Spaces:
Running
on
Zero
Running
on
Zero
polu
commited on
Commit
•
f9aa991
1
Parent(s):
1626723
init
Browse files
app.py
ADDED
@@ -0,0 +1,109 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import spaces
|
2 |
+
import argparse
|
3 |
+
import os
|
4 |
+
import time
|
5 |
+
from os import path
|
6 |
+
from safetensors.torch import load_file
|
7 |
+
from huggingface_hub import hf_hub_download
|
8 |
+
|
9 |
+
cache_path = path.join(path.dirname(path.abspath(__file__)), "models")
|
10 |
+
os.environ["TRANSFORMERS_CACHE"] = cache_path
|
11 |
+
os.environ["HF_HUB_CACHE"] = cache_path
|
12 |
+
os.environ["HF_HOME"] = cache_path
|
13 |
+
|
14 |
+
import gradio as gr
|
15 |
+
import torch
|
16 |
+
from diffusers import FluxPipeline
|
17 |
+
|
18 |
+
torch.backends.cuda.matmul.allow_tf32 = True
|
19 |
+
|
20 |
+
class timer:
|
21 |
+
def __init__(self, method_name="timed process"):
|
22 |
+
self.method = method_name
|
23 |
+
def __enter__(self):
|
24 |
+
self.start = time.time()
|
25 |
+
print(f"{self.method} starts")
|
26 |
+
def __exit__(self, exc_type, exc_val, exc_tb):
|
27 |
+
end = time.time()
|
28 |
+
print(f"{self.method} took {str(round(end - self.start, 2))}s")
|
29 |
+
|
30 |
+
if not path.exists(cache_path):
|
31 |
+
os.makedirs(cache_path, exist_ok=True)
|
32 |
+
|
33 |
+
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
|
34 |
+
pipe.load_lora_weights(hf_hub_download("ByteDance/Hyper-SD", "Hyper-FLUX.1-dev-8steps-lora.safetensors"))
|
35 |
+
pipe.fuse_lora(lora_scale=0.125)
|
36 |
+
pipe.to(device="cuda", dtype=torch.bfloat16)
|
37 |
+
|
38 |
+
with gr.Blocks(theme=gr.themes.Soft()) as demo:
|
39 |
+
gr.Markdown(
|
40 |
+
"""
|
41 |
+
<div style="text-align: center; max-width: 650px; margin: 0 auto;">
|
42 |
+
<h1 style="font-size: 2.5rem; font-weight: 700; margin-bottom: 1rem; display: contents;">Hyper-FLUX-8steps-LoRA</h1>
|
43 |
+
<p style="font-size: 1rem; margin-bottom: 1.5rem;">AutoML team from ByteDance</p>
|
44 |
+
</div>
|
45 |
+
"""
|
46 |
+
)
|
47 |
+
|
48 |
+
with gr.Row():
|
49 |
+
with gr.Column(scale=3):
|
50 |
+
with gr.Group():
|
51 |
+
prompt = gr.Textbox(
|
52 |
+
label="Your Image Description",
|
53 |
+
placeholder="E.g., A serene landscape with mountains and a lake at sunset",
|
54 |
+
lines=3
|
55 |
+
)
|
56 |
+
|
57 |
+
with gr.Accordion("Advanced Settings", open=False):
|
58 |
+
with gr.Group():
|
59 |
+
with gr.Row():
|
60 |
+
height = gr.Slider(label="Height", minimum=256, maximum=1152, step=64, value=1024)
|
61 |
+
width = gr.Slider(label="Width", minimum=256, maximum=1152, step=64, value=1024)
|
62 |
+
|
63 |
+
with gr.Row():
|
64 |
+
steps = gr.Slider(label="Inference Steps", minimum=6, maximum=25, step=1, value=8)
|
65 |
+
scales = gr.Slider(label="Guidance Scale", minimum=0.0, maximum=5.0, step=0.1, value=3.5)
|
66 |
+
|
67 |
+
seed = gr.Number(label="Seed (for reproducibility)", value=3413, precision=0)
|
68 |
+
|
69 |
+
generate_btn = gr.Button("Generate Image", variant="primary", scale=1)
|
70 |
+
|
71 |
+
with gr.Column(scale=4):
|
72 |
+
output = gr.Image(label="Your Generated Image")
|
73 |
+
|
74 |
+
gr.Markdown(
|
75 |
+
"""
|
76 |
+
<div style="max-width: 650px; margin: 2rem auto; padding: 1rem; border-radius: 10px; background-color: #f0f0f0;">
|
77 |
+
<h2 style="font-size: 1.5rem; margin-bottom: 1rem;">How to Use</h2>
|
78 |
+
<ol style="padding-left: 1.5rem;">
|
79 |
+
<li>Enter a detailed description of the image you want to create.</li>
|
80 |
+
<li>Adjust advanced settings if desired (tap to expand).</li>
|
81 |
+
<li>Tap "Generate Image" and wait for your creation!</li>
|
82 |
+
</ol>
|
83 |
+
<p style="margin-top: 1rem; font-style: italic;">Tip: Be specific in your description for best results!</p>
|
84 |
+
</div>
|
85 |
+
"""
|
86 |
+
)
|
87 |
+
|
88 |
+
@spaces.GPU
|
89 |
+
def process_image(height, width, steps, scales, prompt, seed):
|
90 |
+
global pipe
|
91 |
+
with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16), timer("inference"):
|
92 |
+
return pipe(
|
93 |
+
prompt=[prompt],
|
94 |
+
generator=torch.Generator().manual_seed(int(seed)),
|
95 |
+
num_inference_steps=int(steps),
|
96 |
+
guidance_scale=float(scales),
|
97 |
+
height=int(height),
|
98 |
+
width=int(width),
|
99 |
+
max_sequence_length=256
|
100 |
+
).images[0]
|
101 |
+
|
102 |
+
generate_btn.click(
|
103 |
+
process_image,
|
104 |
+
inputs=[height, width, steps, scales, prompt, seed],
|
105 |
+
outputs=output
|
106 |
+
)
|
107 |
+
|
108 |
+
if __name__ == "__main__":
|
109 |
+
demo.launch()
|