from stagesepx import toolbox import numpy as np from test_cutter import test_default as cutter_default from test_cutter import RESULT_DIR as CUTTER_RESULT_DIR import os PROJECT_PATH = os.path.dirname(os.path.dirname(__file__)) VIDEO_PATH = os.path.join(PROJECT_PATH, "demo.mp4") MODEL_PATH = os.path.join(PROJECT_PATH, "model.pkl") IMAGE_NAME = "demo.jpg" IMAGE_PATH = os.path.join(PROJECT_PATH, IMAGE_NAME) # cut, and get result dir cutter_res: VideoCutResult = cutter_default() def _draw_report(res): r = Reporter() report_path = os.path.join(CUTTER_RESULT_DIR, "report.html") r.draw(res, report_path=report_path) assert os.path.isfile(report_path) def test_default(): # --- classify --- cl = SVMClassifier() cl.load(CUTTER_RESULT_DIR) cl.train() cl.save_model(MODEL_PATH, overwrite=True)
from loguru import logger import subprocess import os PROJECT_PATH = os.path.dirname(os.path.dirname(__file__)) VIDEO_PATH = os.path.join(PROJECT_PATH, "demo.mp4") from test_cutter import test_default as cutter_default from test_cutter import RESULT_DIR as CUTTER_RESULT_DIR # prepare cutter_default() def test_cli(): logger.info("checking main") subprocess.check_call(["python3", "-m", "stagesepx.cli"]) def test_analyse(): output = "output.html" subprocess.check_call(["stagesepx", "analyse", VIDEO_PATH, output]) os.remove(output) def test_train(): mod = "output.h5" subprocess.check_call( ["stagesepx", "train", CUTTER_RESULT_DIR, mod, "--epochs", "1"]) # predict subprocess.check_call(