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Create app-backup.py
Browse files- app-backup.py +956 -0
app-backup.py
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1 |
+
import tempfile
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2 |
+
import time
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3 |
+
from collections.abc import Sequence
|
4 |
+
from typing import Any, cast
|
5 |
+
import os
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6 |
+
from huggingface_hub import login, hf_hub_download
|
7 |
+
|
8 |
+
import gradio as gr
|
9 |
+
import numpy as np
|
10 |
+
import pillow_heif
|
11 |
+
import spaces
|
12 |
+
import torch
|
13 |
+
from gradio_image_annotation import image_annotator
|
14 |
+
from gradio_imageslider import ImageSlider
|
15 |
+
from PIL import Image
|
16 |
+
from pymatting.foreground.estimate_foreground_ml import estimate_foreground_ml
|
17 |
+
from refiners.fluxion.utils import no_grad
|
18 |
+
from refiners.solutions import BoxSegmenter
|
19 |
+
from transformers import GroundingDinoForObjectDetection, GroundingDinoProcessor
|
20 |
+
from diffusers import FluxPipeline
|
21 |
+
from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
|
22 |
+
import gc
|
23 |
+
|
24 |
+
from PIL import Image, ImageDraw, ImageFont
|
25 |
+
from PIL import Image
|
26 |
+
from gradio_client import Client, handle_file
|
27 |
+
import uuid
|
28 |
+
|
29 |
+
|
30 |
+
def clear_memory():
|
31 |
+
"""메모리 정리 함수"""
|
32 |
+
gc.collect()
|
33 |
+
try:
|
34 |
+
if torch.cuda.is_available():
|
35 |
+
with torch.cuda.device(0): # 명시적으로 device 0 사용
|
36 |
+
torch.cuda.empty_cache()
|
37 |
+
except:
|
38 |
+
pass
|
39 |
+
|
40 |
+
# GPU 설정
|
41 |
+
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") # 명시적으로 cuda:0 지정
|
42 |
+
|
43 |
+
# GPU 설정을 try-except로 감싸기
|
44 |
+
if torch.cuda.is_available():
|
45 |
+
try:
|
46 |
+
with torch.cuda.device(0):
|
47 |
+
torch.cuda.empty_cache()
|
48 |
+
torch.backends.cudnn.benchmark = True
|
49 |
+
torch.backends.cuda.matmul.allow_tf32 = True
|
50 |
+
except:
|
51 |
+
print("Warning: Could not configure CUDA settings")
|
52 |
+
|
53 |
+
# 번역 모델 초기화
|
54 |
+
model_name = "Helsinki-NLP/opus-mt-ko-en"
|
55 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
56 |
+
model = AutoModelForSeq2SeqLM.from_pretrained(model_name).to('cpu')
|
57 |
+
translator = pipeline("translation", model=model, tokenizer=tokenizer, device=-1)
|
58 |
+
|
59 |
+
def translate_to_english(text: str) -> str:
|
60 |
+
"""한글 텍스트를 영어로 번역"""
|
61 |
+
try:
|
62 |
+
if any(ord('가') <= ord(char) <= ord('힣') for char in text):
|
63 |
+
translated = translator(text, max_length=128)[0]['translation_text']
|
64 |
+
print(f"Translated '{text}' to '{translated}'")
|
65 |
+
return translated
|
66 |
+
return text
|
67 |
+
except Exception as e:
|
68 |
+
print(f"Translation error: {str(e)}")
|
69 |
+
return text
|
70 |
+
|
71 |
+
BoundingBox = tuple[int, int, int, int]
|
72 |
+
|
73 |
+
pillow_heif.register_heif_opener()
|
74 |
+
pillow_heif.register_avif_opener()
|
75 |
+
|
76 |
+
# HF 토큰 설정
|
77 |
+
HF_TOKEN = os.getenv("HF_TOKEN")
|
78 |
+
if HF_TOKEN is None:
|
79 |
+
raise ValueError("Please set the HF_TOKEN environment variable")
|
80 |
+
|
81 |
+
try:
|
82 |
+
login(token=HF_TOKEN)
|
83 |
+
except Exception as e:
|
84 |
+
raise ValueError(f"Failed to login to Hugging Face: {str(e)}")
|
85 |
+
|
86 |
+
# 모델 초기화
|
87 |
+
segmenter = BoxSegmenter(device="cpu")
|
88 |
+
segmenter.device = device
|
89 |
+
segmenter.model = segmenter.model.to(device=segmenter.device)
|
90 |
+
|
91 |
+
gd_model_path = "IDEA-Research/grounding-dino-base"
|
92 |
+
gd_processor = GroundingDinoProcessor.from_pretrained(gd_model_path)
|
93 |
+
gd_model = GroundingDinoForObjectDetection.from_pretrained(gd_model_path, torch_dtype=torch.float32)
