SkeletonDetector
from utils.lib_tracker import Tracker
from utils.lib_classifier import *
import pickle

SRC_DATA_TYPE = "webcam"
SRC_MODEL_PATH = "../model/trained_classifier.pickle"

DST_FOLDER_NAME = lib_commons.get_time_string()

cfg_all = lib_commons.read_yaml("../config/config.yaml")
cfg = cfg_all["s5_test.py"]

CLASSES = np.array(cfg_all["classes"])
print("CLASSES ARE " + str(CLASSES))
SKELETON_FILENAME_FORMAT = cfg_all["skeleton_filename_format"]

WINDOW_SIZE = int(cfg_all["features"]["window_size"])

SRC_WEBCAM_MAX_FPS = float(cfg["settings"]["source"]["webcam_max_framerate"])

OPENPOSE_MODEL = cfg["settings"]["openpose"]["model"]
OPENPOSE_IMG_SIZE = cfg["settings"]["openpose"]["img_size"]