mirror of
https://github.com/maciej3031/comixify.git
synced 2026-03-11 08:54:35 +00:00
62 lines
2 KiB
Python
62 lines
2 KiB
Python
import os
|
|
|
|
import cv2
|
|
import numpy as np
|
|
import torch
|
|
import torchvision.transforms as transforms
|
|
from django.conf import settings
|
|
from torch.autograd import Variable
|
|
|
|
from CartoonGAN.network.Transformer import Transformer
|
|
|
|
|
|
class StyleTransfer():
|
|
@classmethod
|
|
def get_stylized_frames(cls, frames, method="cartoon_gan", gpu=settings.GPU, **kwargs):
|
|
if method == "cartoon_gan":
|
|
return cls._cartoon_gan_stylize(frames, gpu=gpu, **kwargs)
|
|
|
|
@staticmethod
|
|
def _cartoon_gan_stylize(frames, gpu=True, **kwargs):
|
|
style = kwargs.get("style", "Hayao")
|
|
resize = kwargs.get("resize", 450)
|
|
|
|
# TODO: We should load model to memory right after deployment, not on each request.
|
|
# load pretrained model
|
|
model = Transformer()
|
|
model.load_state_dict(torch.load(os.path.join("CartoonGAN/pretrained_model", style + "_net_G_float.pth")))
|
|
model.eval()
|
|
model.cuda() if gpu else model.float()
|
|
|
|
stylized_imgs = []
|
|
for img in frames:
|
|
# resize image, keep aspect ratio
|
|
h, w, _ = img.shape
|
|
ratio = h * 1.0 / w
|
|
if ratio > 1:
|
|
h = resize
|
|
w = int(h * 1.0 / ratio)
|
|
else:
|
|
w = resize
|
|
h = int(w * ratio)
|
|
input_image = cv2.resize(img, (w, h))
|
|
input_image = transforms.ToTensor()(input_image).unsqueeze(0)
|
|
|
|
# preprocess, (-1, 1)
|
|
input_image = -1 + 2 * input_image
|
|
input_image = Variable(input_image).cuda() if gpu else Variable(input_image).float()
|
|
|
|
# forward
|
|
output_image = model(input_image)
|
|
output_image = output_image[0]
|
|
|
|
# deprocess, (0, 1)
|
|
output_image = (output_image.data.cpu().float() * 0.5 + 0.5).numpy()
|
|
|
|
# switch channels -> (c, h, w) -> (h, w, c)
|
|
output_image = np.rollaxis(output_image, 0, 3)
|
|
|
|
# append image to result images
|
|
stylized_imgs.append(output_image)
|
|
|
|
return stylized_imgs
|