From 1690cfb4cc7b7277afca4016c295927cc4f7fafb Mon Sep 17 00:00:00 2001 From: adamhrv Date: Fri, 14 Dec 2018 17:22:57 +0100 Subject: add pose filter --- megapixels/commands/cv/face_pose_to_csv.py | 105 ------------------------ megapixels/commands/cv/face_vec_to_csv.py | 110 ------------------------- megapixels/commands/cv/rois_to_pose.py | 127 +++++++++++++++++++++++++++++ megapixels/commands/cv/rois_to_vecs.py | 109 +++++++++++++++++++++++++ 4 files changed, 236 insertions(+), 215 deletions(-) delete mode 100644 megapixels/commands/cv/face_pose_to_csv.py delete mode 100644 megapixels/commands/cv/face_vec_to_csv.py create mode 100644 megapixels/commands/cv/rois_to_pose.py create mode 100644 megapixels/commands/cv/rois_to_vecs.py (limited to 'megapixels/commands/cv') diff --git a/megapixels/commands/cv/face_pose_to_csv.py b/megapixels/commands/cv/face_pose_to_csv.py deleted file mode 100644 index ca7489de..00000000 --- a/megapixels/commands/cv/face_pose_to_csv.py +++ /dev/null @@ -1,105 +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 - -color_filters = {'color': 1, 'gray': 2, 'all': 3} - -@click.command() -@click.option('-f', '--files', 'opt_fp_files', required=True, - help='Input ROI CSV') -@click.option('-r', '--rois', 'opt_fp_rois', required=True, - help='Input ROI CSV') -@click.option('-m', '--media', 'opt_dir_media', required=True, - help='Input media directory') -@click.option('-o', '--output', 'opt_fp_out', required=True, - help='Output CSV') -@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.pass_context -def cli(ctx, opt_fp_files, opt_fp_rois, opt_dir_media, opt_fp_out, opt_size, - opt_slice, opt_force): - """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 - from app.processors.face_landmarks import LandmarksDLIB - from app.processors.face_pose import FacePoseDLIB - - # ------------------------------------------------- - # init here - - log = logger_utils.Logger.getLogger() - - # init face processors - face_pose = FacePoseDLIB() - face_landmarks = LandmarksDLIB() - - df_files = pd.read_csv(opt_fp_files) - df_rois = pd.read_csv(opt_fp_rois) - - if not opt_force and Path(opt_fp_out).exists(): - log.error('File exists. Use "-f / --force" to overwite') - return - - if opt_slice: - df_rois = df_rois[opt_slice[0]:opt_slice[1]] - - # ------------------------------------------------- - # process here - - df_roi_groups = df_rois.groupby('index') - log.debug('processing {:,} groups'.format(len(df_roi_groups))) - - - poses = [] - - #for df_roi_group in tqdm(df_roi_groups.itertuples(), total=len(df_roi_groups)): - for df_roi_group_idx, df_roi_group in tqdm(df_roi_groups): - # make fp - image_index = df_roi_group.image_index.values[0] - pds_file = df_files.iloc[image_index] - fp_im = join(opt_dir_media, pds_file.subdir, '{}.{}'.format(pds_file.fn, pds_file.ext)) - im = cv.imread(fp_im) - # get bbox - x = df_roi_group.x.values[0] - y = df_roi_group.y.values[0] - w = df_roi_group.w.values[0] - h = df_roi_group.h.values[0] - dim = im.shape[:2][::-1] - bbox = BBox.from_xywh(x, y, w, h).to_dim(dim) - # get pose - landmarks = face_landmarks.landmarks(im, bbox) - pose = face_pose.pose(landmarks, dim) - pose['image_index'] = image_index - poses.append(pose) - - - # save date - file_utils.mkdirs(opt_fp_out) - df = pd.DataFrame.from_dict(poses) - df.index.name = 'index' - df.to_csv(opt_fp_out) \ No newline at end of file diff --git a/megapixels/commands/cv/face_vec_to_csv.py b/megapixels/commands/cv/face_vec_to_csv.py deleted file mode 100644 index 6c9fad09..00000000 --- a/megapixels/commands/cv/face_vec_to_csv.py +++ /dev/null @@ -1,110 +0,0 @@ -""" -Converts ROIs to face vector -""" - -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_files', required=True, - help='Input ROI CSV') -@click.option('-r', '--rois', 'opt_fp_rois', required=True, - help='Input ROI CSV') -@click.option('-m', '--media', 'opt_dir_media', required=True, - help='Input media directory') -@click.option('-o', '--output', 'opt_fp_out', required=True, - help='Output CSV') -@click.option('--size', 'opt_size', - type=(int, int), default=(300, 300), - help='Output image size') -@click.option('-j', '--jitters', 'opt_jitters', default=cfg.DLIB_FACEREC_JITTERS, - help='Number of jitters') -@click.option('-p', '--padding', 