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(
