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-rw-r--r--megapixels/commands/cv/_old_files_to_face_rois.py168
1 files changed, 168 insertions, 0 deletions
diff --git a/megapixels/commands/cv/_old_files_to_face_rois.py b/megapixels/commands/cv/_old_files_to_face_rois.py
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+++ b/megapixels/commands/cv/_old_files_to_face_rois.py
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+"""
+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
+
+color_filters = {'color': 1, 'gray': 2, 'all': 3}
+
+@click.command()
+@click.option('-i', '--input', 'opt_fp_files', required=True,
+ help='Input file meta CSV')
+@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('-p', '--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.option('--recursive/--no-recursive', 'opt_recursive', is_flag=True, default=False,
+ help='Use glob recursion (slower)')
+@click.option('-f', '--force', 'opt_force', is_flag=True,
+ help='Force overwrite file')
+@click.option('--color', 'opt_color_filter',
+ type=click.Choice(color_filters.keys()), default='color',
+ help='Filter to keep color or grayscale images (color = keep color')
+@click.pass_context
+def cli(ctx, opt_dirs_in, opt_fp_out, opt_ext, opt_size, opt_detector_type,
+ opt_gpu, opt_conf_thresh, opt_pyramids, opt_slice, opt_display, opt_recursive, opt_force, opt_color_filter):
+ """Converts frames with faces to CSV of ROIs"""
+
+ 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 not opt_force and Path(opt_fp_out).exists():
+ log.error('File exists. Use "-f / --force" to overwite')
+ return
+
+ 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.MTCNN:
+ detector = face_detector.DetectorMTCNN()
+ elif opt_detector_type == types.FaceDetectNet.HAAR:
+ log.error('{} not yet implemented'.format(opt_detector_type.name))
+ return
+
+
+ # -------------------------------------------------
+ # process here
+ color_filter = color_filters[opt_color_filter]
+
+ # get list of files to process
+ fp_ims = []
+ for opt_dir_in in opt_dirs_in:
+ if opt_recursive:
+ fp_glob = join(opt_dir_in, '**/*.{}'.format(opt_ext))
+ fp_ims += glob(fp_glob, recursive=True)
+ else:
+ fp_glob = join(opt_dir_in, '*.{}'.format(opt_ext))
+ fp_ims += glob(fp_glob)
+ log.debug(fp_glob)
+
+
+ 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)
+
+ # filter out color or grayscale iamges
+ if color_filter != color_filters['all']:
+ try:
+ is_gray = im_utils.is_grayscale(im)
+ if is_gray and color_filter != color_filters['gray']:
+ log.debug('Skipping grayscale image: {}'.format(fp_im))
+ continue
+ except Exception as e:
+ log.error('Could not check grayscale: {}'.format(fp_im))
+ continue
+
+ try:
+ bboxes = detector.detect(im, opt_size=opt_size, opt_pyramids=opt_pyramids)
+ except Exception as e:
+ log.error('could not detect: {}'.format(fp_im))
+ log.error('{}'.format(e))
+ fpp_im = Path(fp_im)
+ subdir = str(fpp_im.parent.relative_to(opt_dir_in))
+
+ for bbox in bboxes:
+ # log.debug('is square: {}'.format(bbox.w == bbox.h))
+ nw,nh = int(bbox.w * im.shape[1]), int(bbox.h * im.shape[0])
+ roi = {
+ 'fn': fpp_im.stem,
+ 'ext': fpp_im.suffix.replace('.',''),
+ 'x': bbox.x,
+ 'y': bbox.y,
+ 'w': bbox.w,
+ 'h': bbox.h,
+ 'image_height': im.shape[0],
+ 'image_width': im.shape[1],
+ 'subdir': subdir}
+ bbox_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=min(1200, opt_size[0]))
+ for bbox in bboxes:
+ bbox_dim = bbox.to_dim(im_md.shape[:2][::-1])
+ cv.rectangle(im_md, bbox_dim.pt_tl, bbox_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
+ file_utils.mkdirs(opt_fp_out)
+ df = pd.DataFrame.from_dict(data)
+ df.to_csv(opt_fp_out, index=False) \ No newline at end of file