Update app.py
Browse files
app.py
CHANGED
@@ -1,11 +1,11 @@
|
|
1 |
# ────────────────────────────────────────────────────────────────────────────
|
2 |
-
# app.py – Text ➜ 2D (FLUX-mini Kontext) ➜ 3D (Hunyuan3D-2)
|
3 |
-
# • Fits into 16 GB system RAM:
|
4 |
-
# •
|
5 |
# ────────────────────────────────────────────────────────────────────────────
|
6 |
import os
|
7 |
import tempfile
|
8 |
-
from typing import List
|
9 |
|
10 |
import gradio as gr
|
11 |
import torch
|
@@ -17,7 +17,7 @@ HF_TOKEN = os.getenv("HF_TOKEN")
|
|
17 |
if not HF_TOKEN:
|
18 |
raise RuntimeError(
|
19 |
"HF_TOKEN이 설정되지 않았습니다. Space Settings → Secrets에서 "
|
20 |
-
"HF_TOKEN
|
21 |
)
|
22 |
login(token=HF_TOKEN, add_to_git_credential=False)
|
23 |
|
@@ -29,46 +29,56 @@ DTYPE = torch.float16 if torch.cuda.is_available() else torch.float32
|
|
29 |
from diffusers import FluxKontextPipeline, FluxPipeline
|
30 |
|
31 |
# Global caches
|
32 |
-
kontext_pipe
|
33 |
-
_text2img_pipe
|
34 |
shape_pipe = None
|
35 |
paint_pipe = None
|
36 |
|
37 |
-
|
38 |
-
|
39 |
-
|
40 |
-
|
41 |
|
|
|
|
|
|
|
42 |
|
43 |
def load_kontext() -> FluxKontextPipeline:
|
|
|
44 |
global kontext_pipe
|
45 |
if kontext_pipe is None:
|
46 |
-
print("[+] Loading FLUX.1-Kontext-
|
47 |
kontext_pipe = FluxKontextPipeline.from_pretrained(
|
48 |
MINI_KONTEXT_REPO,
|
49 |
torch_dtype=DTYPE,
|
50 |
device_map=DEVICE_MAP_STRATEGY,
|
51 |
low_cpu_mem_usage=True,
|
|
|
|
|
52 |
)
|
53 |
kontext_pipe.set_progress_bar_config(disable=True)
|
54 |
return kontext_pipe
|
55 |
|
56 |
|
57 |
def load_text2img() -> FluxPipeline:
|
|
|
58 |
global _text2img_pipe
|
59 |
if _text2img_pipe is None:
|
60 |
-
print("[+] Loading FLUX.1-
|
61 |
_text2img_pipe = FluxPipeline.from_pretrained(
|
62 |
MINI_T2I_REPO,
|
63 |
torch_dtype=DTYPE,
|
64 |
device_map=DEVICE_MAP_STRATEGY,
|
65 |
low_cpu_mem_usage=True,
|
|
|
|
|
66 |
)
|
67 |
_text2img_pipe.set_progress_bar_config(disable=True)
|
68 |
return _text2img_pipe
|
69 |
|
70 |
|
71 |
-
def load_hunyuan()
|
|
|
72 |
global shape_pipe, paint_pipe
|
73 |
if shape_pipe is None or paint_pipe is None:
|
74 |
print("[+] Loading Hunyuan3D-2 (shape & texture)…")
|
@@ -80,6 +90,8 @@ def load_hunyuan() -> tuple:
|
|
80 |
torch_dtype=DTYPE,
|
81 |
device_map=DEVICE_MAP_STRATEGY,
|
82 |
low_cpu_mem_usage=True,
|
|
|
|
|
83 |
)
|
84 |
shape_pipe.set_progress_bar_config(disable=True)
|
85 |
|
@@ -88,40 +100,42 @@ def load_hunyuan() -> tuple:
|
|
88 |
torch_dtype=DTYPE,
|
89 |
device_map=DEVICE_MAP_STRATEGY,
|
90 |
low_cpu_mem_usage=True,
|
|
|
|
|
91 |
)
|
92 |
paint_pipe.set_progress_bar_config(disable=True)
|
93 |
return shape_pipe, paint_pipe
|
94 |
|
95 |
-
#
|
96 |
-
# Helper functions
|
97 |
-
# ──────────────────��────────────────────────────
|
98 |
|
99 |
def generate_single_2d(prompt: str, image: Image.Image | None, guidance_scale: float) -> Image.Image:
|
100 |
-
|
101 |
if image is None:
|
102 |
t2i = load_text2img()
|
103 |
-
|
104 |
-
|
105 |
-
|
106 |
-
return
|
107 |
|
108 |
|
109 |
def generate_multiview(prompt: str, base_image: Image.Image, guidance_scale: float) -> List[Image.Image]:
|
|
|
110 |
kontext = load_kontext()
|
111 |
-
|
112 |
base_image,
