padmanabhbosamia commited on
Commit
b815b4e
·
1 Parent(s): deb41ea

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +7 -6
app.py CHANGED
@@ -12,6 +12,7 @@ from torchvision import transforms as tfms
12
  from tqdm.auto import tqdm
13
  from transformers import CLIPTextModel, CLIPTokenizer, logging
14
  import os
 
15
  import cv2
16
  import torchvision.transforms as T
17
 
@@ -21,7 +22,7 @@ logging.set_verbosity_error()
21
  torch_device = "cuda" if torch.cuda.is_available() else "cpu"
22
 
23
  # Load the autoencoder
24
- vae = AutoencoderKL.from_pretrained("CompVis/stable-diffusion-v1-4", subfolder='vae')
25
 
26
  # Load tokenizer and text encoder to tokenize and encode the text
27
  tokenizer = CLIPTokenizer.from_pretrained("openai/clip-vit-large-patch14")
@@ -38,9 +39,9 @@ vae = vae.to(torch_device)
38
  text_encoder = text_encoder.to(torch_device)
39
  unet = unet.to(torch_device)
40
 
41
- style_files = ['Thumps_up.bin', 'birb_style.bin',
42
- 'snoopy.bin', 'pop_art.bin',
43
- 'boot-mjstyle.bin']
44
 
45
  images_without_loss = []
46
  images_with_loss = []
@@ -251,7 +252,7 @@ def display_images_in_rows(images_with_titles, titles):
251
  # plt.show()
252
 
253
 
254
- def image_generator(prompt = "snoopy", loss_function=None):
255
  images_without_loss = []
256
  images_with_loss = []
257
  if loss_function == "Yes":
@@ -267,7 +268,7 @@ def image_generator(prompt = "snoopy", loss_function=None):
267
  images_with_loss.append(generated_img)
268
 
269
  generated_sd_images = []
270
- titles = ["Bird_style", "Boot-mjstyle", "Snoopy Style", "Pop Art Style", "Thumpsup Style"]
271
 
272
  for i in range(len(titles)):
273
  generated_sd_images.append((images_without_loss[i], titles[i]))
 
12
  from tqdm.auto import tqdm
13
  from transformers import CLIPTextModel, CLIPTokenizer, logging
14
  import os
15
+ MY_TOKEN=os.environ.get('Stable_Diffusion')
16
  import cv2
17
  import torchvision.transforms as T
18
 
 
22
  torch_device = "cuda" if torch.cuda.is_available() else "cpu"
23
 
24
  # Load the autoencoder
25
+ vae = AutoencoderKL.from_pretrained("CompVis/stable-diffusion-v1-4", subfolder="vae",use_auth_token=MY_TOKEN)
26
 
27
  # Load tokenizer and text encoder to tokenize and encode the text
28
  tokenizer = CLIPTokenizer.from_pretrained("openai/clip-vit-large-patch14")
 
39
  text_encoder = text_encoder.to(torch_device)
40
  unet = unet.to(torch_device)
41
 
42
+ style_files = ['bird_style.bin', 'ronaldo.bin',
43
+ 'pop_art.bin', 'threestooges.bin',
44
+ 'bflan.bin']
45
 
46
  images_without_loss = []
47
  images_with_loss = []
 
252
  # plt.show()
253
 
254
 
255
+ def image_generator(prompt = "sky", loss_function=None):
256
  images_without_loss = []
257
  images_with_loss = []
258
  if loss_function == "Yes":
 
268
  images_with_loss.append(generated_img)
269
 
270
  generated_sd_images = []
271
+ titles = ["<birb-style>", "'<ronaldo>", "<pop-art>", "<threestooges>", "<Marbled-painting>"]
272
 
273
  for i in range(len(titles)):
274
  generated_sd_images.append((images_without_loss[i], titles[i]))