default='none',
type=str,
dest='test.out_dir',
help='The test out directory of images.')
# *********** Params for env. **********
parser.add_argument('--seed', default=None, type=int, help='manual seed')
parser.add_argument('--cudnn',
type=str2bool,
nargs='?',
default=True,
help='Use CUDNN.')
parser.add_argument("--local_rank", default=0, type=int)
args = parser.parse_args()
configer = Configer(args_parser=args)
if args.seed is not None:
random.seed(args.seed + args.local_rank)
torch.manual_seed(args.seed + args.local_rank)
cudnn.enabled = True
cudnn.benchmark = args.cudnn
abs_data_dir = os.path.expanduser(configer.get('data', 'data_dir'))
configer.update('data.data_dir', abs_data_dir)
if configer.get('gpu') is not None and not configer.get(
'network.distributed', default=False):
os.environ["CUDA_VISIBLE_DEVICES"] = ','.join(
str(gpu_id) for gpu_id in configer.get('gpu'))
fontScale=0.5,
color=self.configer.get(
'details', 'color_list')[label_id % color_num],
thickness=2)
return image_canvas
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--hypes_file',
default=None,
type=str,
dest='hypes_file',
help='The file of the hyper parameters.')
parser.add_argument('--data_dir',
default=None,
type=str,
dest='data_dir',
help='The data dir of Det Parser.')
parser.add_argument('--json_file',
default=None,
type=str,
dest='json_file',
help='The json file of Det Parser.')
args_parser = parser.parse_args()
det_parser = ClsParser(Configer(hypes_file=args_parser.hypes_file))
det_parser.parse_dir_cls(args_parser.data_dir, args_parser.json_file)
prec = -1.
ap = -1.
return rec, prec, ap
if __name__ == "__main__":
# Example:
# python coco_evaluator.py --config_file ../../../../configs/pose/coco/openpose_vgg19_coco_pose.conf
# --json_dir ../../../results/pose/coco/test_dir/coco/json/
# --gt_dir /home/donny/DataSet/MSCOCO/annotations/person_keypoints_val2017.json
parser = argparse.ArgumentParser()
parser.add_argument('--config_file', default='../../../configs/det/voc/ssd300_vgg16_voc_det.conf', type=str,
dest='config_file', help='The configs file of pose.')
parser.add_argument('--gt_dir', default='/home/donny/DataSet/VOC/VOCdevkit/VOC2007', type=str,
dest='gt_dir', help='The groundtruth annotations file of voc dets.')
parser.add_argument('--json_dir', default='../../../val/results/det/voc/test_dir/image/json', type=str,
dest='json_dir', help='The json dir of predict annotations.')
parser.add_argument('--dataset', default='VOC2007', type=str,
dest='dataset', help='The target dataset.')
args = parser.parse_args()
coco_evaluator = VOCEvaluator(Configer(hypes_file=args.hypes_file))
if args.gt_dir is not None:
pred_dir = coco_evaluator.relabel(args.json_dir)
coco_evaluator.evaluate(pred_dir, args.gt_dir, use_07=(args.dataset == 'VOC2007'))
else:
submission_dir = coco_evaluator.relabel(args.json_dir)
Log.info('Submisson file path: {}'.format(submission_dir))
(int(object['bbox'][0]), int(object['bbox'][1])),
(int(object['bbox'][2]), int(object['bbox'][3])),
color=self.configer.get('details', 'color_list')[object['label'] % color_num], thickness=3)
cv2.putText(image_canvas, class_name,
(int(object['bbox'][0]) + 5, int(object['bbox'][3]) - 5),
cv2.FONT_HERSHEY_SIMPLEX, fontScale=0.5,
color=self.configer.get('details', 'color_list')[object['label'] % color_num], thickness=2)
return image_canvas
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--config_file', default='../../configs/det/coco/yolov3_darknet_coco_det.conf', type=str,
dest='config_file', help='The file of the hyper parameters.')
parser.add_argument('--image_file', default=None, type=str,
dest='image_file', help='The image file of Det Parser.')
parser.add_argument('--json_file', default=None, type=str,
dest='json_file', help='The json file of Det Parser.')
parser.add_argument('--image_dir', default='/home/donny/DataSets/Pallet/train/image', type=str,
dest='image_dir', help='The image directory of Det Parser.')
parser.add_argument('--json_dir', default='/home/donny/DataSets/Pallet/train/json', type=str,
dest='json_dir', help='The json directory of Det Parser.')
args_parser = parser.parse_args()
det_parser = DetParser(Configer(config_file=args_parser.config_file))
det_parser.parse_img_det(args_parser.image_file, args_parser.json_file)
det_parser.parse_dir_det(args_parser.image_dir, args_parser.json_dir)
default='../../configs/seg/coco/mr_fpn_coco_seg.conf',
type=str,
dest='config_file',
help='The file of the hyper parameters.')
parser.add_argument('--image_file',
default=None,
type=str,
dest='image_file',
help='The image file of Ins Parser.')
parser.add_argument('--json_file',
default=None,
type=str,
dest='json_file',
help='The json file of Det Parser.')
parser.add_argument('--image_dir',
default='/home/donny/DataSet/COCO_INS/train/image',
type=str,
dest='image_dir',
help='The image directory of Ins Parser.')
parser.add_argument('--json_dir',
default='/home/donny/DataSet/COCO_INS/train/json',
type=str,
dest='json_dir',
help='The json directory of Ins Parser.')
