Spaces:
Running
Running
fixed upscaler
Browse files
frontend/webui/text_to_image_ui.py
CHANGED
@@ -13,8 +13,16 @@ from frontend.utils import enable_openvino_controls
|
|
13 |
from scipy.ndimage import zoom
|
14 |
import numpy as np
|
15 |
from PIL import Image
|
16 |
-
from super_image import CarnModel,ImageLoader
|
17 |
-
import
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
18 |
|
19 |
random_enabled = True
|
20 |
|
@@ -23,7 +31,8 @@ previous_width = 0
|
|
23 |
previous_height = 0
|
24 |
previous_model_id = ""
|
25 |
previous_num_of_images = 0
|
26 |
-
upscaler = CarnModel.from_pretrained(
|
|
|
27 |
|
28 |
def generate_text_to_image(
|
29 |
prompt,
|
@@ -79,14 +88,11 @@ def generate_text_to_image(
|
|
79 |
previous_num_of_images = 1
|
80 |
out_images = []
|
81 |
for image in images:
|
82 |
-
#out_images.append(image.resize((768, 768),resample=Image.LANCZOS))
|
83 |
in_image = ImageLoader.load_image(image)
|
84 |
up_image = upscaler(in_image)
|
85 |
-
|
86 |
-
|
87 |
-
up_image = cv2.cvtColor(up_image, cv2.COLOR_BGR2RGB)
|
88 |
-
out_images.append(Image.fromarray(up_image))
|
89 |
-
|
90 |
return out_images
|
91 |
|
92 |
|
|
|
13 |
from scipy.ndimage import zoom
|
14 |
import numpy as np
|
15 |
from PIL import Image
|
16 |
+
from super_image import CarnModel, ImageLoader
|
17 |
+
from torchvision import transforms
|
18 |
+
|
19 |
+
transform_image = transforms.ToPILImage()
|
20 |
+
|
21 |
+
|
22 |
+
def tensor2img(tensor):
|
23 |
+
tensor = tensor.squeeze(0).cpu().clamp(0, 1)
|
24 |
+
return transform_image(tensor)
|
25 |
+
|
26 |
|
27 |
random_enabled = True
|
28 |
|
|
|
31 |
previous_height = 0
|
32 |
previous_model_id = ""
|
33 |
previous_num_of_images = 0
|
34 |
+
upscaler = CarnModel.from_pretrained("eugenesiow/carn-bam", scale=2)
|
35 |
+
|
36 |
|
37 |
def generate_text_to_image(
|
38 |
prompt,
|
|
|
88 |
previous_num_of_images = 1
|
89 |
out_images = []
|
90 |
for image in images:
|
91 |
+
# out_images.append(image.resize((768, 768),resample=Image.LANCZOS))
|
92 |
in_image = ImageLoader.load_image(image)
|
93 |
up_image = upscaler(in_image)
|
94 |
+
out_images.append(tensor2img(up_image))
|
95 |
+
|
|
|
|
|
|
|
96 |
return out_images
|
97 |
|
98 |
|