|
113 |
kontext(image=base_image, prompt=f"{prompt}, left side view", guidance_scale=guidance_scale).images[0],
|
114 |
kontext(image=base_image, prompt=f"{prompt}, right side view", guidance_scale=guidance_scale).images[0],
|
115 |
kontext(image=base_image, prompt=f"{prompt}, back view", guidance_scale=guidance_scale).images[0],
|
116 |
]
|
117 |
-
return views
|
118 |
|
119 |
|
120 |
def build_3d_mesh(prompt: str, images: List[Image.Image]) -> str:
|
|
|
121 |
shape, paint = load_hunyuan()
|
122 |
-
|
123 |
-
|
124 |
-
mesh =
|
|
|
125 |
|
126 |
tmpdir = tempfile.mkdtemp()
|
127 |
out_path = os.path.join(tmpdir, "mesh.glb")
|
@@ -146,7 +160,7 @@ def workflow(prompt: str, input_image: Image.Image | None, multiview: bool, guid
|
|
146 |
def build_ui():
|
147 |
with gr.Blocks(css=CSS, title="Text ➜ 2D ➜ 3D (mini)") as demo:
|
148 |
gr.Markdown("# 🌀 텍스트 → 2D → 3D 생성기 (경량 버전)")
|
149 |
-
gr.Markdown("Kontext-
|
150 |
|
151 |
with gr.Row():
|
152 |
with gr.Column():
|
|
|
1 |
# ────────────────────────────────────────────────────────────────────────────
|
2 |
+
# app.py – Text ➜ 2D (FLUX-mini Kontext-dev) ➜ 3D (Hunyuan3D-2)
|
3 |
+
# • Fits into ≈16 GB system RAM: lightweight models + lazy loading + offload
|
4 |
+
# • 2025-07-07: fixed repo names, added HF token + trust_remote_code, cleaned logs
|
5 |
# ────────────────────────────────────────────────────────────────────────────
|
6 |
import os
|
7 |
import tempfile
|
8 |
+
from typing import List
|
9 |
|
10 |
import gradio as gr
|
11 |
import torch
|
|
|
17 |
if not HF_TOKEN:
|
18 |
raise RuntimeError(
|
19 |
"HF_TOKEN이 설정되지 않았습니다. Space Settings → Secrets에서 "
|
20 |
+
"HF_TOKEN=<your_read_token> 을 등록한 뒤 재시작하세요."
|
21 |
)
|
22 |
login(token=HF_TOKEN, add_to_git_credential=False)
|
23 |
|
|
|
29 |
from diffusers import FluxKontextPipeline, FluxPipeline
|
30 |
|
31 |
# Global caches
|
32 |
+
kontext_pipe: FluxKontextPipeline | None = None
|
33 |
+
_text2img_pipe: FluxPipeline | None = None
|
34 |
shape_pipe = None
|
35 |
paint_pipe = None
|
36 |
|
37 |
+
# Repository names (공개 버전)
|
38 |
+
MINI_KONTEXT_REPO = "black-forest-labs/FLUX.1-Kontext-dev" # 이미지 편집/확장용
|
39 |
+
MINI_T2I_REPO = "black-forest-labs/FLUX.1-schnell" # 텍스트→이미지(4-step distilled)
|
40 |
+
HUNYUAN_REPO = "tencent/Hunyuan3D-2" # 3D shape & paint
|
41 |
|
42 |
+
DEVICE_MAP_STRATEGY = "balanced" # "auto"(offload) 미지원, so use "balanced"
|
43 |
+
|
44 |
+
# ──────────────────────────── Loaders ────────────────────────────
|
45 |
|
46 |
def load_kontext() -> FluxKontextPipeline:
|
47 |
+
"""Lazy-load FLUX.1-Kontext-dev (image-to-image editing)."""
|
48 |
global kontext_pipe
|
49 |
if kontext_pipe is None:
|
50 |
+
print("[+] Loading FLUX.1-Kontext-dev … (balanced offload)")
|
51 |
kontext_pipe = FluxKontextPipeline.from_pretrained(
|
52 |
MINI_KONTEXT_REPO,
|
53 |
torch_dtype=DTYPE,
|
54 |
device_map=DEVICE_MAP_STRATEGY,
|
55 |
low_cpu_mem_usage=True,
|
56 |
+
token=HF_TOKEN,
|
57 |
+
trust_remote_code=True,
|
58 |
)
|
59 |
kontext_pipe.set_progress_bar_config(disable=True)
|
60 |
return kontext_pipe
|
61 |
|
62 |
|
63 |
def load_text2img() -> FluxPipeline:
|
64 |
+
"""Lazy-load FLUX.1-schnell (text-to-image)."""