'opt_padding', default=cfg.DLIB_FACEREC_PADDING, - help='Percentage padding') -@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('-g', '--gpu', 'opt_gpu', default=0, - help='GPU index') -@click.pass_context -def cli(ctx, opt_fp_files, opt_fp_rois, opt_dir_media, opt_fp_out, opt_size, - opt_slice, opt_force, opt_gpu, opt_jitters, opt_padding): - """Converts face ROIs to vectors""" - - 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 - from app.processors import face_recognition - - - # ------------------------------------------------- - # init here - - log = logger_utils.Logger.getLogger() - - # init face processors - facerec = face_recognition.RecognitionDLIB() - - # load data - df_file_meta = pd.read_csv(opt_fp_files) - df_rois = pd.read_csv(opt_fp_rois) - - if not opt_force and Path(opt_fp_out).exists(): - log.error('File exists. Use "-f / --force" to overwite') - return - - if opt_slice: - df_rois = df_rois[opt_slice[0]:opt_slice[1]] - - # ------------------------------------------------- - # process here - - df_img_groups = df_rois.groupby('image_index') - log.debug('processing {:,} groups'.format(len(df_img_groups))) - - vecs = [] - - for image_index, df_img_group in tqdm(df_img_groups): - # make fp - roi_index = df_img_group.index.values[0] - file_meta = df_file_meta.iloc[image_index] # locate image meta - fp_im = join(opt_dir_media, file_meta.subdir, '{}.{}'.format(file_meta.fn, file_meta.ext)) - im = cv.imread(fp_im) - # get bbox - x = df_img_group.x.values[0] - y = df_img_group.y.values[0] - w = df_img_group.w.values[0] - h = df_img_group.h.values[0] - imw = df_img_group.image_width.values[0] - imh = df_img_group.image_height.values[0] - dim = im.shape[:2][::-1] - # get face vector - dim = (imw, imh) - bbox_dim = BBox.from_xywh(x, y, w, h).to_dim(dim) # convert to int real dimensions - # compute vec - # padding=opt_padding not yet implemented in 19.16 but merged in master - vec = facerec.vec(im, bbox_dim, jitters=opt_jitters) - vec_str = ','.join([repr(x) for x in vec]) # convert to string for CSV - vecs.append( {'roi_index': roi_index, 'image_index': image_index, 'vec': vec_str}) - - - # save date - file_utils.mkdirs(opt_fp_out) - df = pd.DataFrame.from_dict(vecs) - df.index.name = 'index' - df.to_csv(opt_fp_out) \ No newline at end of file diff --git a/megapixels/commands/cv/rois_to_pose.py b/megapixels/commands/cv/rois_to_pose.py new file mode 100644 index 00000000..3877cecf --- /dev/null +++ b/megapixels/commands/cv/rois_to_pose.py @@ -0,0 +1,127 @@ +""" +Converts ROIs to pose: yaw, roll, pitch +""" + +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_files', required=True, + help='Input ROI CSV') +@click.option('-r', '--rois', 'opt_fp_rois', required=True, + help='Input ROI CSV') +@click.option('-m', '--media', 'opt_dir_media', required=True, + help='Input media directory') +@click.option('-o', '--output', 'opt_fp_out', required=True, + help='Output CSV') +@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_files, opt_fp_rois, opt_dir_media, opt_fp_out, 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 + from app.processors.face_landmarks import LandmarksDLIB + from app.processors.face_pose import FacePoseDLIB + + # ------------------------------------------------- + # init here + + log = logger_utils.Logger.getLogger() + + # init face processors + face_pose = FacePoseDLIB() + face_landmarks = LandmarksDLIB() + + # load datra + df_files = pd.read_csv(opt_fp_files) + df_rois = pd.read_csv(opt_fp_rois) + + if not opt_force and Path(opt_fp_out).exists(): + log.error('File exists. Use "-f / --force" to overwite') + return + + if opt_slice: + df_rois = df_rois[opt_slice[0]:opt_slice[1]] + + # ------------------------------------------------- + # process here + df_img_groups = df_rois.groupby('image_index') + log.debug('processing {:,} groups'.format(len(df_img_groups))) + + + poses = [] + + # iterate + #for df_roi_group_idx, df_roi_group in tqdm(df_roi_groups): + for image_index, df_img_group in tqdm(df_img_groups): + # make fp + #image_index = df_roi_group.image_index.values[0] + pds_file = df_files.iloc[image_index] + fp_im = join(opt_dir_media, pds_file.subdir, '{}.