|
94 |
+
gd_model = gd_model.to(device=device)
|
95 |
+
assert isinstance(gd_model, GroundingDinoForObjectDetection)
|
96 |
+
|
97 |
+
# FLUX 파이프라인 초기화
|
98 |
+
pipe = FluxPipeline.from_pretrained(
|
99 |
+
"black-forest-labs/FLUX.1-dev",
|
100 |
+
torch_dtype=torch.float16,
|
101 |
+
use_auth_token=HF_TOKEN
|
102 |
+
)
|
103 |
+
pipe.enable_attention_slicing(slice_size="auto")
|
104 |
+
|
105 |
+
# LoRA 가중치 로드
|
106 |
+
pipe.load_lora_weights(
|
107 |
+
hf_hub_download(
|
108 |
+
"ByteDance/Hyper-SD",
|
109 |
+
"Hyper-FLUX.1-dev-8steps-lora.safetensors",
|
110 |
+
use_auth_token=HF_TOKEN
|
111 |
+
)
|
112 |
+
)
|
113 |
+
pipe.fuse_lora(lora_scale=0.125)
|
114 |
+
|
115 |
+
# GPU 설정을 try-except로 감싸기
|
116 |
+
try:
|
117 |
+
if torch.cuda.is_available():
|
118 |
+
pipe = pipe.to("cuda:0") # 명시적으로 cuda:0 지정
|
119 |
+
except Exception as e:
|
120 |
+
print(f"Warning: Could not move pipeline to CUDA: {str(e)}")
|
121 |
+
|
122 |
+
client = Client("NabeelShar/BiRefNet_for_text_writing")
|
123 |
+
|
124 |
+
class timer:
|
125 |
+
def __init__(self, method_name="timed process"):
|
126 |
+
self.method = method_name
|
127 |
+
def __enter__(self):
|
128 |
+
self.start = time.time()
|
129 |
+
print(f"{self.method} starts")
|
130 |
+
def __exit__(self, exc_type, exc_val, exc_tb):
|
131 |
+
end = time.time()
|
132 |
+
print(f"{self.method} took {str(round(end - self.start, 2))}s")
|
133 |
+
|
134 |
+
def bbox_union(bboxes: Sequence[list[int]]) -> BoundingBox | None:
|
135 |
+
if not bboxes:
|
136 |
+
return None
|
137 |
+
for bbox in bboxes:
|
138 |
+
assert len(bbox) == 4
|
139 |
+
assert all(isinstance(x, int) for x in bbox)
|
140 |
+
return (
|
141 |
+
min(bbox[0] for bbox in bboxes),
|
142 |
+
min(bbox[1] for bbox in bboxes),
|
143 |
+
max(bbox[2] for bbox in bboxes),
|
144 |
+
max(bbox[3] for bbox in bboxes),
|
145 |
+
)
|
146 |
+
|
147 |
+
def corners_to_pixels_format(bboxes: torch.Tensor, width: int, height: int) -> torch.Tensor:
|
148 |
+
x1, y1, x2, y2 = bboxes.round().to(torch.int32).unbind(-1)
|
149 |
+
return torch.stack((x1.clamp_(0, width), y1.clamp_(0, height), x2.clamp_(0, width), y2.clamp_(0, height)), dim=-1)
|
150 |
+
|
151 |
+
def gd_detect(img: Image.Image, prompt: str) -> BoundingBox | None:
|
152 |
+
inputs = gd_processor(images=img, text=f"{prompt}.", return_tensors="pt").to(device=device)
|
153 |
+
with no_grad():
|
154 |
+
outputs = gd_model(**inputs)
|
155 |
+
width, height = img.size
|
156 |
+
results: dict[str, Any] = gd_processor.post_process_grounded_object_detection(
|
157 |
+
outputs,
|
158 |
+
inputs["input_ids"],
|
159 |
+
target_sizes=[(height, width)],
|
160 |
+
)[0]
|
161 |
+
assert "boxes" in results and isinstance(results["boxes"], torch.Tensor)
|
162 |
+
bboxes = corners_to_pixels_format(results["boxes"].cpu(), width, height)
|
163 |
+
return bbox_union(bboxes.numpy().tolist())
|
164 |
+
|
165 |
+
def apply_mask(img: Image.Image, mask_img: Image.Image, defringe: bool = True) -> Image.Image:
|
166 |
+
assert img.size == mask_img.size
|
167 |
+
img = img.convert("RGB")
|
168 |
+
mask_img = mask_img.convert("L")
|
169 |
+
if defringe:
|
170 |
+
rgb, alpha = np.asarray(img) / 255.0, np.asarray(mask_img) / 255.0
|
171 |
+
foreground = cast(np.ndarray[Any, np.dtype[np.uint8]], estimate_foreground_ml(rgb, alpha))
|
172 |
+
img = Image.fromarray((foreground * 255).astype("uint8"))
|
173 |
+
result = Image.new("RGBA", img.size)
|
174 |
+
result.paste(img, (0, 0), mask_img)
|
175 |
+
return result
|
176 |
+
|
177 |
+
|
178 |
+
def adjust_size_to_multiple_of_8(width: int, height: int) -> tuple[int, int]:
|
179 |
+
"""이미지 크기를 8의 배수로 조정하는 함수"""
|
180 |
+
new_width = ((width + 7) // 8) * 8
|
181 |
+
new_height = ((height + 7) // 8) * 8
