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Diffstat (limited to 'megapixels/datasets/commands/face.py')
| -rw-r--r-- | megapixels/datasets/commands/face.py | 117 |
1 files changed, 0 insertions, 117 deletions
diff --git a/megapixels/datasets/commands/face.py b/megapixels/datasets/commands/face.py deleted file mode 100644 index 6b7b18b7..00000000 --- a/megapixels/datasets/commands/face.py +++ /dev/null @@ -1,117 +0,0 @@ -""" -Crop images to prepare for training -""" - -import click -# from PIL import Image, ImageOps, ImageFilter, ImageDraw - -from app.settings import types -from app.utils import click_utils -from app.settings import app_cfg as cfg - -@click.command() -@click.option('-i', '--input', 'opt_dir_in', required=True, - help='Input directory') -@click.option('-o', '--output', 'opt_fp_out', required=True, - help='Output CSV') -@click.option('-e', '--ext', 'opt_ext', - default='jpg', type=click.Choice(['jpg', 'png']), - help='File glob ext') -@click.option('--size', 'opt_size', - type=(int, int), default=(300, 300), - help='Output image size') -@click.option('-t', '--detector-type', 'opt_detector_type', - type=cfg.FaceDetectNetVar, - default=click_utils.get_default(types.FaceDetectNet.DLIB_CNN), - help=click_utils.show_help(types.FaceDetectNet)) -@click.option('-g', '--gpu', 'opt_gpu', default=0, - help='GPU index') -@click.option('--conf', 'opt_conf_thresh', default=0.85, type=click.FloatRange(0,1), - help='Confidence minimum threshold') -@click.option('--pyramids', 'opt_pyramids', default=0, type=click.IntRange(0,4), - help='Number pyramids to upscale for DLIB detectors') -@click.option('--slice', 'opt_slice', type=(int, int), default=(None, None), - help='Slice list of files') -@click.option('--display/--no-display', 'opt_display', is_flag=True, default=False, - help='Display detections to debug') -@click.pass_context -def cli(ctx, opt_dir_in, opt_fp_out, opt_ext, opt_size, opt_detector_type, - opt_gpu, opt_conf_thresh, opt_pyramids, opt_slice, opt_display): - """Extrace face""" - - import sys - import os - from os.path import join - from pathlib import Path - from glob import glob - from tqdm import tqdm - import numpy as np - import dlib # must keep a local reference for dlib - import cv2 as cv - import pandas as pd - - from app.utils import logger_utils, file_utils, im_utils - from app.processors import face_detector - - # ------------------------------------------------- - # init here - - log = logger_utils.Logger.getLogger() - - if opt_detector_type == types.FaceDetectNet.CVDNN: - detector = face_detector.DetectorCVDNN() - elif opt_detector_type == types.FaceDetectNet.DLIB_CNN: - detector = face_detector.DetectorDLIBCNN(opt_gpu) - elif opt_detector_type == types.FaceDetectNet.DLIB_HOG: - detector = face_detector.DetectorDLIBHOG() - elif opt_detector_type == types.FaceDetectNet.HAAR: - log.error('{} not yet implemented'.format(opt_detector_type.name)) - return - - - # ------------------------------------------------- - # process here - - # get list of files to process - fp_ims = glob(join(opt_dir_in, '*.{}'.format(opt_ext))) - if opt_slice: - fp_ims = fp_ims[opt_slice[0]:opt_slice[1]] - log.debug('processing {:,} files'.format(len(fp_ims))) - - - data = [] - - for fp_im in tqdm(fp_ims): - im = cv.imread(fp_im) - bboxes = detector.detect(im, opt_size=opt_size, opt_pyramids=opt_pyramids) - fpp_im = Path(fp_im) - for bbox in bboxes: - roi = { - 'fn': fpp_im.stem, - 'ext': fpp_im.suffix, - 'x': bbox.x, - 'y': bbox.y, - 'w': bbox.w, - 'h': bbox.h} - dim = bbox.to_dim(im.shape[:2][::-1]) # w,h - data.append(roi) - - # debug display - if opt_display and len(bboxes): - im_md = im_utils.resize(im, width=opt_size[0]) - for bbox in bboxes: - dim = bbox.to_dim(im_md.shape[:2][::-1]) - cv.rectangle(im_md, dim.pt_tl, dim.pt_br, (0,255,0), 3) - cv.imshow('', im_md) - while True: - k = cv.waitKey(1) & 0xFF - if k == 27 or k == ord('q'): # ESC - cv.destroyAllWindows() - sys.exit() - elif k != 255: - # any key to continue - break - - # save date - df = pd.DataFrame.from_dict(data) - df.to_csv(opt_fp_out)
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