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# -*- coding: utf-8 -*-
# Copyright (c) Alibaba, Inc. and its affiliates.
import cv2
import numpy as np
from PIL import Image
import torch
def convert_to_numpy(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.'
return image
class GrayAnnotator:
def __init__(self, cfg):
pass
def forward(self, image):
image = convert_to_numpy(image)
gray_map = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
return gray_map[..., None].repeat(3, axis=2)
class GrayVideoAnnotator(GrayAnnotator):
def forward(self, frames):
ret_frames = []
for frame in frames:
anno_frame = super().forward(np.array(frame))
ret_frames.append(anno_frame)
return ret_frames
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