forked from PulseFocusPlatform/PulseFocusPlatform
181 lines
6.8 KiB
Python
181 lines
6.8 KiB
Python
|
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
|
||
|
#
|
||
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
||
|
# you may not use this file except in compliance with the License.
|
||
|
# You may obtain a copy of the License at
|
||
|
#
|
||
|
# http://www.apache.org/licenses/LICENSE-2.0
|
||
|
#
|
||
|
# Unless required by applicable law or agreed to in writing, software
|
||
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
||
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||
|
# See the License for the specific language governing permissions and
|
||
|
# limitations under the License.
|
||
|
|
||
|
import os
|
||
|
import numpy as np
|
||
|
|
||
|
from ppdet.core.workspace import register, serializable
|
||
|
from .dataset import DetDataset
|
||
|
|
||
|
from ppdet.utils.logger import setup_logger
|
||
|
logger = setup_logger(__name__)
|
||
|
|
||
|
|
||
|
@register
|
||
|
@serializable
|
||
|
class WIDERFaceDataSet(DetDataset):
|
||
|
"""
|
||
|
Load WiderFace records with 'anno_path'
|
||
|
|
||
|
Args:
|
||
|
dataset_dir (str): root directory for dataset.
|
||
|
image_dir (str): directory for images.
|
||
|
anno_path (str): WiderFace annotation data.
|
||
|
data_fields (list): key name of data dictionary, at least have 'image'.
|
||
|
sample_num (int): number of samples to load, -1 means all.
|
||
|
with_lmk (bool): whether to load face landmark keypoint labels.
|
||
|
"""
|
||
|
|
||
|
def __init__(self,
|
||
|
dataset_dir=None,
|
||
|
image_dir=None,
|
||
|
anno_path=None,
|
||
|
data_fields=['image'],
|
||
|
sample_num=-1,
|
||
|
with_lmk=False):
|
||
|
super(WIDERFaceDataSet, self).__init__(
|
||
|
dataset_dir=dataset_dir,
|
||
|
image_dir=image_dir,
|
||
|
anno_path=anno_path,
|
||
|
data_fields=data_fields,
|
||
|
sample_num=sample_num,
|
||
|
with_lmk=with_lmk)
|
||
|
self.anno_path = anno_path
|
||
|
self.sample_num = sample_num
|
||
|
self.roidbs = None
|
||
|
self.cname2cid = None
|
||
|
self.with_lmk = with_lmk
|
||
|
|
||
|
def parse_dataset(self):
|
||
|
anno_path = os.path.join(self.dataset_dir, self.anno_path)
|
||
|
image_dir = os.path.join(self.dataset_dir, self.image_dir)
|
||
|
|
||
|
txt_file = anno_path
|
||
|
|
||
|
records = []
|
||
|
ct = 0
|
||
|
file_lists = self._load_file_list(txt_file)
|
||
|
cname2cid = widerface_label()
|
||
|
|
||
|
for item in file_lists:
|
||
|
im_fname = item[0]
|
||
|
im_id = np.array([ct])
|
||
|
gt_bbox = np.zeros((len(item) - 1, 4), dtype=np.float32)
|
||
|
gt_class = np.zeros((len(item) - 1, 1), dtype=np.int32)
|
||
|
gt_lmk_labels = np.zeros((len(item) - 1, 10), dtype=np.float32)
|
||
|
lmk_ignore_flag = np.zeros((len(item) - 1, 1), dtype=np.int32)
|
||
|
for index_box in range(len(item)):
|
||
|
if index_box < 1:
|
||
|
continue
|
||
|
gt_bbox[index_box - 1] = item[index_box][0]
|
||
|
if self.with_lmk:
|
||
|
gt_lmk_labels[index_box - 1] = item[index_box][1]
|
||
|
lmk_ignore_flag[index_box - 1] = item[index_box][2]
|
||
|
im_fname = os.path.join(image_dir,
|
||
|
im_fname) if image_dir else im_fname
