Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -3,8 +3,8 @@ import numpy as np
|
|
3 |
import random
|
4 |
import spaces
|
5 |
import torch
|
6 |
-
from diffusers import
|
7 |
-
from transformers import CLIPTextModel, CLIPTokenizer,T5EncoderModel, T5TokenizerFast
|
8 |
from live_preview_helpers import calculate_shift, retrieve_timesteps, flux_pipe_call_that_returns_an_iterable_of_images
|
9 |
|
10 |
dtype = torch.bfloat16
|
@@ -20,6 +20,9 @@ MAX_IMAGE_SIZE = 2048
|
|
20 |
|
21 |
pipe.flux_pipe_call_that_returns_an_iterable_of_images = flux_pipe_call_that_returns_an_iterable_of_images.__get__(pipe)
|
22 |
|
|
|
|
|
|
|
23 |
@spaces.GPU(duration=75)
|
24 |
def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidance_scale=3.5, num_inference_steps=28, progress=gr.Progress(track_tqdm=True)):
|
25 |
if randomize_seed:
|
@@ -36,15 +39,17 @@ def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidan
|
|
36 |
output_type="pil",
|
37 |
good_vae=good_vae,
|
38 |
):
|
|
|
|
|
39 |
yield img, seed
|
40 |
-
|
41 |
examples = [
|
42 |
"a tiny astronaut hatching from an egg on the moon",
|
43 |
"a cat holding a sign that says hello world",
|
44 |
"an anime illustration of a wiener schnitzel",
|
45 |
]
|
46 |
|
47 |
-
css="""
|
48 |
#col-container {
|
49 |
margin: 0 auto;
|
50 |
max-width: 520px;
|
@@ -60,7 +65,6 @@ with gr.Blocks(css=css) as demo:
|
|
60 |
""")
|
61 |
|
62 |
with gr.Row():
|
63 |
-
|
64 |
prompt = gr.Text(
|
65 |
label="Prompt",
|
66 |
show_label=False,
|
@@ -68,13 +72,11 @@ with gr.Blocks(css=css) as demo:
|
|
68 |
placeholder="Enter your prompt",
|
69 |
container=False,
|
70 |
)
|
71 |
-
|
72 |
run_button = gr.Button("Run", scale=0)
|
73 |
|
74 |
result = gr.Image(label="Result", show_label=False)
|
75 |
|
76 |
with gr.Accordion("Advanced Settings", open=False):
|
77 |
-
|
78 |
seed = gr.Slider(
|
79 |
label="Seed",
|
80 |
minimum=0,
|
@@ -82,11 +84,9 @@ with gr.Blocks(css=css) as demo:
|
|
82 |
step=1,
|
83 |
value=0,
|
84 |
)
|
85 |
-
|
86 |
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
|
87 |
|
88 |
with gr.Row():
|
89 |
-
|
90 |
width = gr.Slider(
|
91 |
label="Width",
|
92 |
minimum=256,
|
@@ -94,7 +94,6 @@ with gr.Blocks(css=css) as demo:
|
|
94 |
step=32,
|
95 |
value=1024,
|
96 |
)
|
97 |
-
|
98 |
height = gr.Slider(
|
99 |
label="Height",
|
100 |
minimum=256,
|
@@ -104,7 +103,6 @@ with gr.Blocks(css=css) as demo:
|
|
104 |
)
|
105 |
|
106 |
with gr.Row():
|
107 |
-
|
108 |
guidance_scale = gr.Slider(
|
109 |
label="Guidance Scale",
|
110 |
minimum=1,
|
@@ -112,7 +110,6 @@ with gr.Blocks(css=css) as demo:
|
|
112 |
step=0.1,
|
113 |
value=3.5,
|
114 |
)
|
115 |
-
|
116 |
num_inference_steps = gr.Slider(
|
117 |
label="Number of inference steps",
|
118 |
minimum=1,
|
@@ -122,18 +119,27 @@ with gr.Blocks(css=css) as demo:
|
|
122 |
)
|
123 |
|
124 |
gr.Examples(
|
125 |
-
examples
|
126 |
-
fn
|
127 |
-
inputs
|
128 |
-
outputs
|
129 |
cache_examples="lazy"
|
130 |
)
|
131 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
132 |
gr.on(
|
133 |
triggers=[run_button.click, prompt.submit],
|
134 |
-
fn
|
135 |
-
inputs
|
136 |
-
outputs
|
137 |
)
|
138 |
|
139 |
-
demo.launch()
|
|
|
3 |
import random
|
4 |
import spaces
|
5 |
import torch
|
6 |
+
