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-rw-r--r--megapixels/commands/cv/csv_to_faces.py105
1 files changed, 105 insertions, 0 deletions
diff --git a/megapixels/commands/cv/csv_to_faces.py b/megapixels/commands/cv/csv_to_faces.py
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+++ b/megapixels/commands/cv/csv_to_faces.py
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+"""
+Reads in CSV of ROIs and extracts facial regions with padding
+"""
+
+import click
+
+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_fp_in', required=True,
+ help='Input CSV')
+@click.option('-m', '--media', 'opt_dir_media', required=True,
+ help='Input image/video directory')
+@click.option('-o', '--output', 'opt_dir_out', required=True,
+ help='Output directory for extracted ROI images')
+@click.option('--slice', 'opt_slice', type=(int, int), default=(None, None),
+ help='Slice list of files')
+@click.option('--padding', 'opt_padding', default=0.25,
+ help='Facial padding as percentage of face width')
+@click.option('--ext', 'opt_ext_out', default='png', type=click.Choice(['jpg', 'png']),
+ help='Output image type')
+@click.option('--min', 'opt_min', default=(60, 60),
+ help='Minimum original face size')
+@click.pass_context
+def cli(ctx, opt_fp_in, opt_dir_media, opt_dir_out, opt_slice,
+ opt_padding, opt_ext_out, opt_min):
+ """Converts ROIs to images"""
+
+ import os
+ from os.path import join
+ from pathlib import Path
+ from glob import glob
+
+ from tqdm import tqdm
+ import numpy as np
+ from PIL import Image, ImageOps, ImageFilter, ImageDraw
+ import cv2 as cv
+ import pandas as pd
+
+ from app.utils import logger_utils, file_utils, im_utils
+ from app.models.bbox import BBox
+
+ # -------------------------------------------------
+ # process here
+ log = logger_utils.Logger.getLogger()
+
+ df_rois = pd.read_csv(opt_fp_in, dtype={'subdir': str, 'fn': str})
+ if opt_slice:
+ df_rois = df_rois[opt_slice[0]:opt_slice[1]]
+
+ log.info('Processing {:,} rows'.format(len(df_rois)))
+
+ file_utils.mkdirs(opt_dir_out)
+
+ df_rois_grouped = df_rois.groupby(['fn']) # group by fn/filename
+ groups = df_rois_grouped.groups
+ skipped = []
+
+ for group in tqdm(groups):
+ # get image
+ group_rows = df_rois_grouped.get_group(group)
+
+ row = group_rows.iloc[0]
+ fp_im = join(opt_dir_media, str(row['subdir']), '{fn}.{ext}'.format(**row)) # TODO change to ext
+ try:
+ im = Image.open(fp_im).convert('RGB')
+ im.verify()
+ except Exception as e:
+ log.warn('Could not open: {}'.format(fp_im))
+ log.error(e)
+ continue
+
+ for idx, roi in group_rows.iterrows():
+ # get bbox to im dimensions
+ xywh = [roi['x'], roi['y'], roi['w'] , roi['h']]
+ bbox = BBox.from_xywh(*xywh)
+ dim = im.size
+ bbox_dim = bbox.to_dim(dim)
+ # expand
+ opt_padding_px = int(opt_padding * bbox_dim.width)
+ bbox_dim_exp = bbox_dim.expand_dim(opt_padding_px, dim)
+ # crop
+ x1y2 = bbox_dim_exp.pt_tl + bbox_dim_exp.pt_br
+ im_crop = im.crop(box=x1y2)
+
+ # strip exif, create new image and paste data
+ im_crop_data = list(im_crop.getdata())
+ im_crop_no_exif = Image.new(im_crop.mode, im_crop.size)
+ im_crop_no_exif.putdata(im_crop_data)
+
+ # save
+ idx_zpad = file_utils.zpad(idx, zeros=3)
+ subdir = '' if roi['subdir'] == '.' else '{}_'.format(roi['subdir'])
+ subdir = subdir.replace('/', '_')
+ fp_im_out = join(opt_dir_out, '{}{}{}.{}'.format(subdir, roi['fn'], idx_zpad, opt_ext_out))
+ # threshold size and save
+ if im_crop_no_exif.size[0] < opt_min[0] or im_crop_no_exif.size[1] < opt_min[1]:
+ skipped.append(fp_im_out)
+ log.info('Face too small: {}, idx: {}'.format(fp_im, idx))
+ else:
+ im_crop_no_exif.save(fp_im_out)
+
+ log.info('Skipped {:,} images'.format(len(skipped)))