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from glob import glob
import os
from os.path import join
from pathlib import Path
import click
from app.settings import types
from app.utils import click_utils
from app.settings import app_cfg as cfg
from app.utils import logger_utils
import dlib
import pandas as pd
from PIL import Image, ImageOps, ImageFilter
from app.utils import file_utils, im_utils
log = logger_utils.Logger.getLogger()
@click.command()
@click.option('-i', '--input', 'opt_fp_in', required=True,
help='Input directory')
@click.option('-o', '--output', 'opt_fp_out', required=True,
help='Output directory')
@click.option('--size', 'opt_size', default=(320, 240),
help='Inference size for face detection' )
@click.option('--interval', 'opt_frame_interval', default=20,
help='Number of frames before saving next face')
@click.pass_context
def cli(ctx, opt_fp_in, opt_fp_out, opt_size, opt_frame_interval):
"""Converts videos to frames with faces"""
# -------------------------------------------------
# process
from tqdm import tqdm
import cv2 as cv
from tqdm import tqdm
from app.processors import face_detector
detector = face_detector.DetectorDLIBCNN()
# get file list
fp_videos = glob(join(opt_fp_in, '*.mp4'))
fp_videos += glob(join(opt_fp_in, '*.webm'))
fp_videos += glob(join(opt_fp_in, '*.mkv'))
frame_interval_count = 0
frame_count = 0
file_utils.mkdirs(opt_fp_out)
for fp_video in tqdm(fp_videos):
video = cv.VideoCapture(fp_video)
while video.isOpened():
res, frame = video.read()
if not res:
break
frame_count += 1 # for naming
frame_interval_count += 1 # for interval
bboxes = detector.detect(frame, opt_size=opt_size, opt_pyramids=0)
if len(bboxes) > 0 and frame_interval_count >= opt_frame_interval:
# save frame
fname = file_utils.zpad(frame_count)
fp_frame = join(opt_fp_out, '{}_{}.jpg'.format(Path(fp_video).stem, fname))
cv.imwrite(fp_frame, frame)
frame_interval_count = 0
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