args_parser = parser.parse_args()
ins_parser = InsParser(Configer(hypes_file=args_parser.hypes_file))
ins_parser.parse_img_det(args_parser.image_file, args_parser.json_file)
ins_parser.parse_dir_det(args_parser.image_dir, args_parser.json_dir)
dest='config_file',
help='The configs file of pose.')
parser.add_argument('--gt_dir',
default='/home/donny/DataSet/VOC/VOCdevkit/VOC2007',
type=str,
dest='gt_dir',
help='The groundtruth annotations file of voc dets.')
parser.add_argument(
'--json_dir',
default='../../../val/results/det/voc/test_dir/image/json',
type=str,
dest='json_dir',
help='The json dir of predict annotations.')
parser.add_argument('--dataset',
default='VOC2007',
type=str,
dest='dataset',
help='The target dataset.')
args = parser.parse_args()
coco_evaluator = VOCEvaluator(Configer(config_file=args.config_file))
if args.gt_dir is not None:
pred_dir = coco_evaluator.relabel(args.json_dir)
coco_evaluator.evaluate(pred_dir,
args.gt_dir,
use_07=(args.dataset == 'VOC2007'))
else:
submission_dir = coco_evaluator.relabel(args.json_dir)
Log.info('Submisson file path: {}'.format(submission_dir))
(int(length / 2),
self.configer.get('res', 'vis_stick_width')), int(angle), 0, 360, 1)
cv2.fillConvexPoly(cur_canvas, polygon, self.configer.get('details', 'color_list')[i])
image_canvas = cv2.addWeighted(image_canvas, 0.4, cur_canvas, 0.6, 0)
return image_canvas
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--hypes_file', default=None, type=str,
dest='hypes_file', help='The file of the hyper parameters.')
parser.add_argument('--image_file', default=None, type=str,
dest='image_file', help='The image file of Pose Parser.')
parser.add_argument('--json_file', default=None, type=str,
dest='json_file', help='The json file of Pose Parser.')
parser.add_argument('--mask_file', default=None, type=str,
dest='mask_file', help='The mask file of Pose Parser.')
parser.add_argument('--image_dir', default=None, type=str,
dest='image_dir', help='The image directory of Pose Parser.')
parser.add_argument('--json_dir', default=None, type=str,
dest='json_dir', help='The json directory of Pose Parser.')
parser.add_argument('--mask_dir', default=None, type=str,
dest='mask_dir', help='The mask directory of Pose Parser.')
args_parser = parser.parse_args()
pose_parser = PoseParser(Configer(hypes_file=args_parser.hypes_file))
pose_parser.parse_img_pose(args_parser.image_file, args_parser.json_file, args_parser.mask_file)
pose_parser.parse_dir_pose(args_parser.image_dir, args_parser.json_dir, args_parser.mask_dir)
gtmap[np.newaxis, :, :])
img_cnt += 1
Log.info('Evaluate {} images'.format(img_cnt))
Log.info('mIOU: {}'.format(self.seg_running_score.get_mean_iou()))
Log.info('Pixel ACC: {}'.format(
self.seg_running_score.get_pixel_acc()))
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--config_file',
default=None,
type=str,
dest='config_file',
help='The configs file of pose.')
parser.add_argument('--gt_dir',
default=None,
type=str,
dest='gt_dir',
help='The groundtruth annotations.')
parser.add_argument('--pred_dir',
default=None,
type=str,
dest='pred_dir',
help='The label dir of predict annotations.')
args = parser.parse_args()
ade20k_evaluator = ADE20KEvaluator(Configer(hypes_file=args.hypes_file))
ade20k_evaluator.evaluate(args.pred_dir, args.gt_dir)
img_cnt += 1
Log.info('Evaluate {} images'.format(img_cnt))
Log.info('Class mIOU: {}'.format(self.seg_running_score.get_cls_iou()))
Log.info('mIOU: {}'.format(self.seg_running_score.get_mean_iou()))
Log.info('Pixel ACC: {}'.format(
self.seg_running_score.get_pixel_acc()))
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--config_file',
default=None,
type=str,
dest='config_file',
help='The configs file of pose.')
parser.add_argument('--gt_dir',
default=None,
type=str,
dest='gt_dir',
help='The groundtruth annotations.')
parser.add_argument('--pred_dir',
default=None,
type=str,
dest='pred_dir',
help='The label dir of predict annotations.')
args = parser.parse_args()
seg_evaluator = SegEvaluator(Configer(config_file=args.config_file))
seg_evaluator.evaluate(args.pred_dir, args.gt_dir)
default=None,
type=str,
dest='hypes_file',
help='The file of the hyper parameters.')
parser.add_argument('--image_file',
default=None,
type=str,
dest='image_file',
help='The image file of Seg Parser.')
parser.add_argument('--label_file',
default=None,
type=str,
dest='label_file',
help='The label file of Seg Parser.')
parser.add_argument('--image_dir',
default=None,
type=str,
dest='image_dir',
help='The image directory of Seg Parser.')
parser.add_argument('--label_dir',
default=None,
type=str,
dest='label_dir',
help='The label directory of Seg Parser.')
args_parser = parser.parse_args()
seg_parser = SegParser(Configer(hypes_file=args_parser.hypes_file))
seg_parser.parse_img_seg(args_parser.image_file, args_parser.label_file)
seg_parser.parse_dir_seg(args_parser.image_dir, args_parser.label_dir)