|
182 |
+
return new_width, new_height
|
183 |
+
|
184 |
+
def calculate_dimensions(aspect_ratio: str, base_size: int = 512) -> tuple[int, int]:
|
185 |
+
"""선택된 비율에 따라 이미지 크기 계산"""
|
186 |
+
if aspect_ratio == "1:1":
|
187 |
+
return base_size, base_size
|
188 |
+
elif aspect_ratio == "16:9":
|
189 |
+
return base_size * 16 // 9, base_size
|
190 |
+
elif aspect_ratio == "9:16":
|
191 |
+
return base_size, base_size * 16 // 9
|
192 |
+
elif aspect_ratio == "4:3":
|
193 |
+
return base_size * 4 // 3, base_size
|
194 |
+
return base_size, base_size
|
195 |
+
|
196 |
+
@spaces.GPU(duration=20) # 40초에서 20초로 감소
|
197 |
+
def generate_background(prompt: str, aspect_ratio: str) -> Image.Image:
|
198 |
+
try:
|
199 |
+
width, height = calculate_dimensions(aspect_ratio)
|
200 |
+
width, height = adjust_size_to_multiple_of_8(width, height)
|
201 |
+
|
202 |
+
max_size = 768
|
203 |
+
if width > max_size or height > max_size:
|
204 |
+
ratio = max_size / max(width, height)
|
205 |
+
width = int(width * ratio)
|
206 |
+
height = int(height * ratio)
|
207 |
+
width, height = adjust_size_to_multiple_of_8(width, height)
|
208 |
+
|
209 |
+
with timer("Background generation"):
|
210 |
+
try:
|
211 |
+
with torch.inference_mode():
|
212 |
+
image = pipe(
|
213 |
+
prompt=prompt,
|
214 |
+
width=width,
|
215 |
+
height=height,
|
216 |
+
num_inference_steps=8,
|
217 |
+
guidance_scale=4.0
|
218 |
+
).images[0]
|
219 |
+
except Exception as e:
|
220 |
+
print(f"Pipeline error: {str(e)}")
|
221 |
+
return Image.new('RGB', (width, height), 'white')
|
222 |
+
|
223 |
+
return image
|
224 |
+
except Exception as e:
|
225 |
+
print(f"Background generation error: {str(e)}")
|
226 |
+
return Image.new('RGB', (512, 512), 'white')
|
227 |
+
|
228 |
+
def create_position_grid():
|
229 |
+
return """
|
230 |
+
<div class="position-grid" style="display: grid; grid-template-columns: repeat(3, 1fr); gap: 10px; width: 150px; margin: auto;">
|
231 |
+
<button class="position-btn" data-pos="top-left">↖</button>
|
232 |
+
<button class="position-btn" data-pos="top-center">↑</button>
|
233 |
+
<button class="position-btn" data-pos="top-right">↗</button>
|
234 |
+
<button class="position-btn" data-pos="middle-left">←</button>
|
235 |
+
<button class="position-btn" data-pos="middle-center">•</button>
|
236 |
+
<button class="position-btn" data-pos="middle-right">→</button>
|
237 |
+
<button class="position-btn" data-pos="bottom-left">↙</button>
|
238 |
+
<button class="position-btn" data-pos="bottom-center" data-default="true">↓</button>
|
239 |
+
<button class="position-btn" data-pos="bottom-right">↘</button>
|
240 |
+
</div>
|
241 |
+
"""
|
242 |
+
|
243 |
+
def calculate_object_position(position: str, bg_size: tuple[int, int], obj_size: tuple[int, int]) -> tuple[int, int]:
|
244 |
+
"""오브젝트의 위치 계산"""
|
245 |
+
bg_width, bg_height = bg_size
|
246 |
+
obj_width, obj_height = obj_size
|
247 |
+
|
248 |
+
positions = {
|
249 |
+
"top-left": (0, 0),
|
250 |
+
"top-center": ((bg_width - obj_width) // 2, 0),
|
251 |
+
"top-right": (bg_width - obj_width, 0),
|
252 |
+
"middle-left": (0, (bg_height - obj_height) // 2),
|
253 |
+
"middle-center": ((bg_width - obj_width) // 2, (bg_height - obj_height) // 2),
|
254 |
+
"middle-right": (bg_width - obj_width, (bg_height - obj_height) // 2),
|
255 |
+
"bottom-left": (0, bg_height - obj_height),
|
256 |
+
"bottom-center": ((bg_width - obj_width) // 2, bg_height - obj_height),
|
257 |
+
"bottom-right": (bg_width - obj_width, bg_height - obj_height)
|
258 |
+
}
|
259 |
+
|
260 |
+
return positions.get(position, positions["bottom-center"])
|
261 |
+
|
262 |
+
def resize_object(image: Image.Image, scale_percent: float) -> Image.Image:
|
263 |
+
"""오브젝트 크기 조정"""
|
264 |
+
