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visu_transform.py
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visu_transform.py
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import numpy as np
import torchvision
from torchvision import datasets, models, transforms
import matplotlib.pyplot as plt
from PIL import Image
def imshow(inp, title=None):
"""Imshow for Tensor."""
inp = inp.numpy().transpose((1, 2, 0))
mean = np.array([0.485, 0.456, 0.406])
std = np.array([0.229, 0.224, 0.225])
inp = std * inp + mean
inp = np.clip(inp, 0, 1)
plt.imshow(inp)
if title is not None:
plt.title(title)
plt.pause(3) # pause a bit so that plots are updated
def show(img):
"""Show PIL image [0,1] """
npimg = img.numpy()
plt.imshow(np.transpose(npimg, (1, 2, 0)), interpolation='nearest')
plt.pause(3)
transf = transforms.Compose([
transforms.RandomResizedCrop(224),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
])
fourmi = Image.open("fourmi.jpg")
fourmi.show() # Affichage de l'image
fourmi = transf(fourmi)
imshow(fourmi) # Affichage de l'image transformée