From e6bbde6ccbf7d93f50082dcf7ef50cf43eabf206 Mon Sep 17 00:00:00 2001 From: "zhongning.hzn" Date: Thu, 9 Feb 2023 03:37:27 +0000 Subject: [PATCH] image_quality_assessment_mos use LoadImage for image io Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/11596634 --- .../cv/image_quality_assessment_mos.py | 17 +---------------- 1 file changed, 1 insertion(+), 16 deletions(-) diff --git a/modelscope/preprocessors/cv/image_quality_assessment_mos.py b/modelscope/preprocessors/cv/image_quality_assessment_mos.py index 522c30f2..f752b97b 100644 --- a/modelscope/preprocessors/cv/image_quality_assessment_mos.py +++ b/modelscope/preprocessors/cv/image_quality_assessment_mos.py @@ -5,8 +5,6 @@ from typing import Any, Dict, Union import cv2 import numpy as np -import torch -import torch.nn.functional as F from torchvision import transforms from modelscope.metainfo import Preprocessors @@ -14,7 +12,6 @@ from modelscope.preprocessors import LoadImage from modelscope.preprocessors.base import Preprocessor from modelscope.preprocessors.builder import PREPROCESSORS from modelscope.utils.constant import Fields -from modelscope.utils.hub import read_config from modelscope.utils.type_assert import type_assert @@ -29,18 +26,7 @@ class ImageQualityAssessmentMosPreprocessor(Preprocessor): super().__init__(**kwargs) def preprocessors(self, input): - if isinstance(input, str): - img = cv2.imread(input) - elif isinstance(input, PIL.Image.Image): - img = np.array(input.convert('RGB')) - elif isinstance(input, np.ndarray): - if len(input.shape) == 2: - img = cv2.cvtColor(input, cv2.COLOR_GRAY2BGR) - else: - img = input - else: - raise TypeError(f'input should be either str, PIL.Image,' - f' np.array, but got {type(input)}') + img = LoadImage.convert_to_ndarray(input) sub_img_dim = (720, 1280) resize_dim = (1080, 1920) h, w = img.shape[:2] @@ -67,7 +53,6 @@ class ImageQualityAssessmentMosPreprocessor(Preprocessor): if flag: img = np.rot90(img) - img = img[:, :, ::-1] img = LoadImage.convert_to_img(img) test_transforms = transforms.Compose([transforms.ToTensor()]) img = test_transforms(img)