from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler, AutoencoderTiny, AutoencoderKL
|
7 |
+
from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5TokenizerFast
|
8 |
from live_preview_helpers import calculate_shift, retrieve_timesteps, flux_pipe_call_that_returns_an_iterable_of_images
|
9 |
|
10 |
dtype = torch.bfloat16
|
|
|
20 |
|
21 |
pipe.flux_pipe_call_that_returns_an_iterable_of_images = flux_pipe_call_that_returns_an_iterable_of_images.__get__(pipe)
|
22 |
|
23 |
+
# History to keep track of generated images and their parameters
|
24 |
+
history = []
|
25 |
+
|
26 |
@spaces.GPU(duration=75)
|
27 |
def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidance_scale=3.5, num_inference_steps=28, progress=gr.Progress(track_tqdm=True)):
|
28 |
if randomize_seed:
|
|
|
39 |
output_type="pil",
|
40 |
good_vae=good_vae,
|
41 |
):
|
42 |
+
# Save to history
|
43 |
+
history.append((img, prompt, seed, width, height, guidance_scale, num_inference_steps))
|
44 |
yield img, seed
|
45 |
+
|
46 |
examples = [
|
47 |
"a tiny astronaut hatching from an egg on the moon",
|
48 |
"a cat holding a sign that says hello world",
|
49 |
"an anime illustration of a wiener schnitzel",
|
50 |
]
|
51 |
|
52 |
+
css = """
|
53 |
#col-container {
|
54 |
margin: 0 auto;
|
55 |
max-width: 520px;
|
|
|
65 |
""")
|
66 |
|
67 |
with gr.Row():
|
|
|
68 |
prompt = gr.Text(
|
69 |
label="Prompt",
|
70 |
show_label=False,
|
|
|
72 |
placeholder="Enter your prompt",
|
73 |
container=False,
|
74 |
)
|
|
|
75 |
run_button = gr.Button("Run", scale=0)
|
76 |
|
77 |
result = gr.Image(label="Result", show_label=False)
|
78 |
|
79 |
with gr.Accordion("Advanced Settings", open=False):
|
|
|
80 |
seed = gr.Slider(
|
81 |
label="Seed",
|
82 |
minimum=0,
|
|
|
84 |
step=1,
|
85 |
value=0,
|
86 |
)
|
|
|
87 |
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
|
88 |
|
89 |
with gr.Row():
|
|
|
90 |
width = gr.Slider(
|
91 |
label="Width",
|
92 |
minimum=256,
|
|
|
94 |
step=32,
|
95 |
value=1024,
|
96 |
)
|
|
|
97 |
height = gr.Slider(
|
98 |
label="Height",
|
99 |
minimum=256,
|
|
|
103 |
)
|
104 |
|
105 |
with gr.Row():
|
|
|
106 |
guidance_scale = gr.Slider(
|
107 |
label="Guidance Scale",
|
108 |
minimum=1,
|
|
|
110 |
step=0.1,
|
111 |
value=3.5,
|
112 |
)
|
|
|
113 |
num_inference_steps = gr.Slider(
|
114 |
label="Number of inference steps",
|
115 |
minimum=1,
|
|
|
119 |
)
|
120 |
|
121 |
gr.Examples(
|
122 |
+
examples=examples,
|
123 |
+
fn=infer,
|
124 |
+
inputs=[prompt],
|
125 |
+
outputs=[result, seed],
|
126 |
cache_examples="lazy"
|
127 |
)
|
128 |
|
129 |
+
# History button to display previous images and parameters
|
130 |
+
def show_history():
|
131 |
+
return [(img, f"Prompt: {p}, Seed: {s}, Width: {w}, Height: {h}, Guidance Scale: {g}, Steps: {n}") for img, p, s, w, h, g, n in history]
|
132 |
+
|
133 |
+
history_button = gr.Button("Show History")
|
134 |
+
history_gallery = gr.Gallery(label="History").style(grid=[2, 2], height="auto")
|
135 |
+
|
136 |
+
history_button.click(fn=show_history, inputs=[], outputs=[history_gallery])
|
137 |
+
|
138 |
gr.on(
|
139 |
triggers=[run_button.click, prompt.submit],
|
140 |
+
fn=infer,
|
141 |
+
inputs=[prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
|
142 |
+
outputs=[result, seed]
|
143 |
)
|
144 |
|
145 |
+
demo.launch()
|