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A10G
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import PIL
from PIL import Image, ImageDraw ,ImageFont
from matplotlib import pyplot as plt
import torchvision.transforms as T
import os
import torch
import yaml
# This file was copied from the DDPM inversion Repo - https://github.com/inbarhub/DDPM_inversion #
def show_torch_img(img):
img = to_np_image(img)
plt.imshow(img)
plt.axis("off")
def to_np_image(all_images):
all_images = (all_images.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8).cpu().numpy()[0]
return all_images
def tensor_to_pil(tensor_imgs):
if type(tensor_imgs) == list:
tensor_imgs = torch.cat(tensor_imgs)
tensor_imgs = (tensor_imgs / 2 + 0.5).clamp(0, 1)
to_pil = T.ToPILImage()
pil_imgs = [to_pil(img) for img in tensor_imgs]
return pil_imgs
def pil_to_tensor(pil_imgs):
to_torch = T.ToTensor()
if type(pil_imgs) == PIL.Image.Image:
tensor_imgs = to_torch(pil_imgs).unsqueeze(0)*2-1
elif type(pil_imgs) == list:
tensor_imgs = torch.cat([to_torch(pil_imgs).unsqueeze(0)*2-1 for img in pil_imgs]).to(device)
else:
raise Exception("Input need to be PIL.Image or list of PIL.Image")
return tensor_imgs
## TODO implement this
# n = 10
# num_rows = 4
# num_col = n // num_rows
# num_col = num_col + 1 if n % num_rows else num_col
# num_col
def add_margin(pil_img, top = 0, right = 0, bottom = 0,
left = 0, color = (255,255,255)):
width, height = pil_img.size
new_width = width + right + left
new_height = height + top + bottom
result = Image.new(pil_img.mode, (new_width, new_height), color)
result.paste(pil_img, (left, top))
return result
def image_grid(imgs, rows = 1, cols = None,
size = None,
titles = None, text_pos = (0, 0)):
if type(imgs) == list and type(imgs[0]) == torch.Tensor:
imgs = torch.cat(imgs)
if type(imgs) == torch.Tensor:
imgs = tensor_to_pil(imgs)
if not size is None:
imgs = [img.resize((size,size)) for img in imgs]
if cols is None:
cols = len(imgs)
assert len(imgs) >= rows*cols
top=20
w, h = imgs[0].size
delta = 0
if len(imgs)> 1 and not imgs[1].size[1] == h:
delta = top
h = imgs[1].size[1]
if not titles is None:
font = ImageFont.truetype("/usr/share/fonts/truetype/freefont/FreeMono.ttf",
size = 20, encoding="unic")
h = top + h
grid = Image.new('RGB', size=(cols*w, rows*h+delta))
for i, img in enumerate(imgs):
if not titles is None:
img = add_margin(img, top = top, bottom = 0,left=0)
draw = ImageDraw.Draw(img)
draw.text(text_pos, titles[i],(0,0,0),
font = font)
if not delta == 0 and i > 0:
grid.paste(img, box=(i%cols*w, i//cols*h+delta))
else:
grid.paste(img, box=(i%cols*w, i//cols*h))
return grid
"""
input_folder - dataset folder
"""
def load_dataset(input_folder):
# full_file_names = glob.glob(input_folder)
# class_names = [x[0] for x in os.walk(input_folder)]
class_names = next(os.walk(input_folder))[1]
class_names[:] = [d for d in class_names if not d[0] == '.']
file_names=[]
for class_name in class_names:
cur_path = os.path.join(input_folder, class_name)
filenames = next(os.walk(cur_path), (None, None, []))[2]
filenames = [f for f in filenames if not f[0] == '.']
file_names.append(filenames)
return class_names, file_names
def dataset_from_yaml(yaml_location):
with open(yaml_location, 'r') as stream:
data_loaded = yaml.safe_load(stream)
return data_loaded |