Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
|
@@ -25,7 +25,7 @@ pipe = GlmImagePipeline.from_pretrained(
|
|
| 25 |
def infer(prompt, input_images=None, seed=42, randomize_seed=False, width=1024, height=1024,
|
| 26 |
num_inference_steps=50, guidance_scale=1.5, progress=gr.Progress(track_tqdm=True)):
|
| 27 |
"""Main inference function"""
|
| 28 |
-
|
| 29 |
if randomize_seed:
|
| 30 |
seed = random.randint(0, MAX_SEED)
|
| 31 |
|
|
@@ -34,7 +34,8 @@ def infer(prompt, input_images=None, seed=42, randomize_seed=False, width=1024,
|
|
| 34 |
height = (height // 32) * 32
|
| 35 |
|
| 36 |
generator = torch.Generator(device="cuda").manual_seed(seed)
|
| 37 |
-
|
|
|
|
| 38 |
# Prepare image list for image-to-image mode
|
| 39 |
image_list = None
|
| 40 |
if input_images is not None and len(input_images) > 0:
|
|
@@ -46,7 +47,7 @@ def infer(prompt, input_images=None, seed=42, randomize_seed=False, width=1024,
|
|
| 46 |
elif isinstance(img, Image.Image):
|
| 47 |
img = img.convert("RGB")
|
| 48 |
image_list.append(img)
|
| 49 |
-
|
| 50 |
pipe_kwargs = {
|
| 51 |
"prompt": prompt,
|
| 52 |
"height": height,
|
|
@@ -55,11 +56,11 @@ def infer(prompt, input_images=None, seed=42, randomize_seed=False, width=1024,
|
|
| 55 |
"guidance_scale": guidance_scale,
|
| 56 |
"generator": generator,
|
| 57 |
}
|
| 58 |
-
|
| 59 |
# Add images for image-to-image mode
|
| 60 |
if image_list is not None:
|
| 61 |
pipe_kwargs["image"] = image_list
|
| 62 |
-
|
| 63 |
image = pipe(**pipe_kwargs).images[0]
|
| 64 |
|
| 65 |
return image, seed
|
|
@@ -98,23 +99,6 @@ def update_dimensions_from_image(image_list):
|
|
| 98 |
|
| 99 |
return new_width, new_height
|
| 100 |
|
| 101 |
-
|
| 102 |
-
# Text-to-Image examples
|
| 103 |
-
examples_t2i = [
|
| 104 |
-
["A beautifully designed modern food magazine style dessert recipe illustration, themed around a raspberry mousse cake. Clean and bright layout with a bold black title 'Raspberry Mousse Cake Recipe Guide', soft-lit close-up of the finished cake showing light pink layers with fresh raspberries and mint leaves."],
|
| 105 |
-
["A kawaii die-cut sticker of a chubby orange cat, featuring big sparkly eyes and a happy smile with paws raised in greeting and a heart-shaped pink nose. Smooth rounded lines with black outlines and soft gradient shading with pink cheeks."],
|
| 106 |
-
["Soaking wet capybara taking shelter under a banana leaf in the rainy jungle, close up photo, water droplets visible on fur, lush green background"],
|
| 107 |
-
["A photorealistic portrait of an astronaut in a detailed spacesuit, floating in space with Earth visible in the background, dramatic lighting from the sun"],
|
| 108 |
-
["An elegant art deco poster design for a jazz concert, featuring geometric patterns in gold and deep blue, stylized saxophone silhouette, vintage typography"],
|
| 109 |
-
]
|
| 110 |
-
|
| 111 |
-
# Image-to-Image examples
|
| 112 |
-
examples_i2i = [
|
| 113 |
-
["Transform this scene into a cyberpunk cityscape at night with neon lights and flying cars"],
|
| 114 |
-
["Replace the background with an underwater coral reef scene with tropical fish"],
|
| 115 |
-
["Convert this to a watercolor painting style with soft pastel colors"],
|
| 116 |
-
]
|
| 117 |
-
|
| 118 |
css = """
|
| 119 |
#col-container {
|
| 120 |
margin: 0 auto;
|
|
|
|
| 25 |
def infer(prompt, input_images=None, seed=42, randomize_seed=False, width=1024, height=1024,
|
| 26 |
num_inference_steps=50, guidance_scale=1.5, progress=gr.Progress(track_tqdm=True)):
|
| 27 |
"""Main inference function"""
|
| 28 |
+
print("Randomizing seed")
|
| 29 |
if randomize_seed:
|
| 30 |
seed = random.randint(0, MAX_SEED)
|
| 31 |
|
|
|
|
| 34 |
height = (height // 32) * 32
|
| 35 |
|
| 36 |
generator = torch.Generator(device="cuda").manual_seed(seed)
|
| 37 |
+
|
| 38 |
+
print("preparing iages")
|
| 39 |
# Prepare image list for image-to-image mode
|
| 40 |
image_list = None
|
| 41 |
if input_images is not None and len(input_images) > 0:
|
|
|
|
| 47 |
elif isinstance(img, Image.Image):
|
| 48 |
img = img.convert("RGB")
|
| 49 |
image_list.append(img)
|
| 50 |
+
print("handling kwargs")
|
| 51 |
pipe_kwargs = {
|
| 52 |
"prompt": prompt,
|
| 53 |
"height": height,
|
|
|
|
| 56 |
"guidance_scale": guidance_scale,
|
| 57 |
"generator": generator,
|
| 58 |
}
|
| 59 |
+
print("adding images")
|
| 60 |
# Add images for image-to-image mode
|
| 61 |
if image_list is not None:
|
| 62 |
pipe_kwargs["image"] = image_list
|
| 63 |
+
print("running kwargs")
|
| 64 |
image = pipe(**pipe_kwargs).images[0]
|
| 65 |
|
| 66 |
return image, seed
|
|
|
|
| 99 |
|
| 100 |
return new_width, new_height
|
| 101 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 102 |
css = """
|
| 103 |
#col-container {
|
| 104 |
margin: 0 auto;
|