width = int(image.width * scale_percent / 100)
|
265 |
+
height = int(image.height * scale_percent / 100)
|
266 |
+
return image.resize((width, height), Image.Resampling.LANCZOS)
|
267 |
+
|
268 |
+
def combine_with_background(foreground: Image.Image, background: Image.Image,
|
269 |
+
position: str = "bottom-center", scale_percent: float = 100) -> Image.Image:
|
270 |
+
"""전경과 배경 합성 함수"""
|
271 |
+
print(f"Combining with position: {position}, scale: {scale_percent}")
|
272 |
+
|
273 |
+
result = background.convert('RGBA')
|
274 |
+
scaled_foreground = resize_object(foreground, scale_percent)
|
275 |
+
|
276 |
+
x, y = calculate_object_position(position, result.size, scaled_foreground.size)
|
277 |
+
print(f"Calculated position coordinates: ({x}, {y})")
|
278 |
+
|
279 |
+
result.paste(scaled_foreground, (x, y), scaled_foreground)
|
280 |
+
return result
|
281 |
+
|
282 |
+
@spaces.GPU(duration=30) # 120초에서 30초로 감소
|
283 |
+
def _gpu_process(img: Image.Image, prompt: str | BoundingBox | None) -> tuple[Image.Image, BoundingBox | None, list[str]]:
|
284 |
+
time_log: list[str] = []
|
285 |
+
try:
|
286 |
+
if isinstance(prompt, str):
|
287 |
+
t0 = time.time()
|
288 |
+
bbox = gd_detect(img, prompt)
|
289 |
+
time_log.append(f"detect: {time.time() - t0}")
|
290 |
+
if not bbox:
|
291 |
+
print(time_log[0])
|
292 |
+
raise gr.Error("No object detected")
|
293 |
+
else:
|
294 |
+
bbox = prompt
|
295 |
+
t0 = time.time()
|
296 |
+
mask = segmenter(img, bbox)
|
297 |
+
time_log.append(f"segment: {time.time() - t0}")
|
298 |
+
return mask, bbox, time_log
|
299 |
+
except Exception as e:
|
300 |
+
print(f"GPU process error: {str(e)}")
|
301 |
+
raise
|
302 |
+
|
303 |
+
def _process(img: Image.Image, prompt: str | BoundingBox | None, bg_prompt: str | None = None, aspect_ratio: str = "1:1") -> tuple[tuple[Image.Image, Image.Image, Image.Image], gr.DownloadButton]:
|
304 |
+
try:
|
305 |
+
# 입력 이미지 크기 제한
|
306 |
+
max_size = 1024
|
307 |
+
if img.width > max_size or img.height > max_size:
|
308 |
+
ratio = max_size / max(img.width, img.height)
|
309 |
+
new_size = (int(img.width * ratio), int(img.height * ratio))
|
310 |
+
img = img.resize(new_size, Image.LANCZOS)
|
311 |
+
|
312 |
+
# CUDA 메모리 관리 수정
|
313 |
+
try:
|
314 |
+
if torch.cuda.is_available():
|
315 |
+
current_device = torch.cuda.current_device()
|
316 |
+
with torch.cuda.device(current_device):
|
317 |
+
torch.cuda.empty_cache()
|
318 |
+
except Exception as e:
|
319 |
+
print(f"CUDA memory management failed: {e}")
|
320 |
+
|
321 |
+
with torch.cuda.amp.autocast(enabled=torch.cuda.is_available()):
|
322 |
+
mask, bbox, time_log = _gpu_process(img, prompt)
|
323 |
+
masked_alpha = apply_mask(img, mask, defringe=True)
|
324 |
+
|
325 |
+
if bg_prompt:
|
326 |
+
background = generate_background(bg_prompt, aspect_ratio)
|
327 |
+
combined = background
|
328 |
+
else:
|
329 |
+
combined = Image.alpha_composite(Image.new("RGBA", masked_alpha.size, "white"), masked_alpha)
|
330 |
+
|
331 |
+
clear_memory()
|
332 |
+
|
333 |
+
with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp:
|
334 |
+
combined.save(temp.name)
|
335 |
+
return (img, combined, masked_alpha), gr.DownloadButton(value=temp.name, interactive=True)
|
336 |
+
except Exception as e:
|
337 |
+
clear_memory()
|
338 |
+
print(f"Processing error: {str(e)}")
|
339 |
+
raise gr.Error(f"Processing failed: {str(e)}")
|
340 |
+
|
341 |
+
def on_change_bbox(prompts: dict[str, Any] | None):
|
342 |
+
return gr.update(interactive=prompts is not None)
|
343 |
+
|
344 |
+
|
345 |
+
def on_change_prompt(img: Image.Image | None, prompt: str | None, bg_prompt: str | None = None):
|
346 |
+
return gr.update(interactive=bool(img and prompt))
|
347 |
+
|
348 |
+
|
349 |
+
