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f8d22a5 47a2c66 f8d22a5 ba59b4f f8d22a5 ed877b6 f8d22a5 ed877b6 f8d22a5 ed877b6 f8d22a5 ed877b6 89ea543 ed877b6 c211492 f8d22a5 47a2c66 f8d22a5 47a2c66 f8d22a5 47a2c66 f8d22a5 47a2c66 f8d22a5 47a2c66 ed877b6 89ea543 ed877b6 47a2c66 ed877b6 89ea543 ed877b6 f8d22a5 47a2c66 f8d22a5 c211492 47a2c66 f8d22a5 47a2c66 f8d22a5 47a2c66 f8d22a5 47a2c66 f8d22a5 c401704 f8d22a5 47a2c66 f8d22a5 47a2c66 f8d22a5 47a2c66 f8d22a5 47a2c66 f8d22a5 47a2c66 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 | """Mage-Flow: Efficient Native-Resolution Foundation Model for Image Generation and Editing.
Gradio Space demo with a single unified interface: enter a prompt and optionally
upload an image. If an image is provided, the request is routed to the
Mage-Flow-Edit-Turbo model; otherwise it is routed to the Mage-Flow-Turbo model.
"""
import os
# Use flash_attention_2 for the HF text encoder (flash_attn is installed via wheel)
os.environ.setdefault("VF_HF_ATTN_IMPL", "flash_attention_2")
import textwrap
import spaces # MUST be first (after env setup)
import torch
import gradio as gr
from PIL import Image, ImageDraw, ImageFont
from mage_flow.pipeline import MageFlowPipeline
from mage_flow.models.modules.mage_text import CATEGORY_DISPLAY
T2I_MODEL = "microsoft/Mage-Flow-Turbo"
EDIT_MODEL = "microsoft/Mage-Flow-Edit-Turbo"
pipe_t2i = MageFlowPipeline.from_pretrained(T2I_MODEL, device="cuda")
pipe_edit = MageFlowPipeline.from_pretrained(EDIT_MODEL, device="cuda")
def _block_reason_text(verdict) -> str:
"""Human-readable block reason: '<category> · <explanation>'."""
cat = ", ".join(
CATEGORY_DISPLAY.get(c, c) for c in verdict.categories
) or "policy violation"
reason = (verdict.reason or "").strip()
return f"{cat} · {reason}" if reason else cat
def _blocked_image(reason_text: str, height: int = 1024, width: int = 1024) -> Image.Image:
"""Neutral background image with the safety-filter message drawn on it."""
img = Image.new("RGB", (int(width), int(height)), color=(245, 245, 245))
draw = ImageDraw.Draw(img)
try:
font = ImageFont.load_default(size=28)
except TypeError: # older Pillow: load_default() takes no size
font = ImageFont.load_default()
message = (
"The classifiers included by default in the Microsoft Mage Flow model flagged the following:\n\n" + reason_text
)
# Wrap each paragraph to a column width that fits the image.
max_chars = max(20, int(width / 16))
lines = []
for para in message.split("\n"):
if not para:
lines.append("")
continue
lines.extend(textwrap.wrap(para, width=max_chars))
# Vertically center the text block.
line_h = 38
total_h = line_h * len(lines)
y = max(20, (int(height) - total_h) // 2)
for line in lines:
draw.text((40, y), line, fill=(20, 20, 20), font=font)
y += line_h
return img
@spaces.GPU(duration=60)
def generate(
prompt: str,
image=None,
negative_prompt: str = " ",
steps: int = 4,
cfg: float = 1.0,
height: int = 1024,
width: int = 1024,
max_size: int = 1024,
seed: int = 42,
progress=gr.Progress(track_tqdm=True),
):
"""Generate or edit an image with Mage-Flow.
If ``image`` is provided, the reference image is edited with
Mage-Flow-Edit-Turbo. Otherwise a new image is generated from the text
prompt with Mage-Flow-Turbo.
Args:
prompt: Text description (generation) or edit instruction (editing).
image: Optional reference image. When given, routes to the edit model.
negative_prompt: What to avoid in the result.
steps: Number of denoising steps (Turbo uses 4).
cfg: Classifier-free guidance scale (Turbo uses 1.0).
height: Output image height for text-to-image (multiple of 16).
width: Output image width for text-to-image (multiple of 16).
max_size: Longest side of edited output (0 = keep source resolution).
seed: Random seed for reproducibility.