{}'.format(pds_file.fn, pds_file.ext)) + im = cv.imread(fp_im) + # get bbox + x = df_img_group.x.values[0] + y = df_img_group.y.values[0] + w = df_img_group.w.values[0] + h = df_img_group.h.values[0] + dim = im.shape[:2][::-1] + bbox = BBox.from_xywh(x, y, w, h).to_dim(dim) + # get pose + landmarks = face_landmarks.landmarks(im, bbox) + pose_data = face_pose.pose(landmarks, dim, project_points=opt_display) + pose_degrees = pose_data['degrees'] # only keep the degrees data + + # use the project point data if display flag set + if opt_display: + pts_im = pose_data['points_image'] + pts_model = pose_data['points_model'] + pt_nose = pose_data['point_nose'] + dst = im.copy() + face_pose.draw_pose(dst, pts_im, pts_model, pt_nose) + face_pose.draw_degrees(dst, pose_degrees) + # display to cv window + cv.imshow('', dst) + 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 + + # add image index and append to result CSV data + pose_degrees['image_index'] = image_index + poses.append(pose_degrees) + + + # save date + file_utils.mkdirs(opt_fp_out) + df = pd.DataFrame.from_dict(poses) + df.index.name = 'index' + df.to_csv(opt_fp_out) \ No newline at end of file diff --git a/megapixels/commands/cv/rois_to_vecs.py b/megapixels/commands/cv/rois_to_vecs.py new file mode 100644 index 00000000..525f4404 --- /dev/null +++ b/megapixels/commands/cv/rois_to_vecs.py @@ -0,0 +1,109 @@ +""" +Converts ROIs to face vector +""" + +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_files', required=True, + help='Input file meta CSV') +@click.option('-r', '--rois', 'opt_fp_rois', required=True, + help='Input ROI CSV') +@click.option('-m', '--media', 'opt_dir_media', required=True, + help='Input media directory') +@click.option('-o', '--output', 'opt_fp_out', required=True, + help='Output CSV') +@click.option('--size', 'opt_size', + type=(int, int), default=(300, 300), + help='Output image size') +@click.option('-j', '--jitters', 'opt_jitters', default=cfg.DLIB_FACEREC_JITTERS, + help='Number of jitters') +@click.option('-p', '--padding', 'opt_padding', default=cfg.DLIB_FACEREC_PADDING, + help='Percentage padding') +@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('-g', '--gpu', 'opt_gpu', default=0, + help='GPU index') +@click.pass_context +def cli(ctx, opt_fp_files, opt_fp_rois, opt_dir_media, opt_fp_out, opt_size, + opt_slice, opt_force, opt_gpu, opt_jitters, opt_padding): + """Converts face ROIs to vectors""" + + 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 + from app.processors import face_recognition + + + # ------------------------------------------------- + # init here + + log = logger_utils.Logger.getLogger() + + # init face processors + facerec = face_recognition.RecognitionDLIB() + + # load data + df_file_meta = pd.read_csv(opt_fp_files) + df_rois = pd.read_csv(opt_fp_rois) + + if not opt_force and Path(opt_fp_out).exists(): + log.error('File exists. Use "-f / --force" to overwite') + return + + if opt_slice: + df_rois = df_rois[opt_slice[0]:opt_slice[1]] + + # ------------------------------------------------- + # process here + df_img_groups = df_rois.groupby('image_index') + log.debug('processing {:,} groups'.format(len(df_img_groups))) + + vecs = [] + + for image_index, df_img_group in tqdm(df_img_groups): + # make fp + roi_index = df_img_group.index.values[0] + file_meta = df_file_meta.iloc[image_index] # locate image meta + fp_im = join(opt_dir_media, file_meta.subdir, '{}.{}'.format(file_meta.fn, file_meta.ext)) + im = cv.imread(fp_im) + # get bbox + x = df_img_group.x.values[0] + y = df_img_group.y.values[0] + w = df_img_group.w.values[0] + h = df_img_group.h.values[0] + imw = df_img_group.image_width.values[0] + imh = df_img_group.image_height.values[0] + dim = im.shape[:2][::-1] + # get face vector + dim = (imw, imh) + bbox_dim = BBox.from_xywh(x, y, w, h).to_dim(dim) # convert to int real dimensions + # compute vec + # padding=opt_padding not yet implemented in 19.16 but merged in master + vec = facerec.vec(im, bbox_dim, jitters=opt_jitters) + vec_str = ','.join([repr(x) for x in vec]) # convert to string for CSV + vecs.append( {'roi_index': roi_index, 'image_index': image_index, 'vec': vec_str}) + + + # save date + file_utils.mkdirs(opt_fp_out) + df = pd.DataFrame.from_dict(vecs) + df.index.name = 'index' + df.to_csv(opt_fp_out) \ No newline at end of file -- cgit v1.2.3-70-g09d2