def process_prompt(img: Image.Image, prompt: str, bg_prompt: str | None = None,
|
350 |
+
aspect_ratio: str = "1:1", position: str = "bottom-center",
|
351 |
+
scale_percent: float = 100) -> tuple[Image.Image, Image.Image]:
|
352 |
+
try:
|
353 |
+
if img is None or prompt.strip() == "":
|
354 |
+
raise gr.Error("Please provide both image and prompt")
|
355 |
+
|
356 |
+
print(f"Processing with position: {position}, scale: {scale_percent}") # 디버깅용
|
357 |
+
|
358 |
+
try:
|
359 |
+
prompt = translate_to_english(prompt)
|
360 |
+
if bg_prompt:
|
361 |
+
bg_prompt = translate_to_english(bg_prompt)
|
362 |
+
except Exception as e:
|
363 |
+
print(f"Translation error (continuing with original text): {str(e)}")
|
364 |
+
|
365 |
+
results, _ = _process(img, prompt, bg_prompt, aspect_ratio)
|
366 |
+
|
367 |
+
if bg_prompt:
|
368 |
+
try:
|
369 |
+
print(f"Using position: {position}") # 디버깅용
|
370 |
+
# 위치 값 검증
|
371 |
+
valid_positions = ["top-left", "top-center", "top-right",
|
372 |
+
"middle-left", "middle-center", "middle-right",
|
373 |
+
"bottom-left", "bottom-center", "bottom-right"]
|
374 |
+
if position not in valid_positions:
|
375 |
+
position = "bottom-center"
|
376 |
+
print(f"Invalid position, using default: {position}")
|
377 |
+
|
378 |
+
combined = combine_with_background(
|
379 |
+
foreground=results[2],
|
380 |
+
background=results[1],
|
381 |
+
position=position,
|
382 |
+
scale_percent=scale_percent
|
383 |
+
)
|
384 |
+
return combined, results[2]
|
385 |
+
except Exception as e:
|
386 |
+
print(f"Combination error: {str(e)}")
|
387 |
+
return results[1], results[2]
|
388 |
+
|
389 |
+
return results[1], results[2] # 기본 반환 추가
|
390 |
+
except Exception as e:
|
391 |
+
print(f"Error in process_prompt: {str(e)}")
|
392 |
+
raise gr.Error(str(e))
|
393 |
+
finally:
|
394 |
+
clear_memory()
|
395 |
+
|
396 |
+
|
397 |
+
def process_bbox(img: Image.Image, box_input: str) -> tuple[Image.Image, Image.Image]:
|
398 |
+
try:
|
399 |
+
if img is None or box_input.strip() == "":
|
400 |
+
raise gr.Error("Please provide both image and bounding box coordinates")
|
401 |
+
|
402 |
+
try:
|
403 |
+
coords = eval(box_input)
|
404 |
+
if not isinstance(coords, list) or len(coords) != 4:
|
405 |
+
raise ValueError("Invalid box format")
|
406 |
+
bbox = tuple(int(x) for x in coords)
|
407 |
+
except:
|
408 |
+
raise gr.Error("Invalid box format. Please provide [xmin, ymin, xmax, ymax]")
|
409 |
+
|
410 |
+
# Process the image
|
411 |
+
results, _ = _process(img, bbox)
|
412 |
+
|
413 |
+
# 합성된 이미지와 추출된 이미지만 반환
|
414 |
+
return results[1], results[2]
|
415 |
+
except Exception as e:
|
416 |
+
raise gr.Error(str(e))
|
417 |
+
|
418 |
+
# Event handler functions 수정
|
419 |
+
def update_process_button(img, prompt):
|
420 |
+
return gr.update(
|
421 |
+
interactive=bool(img and prompt),
|
422 |
+
variant="primary" if bool(img and prompt) else "secondary"
|
423 |
+
)
|
424 |
+
|
425 |
+
def update_box_button(img, box_input):
|
426 |
+
try:
|
427 |
+
if img and box_input:
|
428 |
+
coords = eval(box_input)
|
429 |
+
if isinstance(coords, list) and len(coords) == 4:
|
430 |
+
return gr.update(interactive=True, variant="primary")
|
431 |
+
return gr.update(interactive=False, variant="secondary")
|
432 |
+
except:
|
433 |
+
return gr.update(interactive=False, variant="secondary")
|
434 |
+
|
435 |
+
|
436 |
+
css = """
|
437 |
+
footer {display: none}
|
438 |
+
.main-title {
|
439 |
+
text-align: center;
|
440 |
+
margin: 1em 0;
|
441 |
+
padding: 1.5em;
|
442 |
+
background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
|
443 |
+
border-radius: 15px;
|
444 |
+
box-shadow: 0 4px 6px rgba(0,0,0,0.1);
|
445 |
+
}
|
446 |
+
.main-title h1 {
|
447 |
+
color: #2196F3;
|
448 |
+
font-size: 2.8em;
|
449 |
+
margin-bottom: 0.3em;
|
450 |
