利用Inception Score衡量自己的模型生成的图片多样性
代码:
import torch
from torch import nn
from torch.nn import functional as F
import torch.utils.data
from torchvision.models.inception import inception_v3
import numpy as np
from tqdm import tqdm
from PIL import Image
import os
from scipy.stats import entropy
# we should use same mean and std for inception v3 model in training and testing process
# reference web page: https://pytorch.org/hub/pytorch_vision_inception_v3/
mean_inception = [0.485, 0.456, 0.406]
std_inception = [0.229, 0.224, 0.225]
def imread(filename):
"""
Loads an image file into a (height, width, 3) uint8 ndarray.
"""
return np.asarray(Image.open(filename), dtype=np.uint8)[..., :3]
def inception_score(batch_size=50, resize=True, splits=10)