"""
if not (prompt or "").strip():
raise gr.Error("Prompt is empty.")
if image is not None:
# Route to the edit model when an image is provided.
if isinstance(image, str):
image = Image.open(image)
refs = [image.convert("RGB")]
# Content-safety gate: surface a block to the user instead of failing
# silently (gr.Warning toast + a stamped output image).
verdict = pipe_edit.model.txt_enc.screen_edit(prompt, refs)
if verdict.violates:
reason_text = _block_reason_text(verdict)
gr.Warning("The classifiers included by default in the Microsoft Mage Flow model flagged the following: " + reason_text)
w, h = refs[0].size
return _blocked_image(reason_text, height=h, width=w)
out = pipe_edit.edit(
[prompt],
[refs],
neg_prompts=[negative_prompt or " "],
seeds=[int(seed)],
steps=int(steps),
cfg=float(cfg),
max_size=int(max_size) if max_size else None,
)[0]
return out
# No image: route to the text-to-image model.
# Content-safety gate: surface a block to the user instead of failing
# silently (gr.Warning toast + a stamped output image).
verdict = pipe_t2i.model.txt_enc.screen_text(prompt)
if verdict.violates:
reason_text = _block_reason_text(verdict)
gr.Warning("The classifiers included by default in the Microsoft Mage Flow model flagged the following: " + reason_text)
return _blocked_image(reason_text, height=int(height), width=int(width))
img = pipe_t2i.generate(
[prompt],
neg_prompts=[negative_prompt or " "],
seeds=[int(seed)],
steps=int(steps),
cfg=float(cfg),
heights=[int(height)],
widths=[int(width)],
)[0]
return img
ASSETS_DIR = os.path.join(os.path.dirname(__file__), "mage_flow", "assets")
CSS = """
#col-container { margin: 0 auto; max-width: 1100px; }
.dark .gradio-container { color: var(--body-text-color); }
"""
with gr.Blocks(css=CSS) as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown(
"# Mage-Flow\n"
"Efficient Native-Resolution Foundation Model for Image Generation and Editing. "
"Enter a prompt to generate an image, or upload an image to edit it.\n\n"
"Models: [Mage-Flow-Turbo](https://huggingface.co/microsoft/Mage-Flow-Turbo) & "
"[Mage-Flow-Edit-Turbo](https://huggingface.co/microsoft/Mage-Flow-Edit-Turbo) | "
"[Paper](https://huggingface.co/papers/2607.19064) | "
"[GitHub](https://github.com/microsoft/Mage)"
)
with gr.Row():
with gr.Column(scale=1):
with gr.Row():
prompt = gr.Textbox(
label="Prompt",
show_label=False,
max_lines=3,
placeholder="Describe an image to generate, or an edit instruction for an uploaded image",
container=False,
scale=4,
)
run_btn = gr.Button("Run", variant="primary", scale=1)
with gr.Accordion("Input image (optional — enables editing)", open=True):
image = gr.Image(
type="pil",
label="Input image",
show_label=False,
height=300,
)
with gr.Accordion("Advanced Settings", open=False):
negative_prompt = gr.Textbox(label="Negative prompt", value=" ", lines=1)
with gr.Row():
steps = gr.Slider(1, 50, value=4, step=1, label="Steps")
cfg = gr.Slider(1.0, 10.0, value=1.0, step=0.5, label="CFG")
with gr.Row():
height = gr.Slider(256, 1536, value=1024, step=16, label="Height (text→image)")
width = gr.Slider(256, 1536, value=1024, step=16, label="Width (text→image)")
max_size = gr.Slider(
0, 1536, value=1024, step=16,
label="Max output side for editing (0 = keep source size)",
)
seed = gr.Number(value=42, precision=0, label="Seed")
with gr.Column(scale=1):
result = gr.Image(type="pil", label="Output", height=560)
gr.Markdown("### Text → Image examples")
gr.Examples(
examples=[
["A close-up portrait of an elderly Hausa man with deep wrinkles, wearing a traditional hat, soft natural lighting, ultra realistic."],
["A serene mountain landscape at sunset, with snow-capped peaks reflecting golden light, photorealistic."],
["A cute robot playing a guitar in a neon-lit cyberpunk city, digital art style."],
],
inputs=[prompt],
outputs=result,
fn=generate,
cache_examples=True,
cache_mode="lazy",
)
gr.Markdown("### Image editing examples")
gr.Examples(
examples=[
["change the background to a city street", os.path.join(ASSETS_DIR, "dog.jpg")],
["make it look like a painting", os.path.join(ASSETS_DIR, "cuisine.jpg")],
["add a hat to the person", os.path.join(ASSETS_DIR, "portrait.jpg")],
],
inputs=[prompt, image],
outputs=result,
fn=generate,
cache_examples=True,
cache_mode="lazy",
)
inputs = [prompt, image, negative_prompt, steps, cfg, height, width, max_size, seed]
run_btn.click(lambda: None, None, result).then(
generate, inputs, result, api_name="generate",
)
prompt.submit(lambda: None, None, result).then(
generate, inputs, result, api_name=False,
)
if __name__ == "__main__":
demo.launch(theme=gr.themes.Citrus(), mcp_server=True, show_error=True)
|