+
font-weight: 700;
|
451 |
+
}
|
452 |
+
.main-title p {
|
453 |
+
color: #555;
|
454 |
+
font-size: 1.3em;
|
455 |
+
line-height: 1.4;
|
456 |
+
}
|
457 |
+
.container {
|
458 |
+
max-width: 1200px;
|
459 |
+
margin: auto;
|
460 |
+
padding: 20px;
|
461 |
+
}
|
462 |
+
.input-panel, .output-panel {
|
463 |
+
background: white;
|
464 |
+
padding: 1.5em;
|
465 |
+
border-radius: 12px;
|
466 |
+
box-shadow: 0 2px 8px rgba(0,0,0,0.08);
|
467 |
+
margin-bottom: 1em;
|
468 |
+
}
|
469 |
+
.controls-panel {
|
470 |
+
background: #f8f9fa;
|
471 |
+
padding: 1em;
|
472 |
+
border-radius: 8px;
|
473 |
+
margin: 1em 0;
|
474 |
+
}
|
475 |
+
.image-display {
|
476 |
+
min-height: 512px;
|
477 |
+
display: flex;
|
478 |
+
align-items: center;
|
479 |
+
justify-content: center;
|
480 |
+
background: #fafafa;
|
481 |
+
border-radius: 8px;
|
482 |
+
margin: 1em 0;
|
483 |
+
}
|
484 |
+
.example-section {
|
485 |
+
text-align: center;
|
486 |
+
padding: 2em;
|
487 |
+
background: #f5f5f5;
|
488 |
+
border-radius: 12px;
|
489 |
+
margin-top: 2em;
|
490 |
+
}
|
491 |
+
.example-section img {
|
492 |
+
max-width: 100%;
|
493 |
+
border-radius: 8px;
|
494 |
+
box-shadow: 0 4px 8px rgba(0,0,0,0.1);
|
495 |
+
}
|
496 |
+
.accordion {
|
497 |
+
border: 1px solid #e0e0e0;
|
498 |
+
border-radius: 8px;
|
499 |
+
margin: 1em 0;
|
500 |
+
}
|
501 |
+
.accordion-header {
|
502 |
+
padding: 1em;
|
503 |
+
background: #f5f5f5;
|
504 |
+
cursor: pointer;
|
505 |
+
}
|
506 |
+
.accordion-content {
|
507 |
+
padding: 1em;
|
508 |
+
display: none;
|
509 |
+
}
|
510 |
+
.accordion.open .accordion-content {
|
511 |
+
display: block;
|
512 |
+
}
|
513 |
+
.position-grid {
|
514 |
+
display: grid;
|
515 |
+
grid-template-columns: repeat(3, 1fr);
|
516 |
+
gap: 8px;
|
517 |
+
margin: 1em 0;
|
518 |
+
}
|
519 |
+
.position-btn {
|
520 |
+
padding: 10px;
|
521 |
+
border: 1px solid #ddd;
|
522 |
+
border-radius: 4px;
|
523 |
+
background: white;
|
524 |
+
cursor: pointer;
|
525 |
+
transition: all 0.3s ease;
|
526 |
+
width: 40px;
|
527 |
+
height: 40px;
|
528 |
+
display: flex;
|
529 |
+
align-items: center;
|
530 |
+
justify-content: center;
|
531 |
+
}
|
532 |
+
.position-btn:hover {
|
533 |
+
background: #e3f2fd;
|
534 |
+
}
|
535 |
+
.position-btn.selected {
|
536 |
+
background-color: #2196F3;
|
537 |
+
color: white;
|
538 |
+
border-color: #1976D2;
|
539 |
+
}
|
540 |
+
"""
|
541 |
+
|
542 |
+
|
543 |
+
def add_text_with_stroke(draw, text, x, y, font, text_color, stroke_width):
|
544 |
+
"""Helper function to draw text with stroke"""
|
545 |
+
# Draw the stroke/outline
|
546 |
+
for adj_x in range(-stroke_width, stroke_width + 1):
|
547 |
+
for adj_y in range(-stroke_width, stroke_width + 1):
|
548 |
+
draw.text((x + adj_x, y + adj_y), text, font=font, fill=text_color)
|
549 |
+
|
550 |
+
def remove_background(image):
|
551 |
+
# Save the image to a specific location
|
552 |
+
filename = f"image_{uuid.uuid4()}.png" # Generates a universally unique identifier (UUID) for the filename
|
553 |
+
image.save(filename)
|
554 |
+
# Call gradio client for background removal
|
555 |
+
result = client.predict(images=handle_file(filename), api_name="/image")
|
556 |
+
return Image.open(result[0])
|
557 |
+
|
558 |
+
def superimpose(image_with_text, overlay_image):
|
559 |
+
# Open image as RGBA to handle transparency
|
560 |
+
overlay_image = overlay_image.convert("RGBA")
|
561 |
+
# Paste overlay on the background
|
562 |
+
image_with_text.paste(overlay_image, (0, 0), overlay_image)
|
563 |
+
# Save the final image
|
564 |
+
# image_with_text.save("output_image.png")
|
565 |
+
return image_with_text
|
566 |
+
|
567 |
+
def add_text_to_image(
|
568 |
+
input_image,
|
569 |
+
text,
|
570 |
+
font_size,
|
571 |
+
color,
|
572 |
+
opacity,
