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# -*- coding: utf-8 -*-
# Copyright (c) Alibaba, Inc. and its affiliates.
from abc import ABCMeta
import cv2
import numpy as np
import torch
from PIL import Image
from scepter.modules.annotator.base_annotator import BaseAnnotator
from scepter.modules.annotator.registry import ANNOTATORS
from scepter.modules.utils.config import dict_to_yaml
@ANNOTATORS.register_class()
class ColorAnnotator(BaseAnnotator, metaclass=ABCMeta):
para_dict = {}
def __init__(self, cfg, logger=None):
super().__init__(cfg, logger=logger)
self.ratio = cfg.get('RATIO', 64)
self.random_cfg = cfg.get('RANDOM_CFG', None)
def forward(self, image):
if isinstance(image, Image.Image):
image = np.array(image)
elif isinstance(image, torch.Tensor):
image = image.detach().cpu().numpy()
elif isinstance(image, np.ndarray):
image = image.copy()
else:
raise f'Unsurpport datatype{type(image)}, only surpport np.ndarray, torch.Tensor, Pillow Image.'
h, w = image.shape[:2]
if self.random_cfg is None:
ratio = self.ratio
else:
proba = self.random_cfg.get('PROBA', 1.0)
if np.random.random() < proba:
if 'CHOICE_RATIO' in self.random_cfg:
ratio = np.random.choice(self.random_cfg['CHOICE_RATIO'])
else:
min_ratio = self.random_cfg.get('MIN_RATIO', 48)
max_ratio = self.random_cfg.get('MAX_RATIO', 96)
ratio = np.random.randint(min_ratio, max_ratio)
else:
ratio = self.ratio
image = cv2.resize(image, (int(w // ratio), int(h // ratio)),
interpolation=cv2.INTER_CUBIC)
image = cv2.resize(image, (w, h), interpolation=cv2.INTER_NEAREST)
assert len(image.shape) < 4
return image
@staticmethod
def get_config_template():
return dict_to_yaml('ANNOTATORS',
__class__.__name__,
ColorAnnotator.para_dict,
set_name=True)
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