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Diffstat (limited to 'megapixels/commands/cv/face_pose.py')
| -rw-r--r-- | megapixels/commands/cv/face_pose.py | 164 |
1 files changed, 0 insertions, 164 deletions
diff --git a/megapixels/commands/cv/face_pose.py b/megapixels/commands/cv/face_pose.py deleted file mode 100644 index cb7ec56c..00000000 --- a/megapixels/commands/cv/face_pose.py +++ /dev/null @@ -1,164 +0,0 @@ -""" -NB: This only works with the DLIB 68-point landmarks. - -Converts ROIs to pose: yaw, roll, pitch -pitch: looking down or up in yes gesture -roll: tilting head towards shoulder -yaw: twisting head left to right in no gesture - -""" - -""" -TODO -- check compatibility with MTCNN 68 point detector -- improve accuracy by using MTCNN 5-point -- refer to https://github.com/jerryhouuu/Face-Yaw-Roll-Pitch-from-Pose-Estimation-using-OpenCV/ -""" - -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', default=None, - help='Override enum input filename CSV') -@click.option('-o', '--output', 'opt_fp_out', default=None, - help='Override enum output filename CSV') -@click.option('-m', '--media', 'opt_dir_media', default=None, - help='Override enum media directory') -@click.option('--store', 'opt_data_store', - type=cfg.DataStoreVar, - default=click_utils.get_default(types.DataStore.HDD), - show_default=True, - help=click_utils.show_help(types.Dataset)) -@click.option('--dataset', 'opt_dataset', - type=cfg.DatasetVar, - required=True, - show_default=True, - help=click_utils.show_help(types.Dataset)) -@click.option('--size', 'opt_size', - type=(int, int), default=(300, 300), - help='Output image size') -@click.option('--slice', 'opt_slice', type=(int, int), default=(None, None), - help='Slice list of files') -@click.option('-f', '--force', 'opt_force', is_flag=True, - help='Force overwrite file') -@click.option('-d', '--display', 'opt_display', is_flag=True, - help='Display image for debugging') -@click.pass_context -def cli(ctx, opt_fp_in, opt_fp_out, opt_dir_media, opt_data_store, opt_dataset, opt_size, - opt_slice, opt_force, opt_display): - """Converts ROIs to pose: roll, yaw, pitch""" - - 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.models.bbox import BBox - from app.utils import logger_utils, file_utils, im_utils, display_utils, draw_utils - from app.processors.face_landmarks import Dlib2D_68 - from app.processors.face_pose import FacePoseDLIB - from app.models.data_store import DataStore - - # ------------------------------------------------- - # init here - - log = logger_utils.Logger.getLogger() - - # set data_store - data_store = DataStore(opt_data_store, opt_dataset) - - # get filepath out - fp_out = data_store.metadata(types.Metadata.FACE_POSE) if opt_fp_out is None else opt_fp_out - if not opt_force and Path(fp_out).exists(): - log.error('File exists. Use "-f / --force" to overwite') - return - - # init face processors - face_pose = FacePoseDLIB() - face_landmarks = Dlib2D_68() - - # ------------------------------------------------- - # load data - - fp_record = data_store.metadata(types.Metadata.FILE_RECORD) - df_record = pd.read_csv(fp_record, dtype=cfg.FILE_RECORD_DTYPES).set_index('index') - # load ROI data - fp_roi = data_store.metadata(types.Metadata.FACE_ROI) - df_roi = pd.read_csv(fp_roi).set_index('index') - # slice if you want - if opt_slice: - df_roi = df_roi[opt_slice[0]:opt_slice[1]] - # group by image index (speedup if multiple faces per image) - df_img_groups = df_roi.groupby('record_index') - log.debug('processing {:,} groups'.format(len(df_img_groups))) - - # store poses and convert to DataFrame - results = [] - - # ------------------------------------------------- - # iterate groups with file/record index as key - for record_index, df_img_group in tqdm(df_img_groups): - - # access the file_record - file_record = df_record.iloc[record_index] # pands.DataSeries - - # load image - fp_im = data_store.face(file_record.subdir, file_record.fn, file_record.ext) - im = cv.imread(fp_im) - im_resized = im_utils.resize(im, width=opt_size[0], height=opt_size[1]) - - # iterate image group dataframe with roi index as key - for roi_index, df_img in df_img_group.iterrows(): - - # get bbox - x, y, w, h = df_img.x, df_img.y, df_img.w, df_img.h - #dim = (file_record.width, file_record.height) - dim = im_resized.shape[:2][::-1] - bbox_norm = BBox.from_xywh(x, y, w, h) - bbox_dim = bbox_norm.to_dim(dim) - - # get pose - landmarks = face_landmarks.landmarks(im_resized, bbox_norm) - pose_data = face_pose.pose(landmarks, dim) - #pose_degrees = pose_data['degrees'] # only keep the degrees data - #pose_degrees['points_nose'] = pose_data - - # draw landmarks if optioned - if opt_display: - draw_utils.draw_pose(im_resized, pose_data['point_nose'], pose_data['points']) - draw_utils.draw_degrees(im_resized, pose_data) - cv.imshow('', im_resized) - display_utils.handle_keyboard() - - # add image index and append to result CSV data - pose_data['roi_index'] = roi_index - for k, v in pose_data['points'].items(): - pose_data[f'point_{k}_x'] = v[0] / dim[0] - pose_data[f'point_{k}_y'] = v[1] / dim[1] - - # rearrange data structure for DataFrame - pose_data.pop('points') - pose_data['point_nose_x'] = pose_data['point_nose'][0] / dim[0] - pose_data['point_nose_y'] = pose_data['point_nose'][1] / dim[1] - pose_data.pop('point_nose') - results.append(pose_data) - - # create DataFrame and save to CSV - file_utils.mkdirs(fp_out) - df = pd.DataFrame.from_dict(results) - df.index.name = 'index' - df.to_csv(fp_out) - - # save script - file_utils.write_text(' '.join(sys.argv), '{}.sh'.format(fp_out))
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