|
65 |
global _text2img_pipe
|
66 |
if _text2img_pipe is None:
|
67 |
+
print("[+] Loading FLUX.1-schnell (text→image)…")
|
68 |
_text2img_pipe = FluxPipeline.from_pretrained(
|
69 |
MINI_T2I_REPO,
|
70 |
torch_dtype=DTYPE,
|
71 |
device_map=DEVICE_MAP_STRATEGY,
|
72 |
low_cpu_mem_usage=True,
|
73 |
+
token=HF_TOKEN,
|
74 |
+
trust_remote_code=True,
|
75 |
)
|
76 |
_text2img_pipe.set_progress_bar_config(disable=True)
|
77 |
return _text2img_pipe
|
78 |
|
79 |
|
80 |
+
def load_hunyuan():
|
81 |
+
"""Lazy-load Hunyuan3D-2 shape & texture pipelines."""
|
82 |
global shape_pipe, paint_pipe
|
83 |
if shape_pipe is None or paint_pipe is None:
|
84 |
print("[+] Loading Hunyuan3D-2 (shape & texture)…")
|
|
|
90 |
torch_dtype=DTYPE,
|
91 |
device_map=DEVICE_MAP_STRATEGY,
|
92 |
low_cpu_mem_usage=True,
|
93 |
+
token=HF_TOKEN,
|
94 |
+
trust_remote_code=True,
|
95 |
)
|
96 |
shape_pipe.set_progress_bar_config(disable=True)
|
97 |
|
|
|
100 |
torch_dtype=DTYPE,
|
101 |
device_map=DEVICE_MAP_STRATEGY,
|
102 |
low_cpu_mem_usage=True,
|
103 |
+
token=HF_TOKEN,
|
104 |
+
trust_remote_code=True,
|
105 |
)
|
106 |
paint_pipe.set_progress_bar_config(disable=True)
|
107 |
return shape_pipe, paint_pipe
|
108 |
|
109 |
+
# ───────────────────────────── Helpers ─────────────────────────────
|
|
|
|
|
110 |
|
111 |
def generate_single_2d(prompt: str, image: Image.Image | None, guidance_scale: float) -> Image.Image:
|
112 |
+
"""Generate a single 2D image (txt2img or img2img)."""
|
113 |
if image is None:
|
114 |
t2i = load_text2img()
|
115 |
+
return t2i(prompt=prompt, guidance_scale=guidance_scale).images[0]
|
116 |
+
|
117 |
+
kontext = load_kontext()
|
118 |
+
return kontext(image=image, prompt=prompt, guidance_scale=guidance_scale).images[0]
|
119 |
|
120 |
|
121 |
def generate_multiview(prompt: str, base_image: Image.Image, guidance_scale: float) -> List[Image.Image]:
|
122 |
+
"""Generate 4-view images for better 3D reconstruction."""
|
123 |
kontext = load_kontext()
|
124 |
+
return [
|
125 |
base_image,
|
126 |
kontext(image=base_image, prompt=f"{prompt}, left side view", guidance_scale=guidance_scale).images[0],
|
127 |
kontext(image=base_image, prompt=f"{prompt}, right side view", guidance_scale=guidance_scale).images[0],
|
128 |
kontext(image=base_image, prompt=f"{prompt}, back view", guidance_scale=guidance_scale).images[0],
|
129 |
]
|
|
|
130 |
|
131 |
|
132 |
def build_3d_mesh(prompt: str, images: List[Image.Image]) -> str:
|
133 |
+
"""Create GLB mesh from single or multi-view images."""
|
134 |
shape, paint = load_hunyuan()
|
135 |
+
source = images if len(images) > 1 else images[0]
|
136 |
+
|
137 |
+
mesh = shape(image=source, prompt=prompt)[0]
|
138 |
+
mesh = paint(mesh, image=source) # texture painting
|
139 |
|
140 |
tmpdir = tempfile.mkdtemp()
|
141 |
out_path = os.path.join(tmpdir, "mesh.glb")
|
|
|
160 |
def build_ui():
|
161 |
with gr.Blocks(css=CSS, title="Text ➜ 2D ➜ 3D (mini)") as demo:
|
162 |
gr.Markdown("# 🌀 텍스트 → 2D → 3D 생성기 (경량 버전)")
|
163 |
+
gr.Markdown("Kontext-dev + Hunyuan3D-2. 16 GB RAM에서도 동작합니다.")
|
164 |
|
165 |
with gr.Row():
|
166 |
with gr.Column():
|