|
||
|
widerface_rec = {
|
||
|
'im_file': im_fname,
|
||
|
'im_id': im_id,
|
||
|
} if 'image' in self.data_fields else {}
|
||
|
gt_rec = {
|
||
|
'gt_bbox': gt_bbox,
|
||
|
'gt_class': gt_class,
|
||
|
}
|
||
|
for k, v in gt_rec.items():
|
||
|
if k in self.data_fields:
|
||
|
widerface_rec[k] = v
|
||
|
if self.with_lmk:
|
||
|
widerface_rec['gt_keypoint'] = gt_lmk_labels
|
||
|
widerface_rec['keypoint_ignore'] = lmk_ignore_flag
|
||
|
|
||
|
if len(item) != 0:
|
||
|
records.append(widerface_rec)
|
||
|
|
||
|
ct += 1
|
||
|
if self.sample_num > 0 and ct >= self.sample_num:
|
||
|
break
|
||
|
assert len(records) > 0, 'not found any widerface in %s' % (anno_path)
|
||
|
logger.debug('{} samples in file {}'.format(ct, anno_path))
|
||
|
self.roidbs, self.cname2cid = records, cname2cid
|
||
|
|
||
|
def _load_file_list(self, input_txt):
|
||
|
with open(input_txt, 'r') as f_dir:
|
||
|
lines_input_txt = f_dir.readlines()
|
||
|
|
||
|
file_dict = {}
|
||
|
num_class = 0
|
||
|
exts = ['jpg', 'jpeg', 'png', 'bmp']
|
||
|
exts += [ext.upper() for ext in exts]
|
||
|
for i in range(len(lines_input_txt)):
|
||
|
line_txt = lines_input_txt[i].strip('\n\t\r')
|
||
|
split_str = line_txt.split(' ')
|
||
|
if len(split_str) == 1:
|
||
|
img_file_name = os.path.split(split_str[0])[1]
|
||
|
split_txt = img_file_name.split('.')
|
||
|
if len(split_txt) < 2:
|
||
|
continue
|
||
|
elif split_txt[-1] in exts:
|
||
|
if i != 0:
|
||
|
num_class += 1
|
||
|
file_dict[num_class] = [line_txt]
|
||
|
else:
|
||
|
if len(line_txt) <= 6:
|
||
|
continue
|
||
|
result_boxs = []
|
||
|
xmin = float(split_str[0])
|
||
|
ymin = float(split_str[1])
|
||
|
w = float(split_str[2])
|
||
|
h = float(split_str[3])
|
||
|
# Filter out wrong labels
|
||
|
if w < 0 or h < 0:
|
||
|
logger.warning('Illegal box with w: {}, h: {} in '
|
||
|
'img: {}, and it will be ignored'.format(
|
||
|
w, h, file_dict[num_class][0]))
|
||
|
continue
|
||
|
xmin = max(0, xmin)
|
||
|
ymin = max(0, ymin)
|
||
|
xmax = xmin + w
|
||
|
ymax = ymin + h
|
||
|
gt_bbox = [xmin, ymin, xmax, ymax]
|
||
|
result_boxs.append(gt_bbox)
|
||
|
if self.with_lmk:
|
||
|
assert len(split_str) > 18, 'When `with_lmk=True`, the number' \
|
||
|
'of characters per line in the annotation file should' \
|
||
|
'exceed 18.'
|
||
|
lmk0_x = float(split_str[5])
|
||
|
lmk0_y = float(split_str[6])
|
||
|
lmk1_x = float(split_str[8])
|
||
|
lmk1_y = float(split_str[9])
|
||
|
lmk2_x = float(split_str[11])
|
||
|
lmk2_y = float(split_str[12])
|
||
|
lmk3_x = float(split_str[14])
|
||
|
lmk3_y = float(split_str[15])
|
||
|
lmk4_x = float(split_str[17])
|
||
|
lmk4_y = float(split_str[18])
|
||
|
lmk_ignore_flag = 0 if lmk0_x == -1 else 1
|
||
|
gt_lmk_label = [
|
||
|
lmk0_x, lmk0_y, lmk1_x, lmk1_y, lmk2_x, lmk2_y, lmk3_x,
|
||
|
lmk3_y, lmk4_x, lmk4_y
|
||
|
]
|
||
|
result_boxs.append(gt_lmk_label)
|
||
|
result_boxs.append(lmk_ignore_flag)
|
||
|
file_dict[num_class].append(result_boxs)
|
||
|
|
||
|
return list(file_dict.values())
|
||
|
|
||
|
|
||
|
def widerface_label():
|
||
|
labels_map = {'face': 0}
|
||
|
return labels_map
|