|
573 |
+
x_position,
|
574 |
+
y_position,
|
575 |
+
thickness,
|
576 |
+
text_position_type,
|
577 |
+
font_choice
|
578 |
+
):
|
579 |
+
try:
|
580 |
+
if input_image is None or text.strip() == "":
|
581 |
+
return input_image
|
582 |
+
|
583 |
+
# PIL Image 객체로 변환
|
584 |
+
if not isinstance(input_image, Image.Image):
|
585 |
+
if isinstance(input_image, np.ndarray):
|
586 |
+
image = Image.fromarray(input_image)
|
587 |
+
else:
|
588 |
+
raise ValueError("Unsupported image type")
|
589 |
+
else:
|
590 |
+
image = input_image.copy()
|
591 |
+
|
592 |
+
# 이미지를 RGBA 모드로 변환
|
593 |
+
if image.mode != 'RGBA':
|
594 |
+
image = image.convert('RGBA')
|
595 |
+
|
596 |
+
# 폰트 설정
|
597 |
+
font_files = {
|
598 |
+
"Default": "DejaVuSans.ttf",
|
599 |
+
"Korean Regular": "ko-Regular.ttf"
|
600 |
+
}
|
601 |
+
|
602 |
+
try:
|
603 |
+
font_file = font_files.get(font_choice, "DejaVuSans.ttf")
|
604 |
+
font = ImageFont.truetype(font_file, int(font_size))
|
605 |
+
except Exception as e:
|
606 |
+
print(f"Font loading error ({font_choice}): {str(e)}")
|
607 |
+
font = ImageFont.load_default()
|
608 |
+
|
609 |
+
# 색상 설정
|
610 |
+
color_map = {
|
611 |
+
'White': (255, 255, 255),
|
612 |
+
'Black': (0, 0, 0),
|
613 |
+
'Red': (255, 0, 0),
|
614 |
+
'Green': (0, 255, 0),
|
615 |
+
'Blue': (0, 0, 255),
|
616 |
+
'Yellow': (255, 255, 0),
|
617 |
+
'Purple': (128, 0, 128)
|
618 |
+
}
|
619 |
+
rgb_color = color_map.get(color, (255, 255, 255))
|
620 |
+
|
621 |
+
# 임시 Draw 객체 생성하여 텍스트 크기 계산
|
622 |
+
temp_draw = ImageDraw.Draw(image)
|
623 |
+
text_bbox = temp_draw.textbbox((0, 0), text, font=font)
|
624 |
+
text_width = text_bbox[2] - text_bbox[0]
|
625 |
+
text_height = text_bbox[3] - text_bbox[1]
|
626 |
+
|
627 |
+
# 위치 계산
|
628 |
+
actual_x = int((image.width - text_width) * (x_position / 100))
|
629 |
+
actual_y = int((image.height - text_height) * (y_position / 100))
|
630 |
+
|
631 |
+
# 텍스트 색상 설정
|
632 |
+
text_color = (*rgb_color, int(opacity))
|
633 |
+
|
634 |
+
if text_position_type == "Text Behind Image":
|
635 |
+
try:
|
636 |
+
# 원본 이미지에서 전경 객체만 추출
|
637 |
+
foreground = remove_background(image)
|
638 |
+
|
639 |
+
# 배경 이미지 생성 (원본 이미지 복사)
|
640 |
+
background = image.copy()
|
641 |
+
|
642 |
+
# 텍스트를 그릴 임시 레이어 생성
|
643 |
+
text_layer = Image.new('RGBA', image.size, (255, 255, 255, 0))
|
644 |
+
draw_text = ImageDraw.Draw(text_layer)
|
645 |
+
|
646 |
+
# 텍스트 그리기
|
647 |
+
add_text_with_stroke(
|
648 |
+
draw_text,
|
649 |
+
text,
|
650 |
+
actual_x,
|
651 |
+
actual_y,
|
652 |
+
font,
|
653 |
+
text_color,
|
654 |
+
int(thickness)
|
655 |
+
)
|
656 |
+
|
657 |
+
# 배경에 텍스트 합성
|
658 |
+
background = Image.alpha_composite(background, text_layer)
|
659 |
+
|
660 |
+
# 텍스트가 있는 배경 위에 전경 객체 합성
|
661 |
+
output_image = Image.alpha_composite(background, foreground)
|
662 |
+
except Exception as e:
|
663 |
+
print(f"Error in Text Behind Image processing: {str(e)}")
|
664 |
+
return input_image
|
665 |
+
else:
|
666 |
+
# 텍스트 오버레이 생성
|
667 |
+
txt_overlay = Image.new('RGBA', image.size, (255, 255, 255, 0))
|
668 |
+
draw = ImageDraw.Draw(txt_overlay)
|
669 |
+
|
670 |
+
# 텍스트를 이미지 위에 그리기
|
671 |
+
add_text_with_stroke(
|
672 |
+
draw,
|
673 |
+
text,
|
674 |
+
actual_x,
|
675 |
+
actual_y,
|
676 |
+
font,
|
677 |
+
text_color,
|
678 |
+
int(thickness)
|
679 |
+
)
|
680 |
+
output_image = Image.alpha_composite(image, txt_overlay)
|
681 |
+
|
682 |
+
# RGB로 변환
|
683 |
+
output_image = output_image.convert('RGB')
|
684 |
+
|
685 |
+
return output_image
|
686 |
+
|
687 |
+
except Exception as e:
|
688 |
+
print(f"Error in add_text_to_image: {str(e)}")
|
689 |
+
return input_image
|
690 |
+
|
691 |
+
|
692 |
+
def update_position(new_position):
|
693 |
+
"""위치 업데이트 함수"""
|
694 |
+
