Transpose: paddle.vision.transforms.Transpose(order=(2, 0, 1)) #将输入的图像数据更改为目标格式 作为函数使用的: adjust_brightness: paddle.vision.transforms.adjust_brightness(img, brightness_factor) adjust_contrast: paddle.vision.transforms.adjust_contrast(img, contrast_factor) adjust_hue: paddle.vis...
In [ ] import os import paddle import paddleslim import numpy as np import paddle.vision.transforms as T from PIL import Image# 开启静态图模式paddle.enable_static()# 模型的路径和文件名称model_dir = "models/MobileNetV1_infer" model_filename = 'inference.pdmodel' params_filename = 'inference...
( model_type='ffhq-inversion', size=1024, style_dim=512, n_mlp=8, channel_multiplier=2 ) transform = transforms.Compose( [ transforms.Resize(256), transforms.CenterCrop(256), transforms.Transpose(), transforms.Normalize([127.5, 127.5, 127.5], [127.5, 127.5, 127.5]), ] ) img1_tensor =...
import paddle from paddle.vision.transforms import Compose, ColorJitter, Resize,Transpose, Normalize import cv2 import numpy as np from PIL import Image from paddle.io import Dataset #自定义的数据预处理函数,输入原始图像,输出处理后的图像,可以借用paddle.vision.transforms的数据处理功能 def preprocess(img...
print('视觉数据预处理方法:'+str(paddle.vision.transforms.__all__))视觉数据预处理方法:['BaseTransform','Compose','Resize','RandomResizedCrop','CenterCrop','RandomHorizontalFlip','RandomVerticalFlip','Transpose','Normalize','BrightnessTransform','SaturationTransform','ContrastTransform','HueTransform'...
print('视觉数据预处理方法:' + str(paddle.vision.transforms.__all__)) 1. 视觉数据预处理方法:['BaseTransform', 'Compose', 'Resize', 'RandomResizedCrop', 'CenterCrop', 'RandomHorizontalFlip', 'RandomVerticalFlip', 'Transpose', 'Normalize', 'BrightnessTransform', 'SaturationTransform', 'Contrast...
numpyndarray,调整亮度、对比度、饱和度和色调后的图像。 代码示例¶ importnumpyasnpfromPILimportImagefrompaddle.vision.transformsimportColorJittertransform=ColorJitter(0.4,0.4,0.4,0.4)fake_img=Image.fromarray((np.random.rand(224,224,3)*255.).astype(np.uint8))fake_img=transform(fake_img)...
print('视觉数据预处理方法:'+str(paddle.vision.transforms.__all__)) 代码语言:javascript 复制 视觉数据预处理方法:['BaseTransform','Compose','Resize','RandomResizedCrop','CenterCrop','RandomHorizontalFlip','RandomVerticalFlip','Transpose','Normalize','BrightnessTransform','SaturationTransform','Contrast...
import paddle import paddle.vision.transforms as T from paddle.static import InputSpec # declarative mode transform = T.Compose([ T.Transpose(), T.Normalize([127.5], [127.5]) ]) val_dataset = paddle.vision.datasets.MNIST(mode='test', transform=transform) input = InputSpec([-1, 1, 28, ...
对于图像场景,可使用 paddle.vision.transforms.ToTensor 直接将 PIL.Image 格式的数据转为 Tensor,使用 paddle.to_tensor 将图像的标签(Label,通常是 Python 或 Numpy 格式的数据)转为 Tensor。 对于文本场景,需将文本数据解码为数字后,再通过 paddle.to_tensor 转为 Tensor。不同文本任务标签形式不一样,有的任务...