print(f"Position updated to: {new_position}")
|
695 |
+
return new_position
|
696 |
+
|
697 |
+
def update_controls(bg_prompt):
|
698 |
+
"""배경 프롬프트 입력 여부에 따라 컨트롤 표시 업데이트"""
|
699 |
+
is_visible = bool(bg_prompt)
|
700 |
+
return [
|
701 |
+
gr.update(visible=is_visible), # aspect_ratio
|
702 |
+
gr.update(visible=is_visible), # object_controls
|
703 |
+
]
|
704 |
+
|
705 |
+
with gr.Blocks(theme=gr.themes.Soft(), css=css) as demo:
|
706 |
+
position = gr.State(value="bottom-center") # 여기로 이동
|
707 |
+
|
708 |
+
gr.HTML("""
|
709 |
+
<div class="main-title">
|
710 |
+
<h1>🎨 GiniGen Canvas-o3</h1>
|
711 |
+
<p>Remove background of specified objects, generate new backgrounds, and insert text over or behind images with prompts.</p>
|
712 |
+
</div>
|
713 |
+
""")
|
714 |
+
|
715 |
+
with gr.Row(equal_height=True):
|
716 |
+
# 왼쪽 패널 (입력)
|
717 |
+
with gr.Column(scale=1):
|
718 |
+
with gr.Group(elem_classes="input-panel"):
|
719 |
+
input_image = gr.Image(
|
720 |
+
type="pil",
|
721 |
+
label="Upload Image",
|
722 |
+
interactive=True,
|
723 |
+
height=400
|
724 |
+
)
|
725 |
+
text_prompt = gr.Textbox(
|
726 |
+
label="Object to Extract",
|
727 |
+
placeholder="Enter what you want to extract...",
|
728 |
+
interactive=True
|
729 |
+
)
|
730 |
+
with gr.Row():
|
731 |
+
bg_prompt = gr.Textbox(
|
732 |
+
label="Background Prompt (optional)",
|
733 |
+
placeholder="Describe the background...",
|
734 |
+
interactive=True,
|
735 |
+
scale=3
|
736 |
+
)
|
737 |
+
aspect_ratio = gr.Dropdown(
|
738 |
+
choices=["1:1", "16:9", "9:16", "4:3"],
|
739 |
+
value="1:1",
|
740 |
+
label="Aspect Ratio",
|
741 |
+
interactive=True,
|
742 |
+
visible=True,
|
743 |
+
scale=1
|
744 |
+
)
|
745 |
+
|
746 |
+
with gr.Group(elem_classes="controls-panel", visible=False) as object_controls:
|
747 |
+
with gr.Column(scale=1):
|
748 |
+
position = gr.State(value="bottom-center") # 초기값 설정
|
749 |
+
with gr.Row():
|
750 |
+
btn_top_left = gr.Button("↖", elem_classes="position-btn")
|
751 |
+
btn_top_center = gr.Button("↑", elem_classes="position-btn")
|
752 |
+
btn_top_right = gr.Button("↗", elem_classes="position-btn")
|
753 |
+
with gr.Row():
|
754 |
+
btn_middle_left = gr.Button("←", elem_classes="position-btn")
|
755 |
+
btn_middle_center = gr.Button("•", elem_classes="position-btn")
|
756 |
+
btn_middle_right = gr.Button("→", elem_classes="position-btn")
|
757 |
+
with gr.Row():
|
758 |
+
btn_bottom_left = gr.Button("↙", elem_classes="position-btn")
|
759 |
+
btn_bottom_center = gr.Button("↓", elem_classes="position-btn", value="selected")
|
760 |
+
btn_bottom_right = gr.Button("↘", elem_classes="position-btn")
|
761 |
+
with gr.Column(scale=1):
|
762 |
+
scale_slider = gr.Slider(
|
763 |
+
minimum=10,
|
764 |
+
maximum=200,
|
765 |
+
value=50,
|
766 |
+
step=5,
|
767 |
+
label="Object Size (%)"
|
768 |
+
)
|
769 |
+
|
770 |
+
process_btn = gr.Button(
|
771 |
+
"Process",
|
772 |
+
variant="primary",
|
773 |
+
interactive=False,
|
774 |
+
size="lg"
|
775 |
+
)
|
776 |
+
|
777 |
+
# 오른쪽 패널 (출력)
|
778 |
+
with gr.Column(scale=1):
|
779 |
+
with gr.Group(elem_classes="output-panel"):
|
780 |
+
with gr.Tab("Result"):
|
781 |
+
combined_image = gr.Image(
|
782 |
+
label="Combined Result",
|
783 |
+
show_download_button=True,
|
784 |
+
type="pil",
|
785 |
+
height=400
|
786 |
+
)
|
787 |
+
|
788 |
+
# 텍스트 삽입 옵션을 Accordion으로 변경
|
789 |
+
with gr.Accordion("Text Insertion Options", open=False):
|
790 |
+
with gr.Group():
|
791 |
+
with gr.Row():
|
792 |
+
text_input = gr.Textbox(
|
793 |
+
label="Text Content",
|
794 |
+
placeholder="Enter text to add..."
|
795 |
+
)
|
796 |
+
text_position_type = gr.Radio(
|
797 |
+
choices=["Text Over Image", "Text Behind Image"],
|
798 |
+
value="Text Over Image",
|
799 |
+
label="Text Position"
|
800 |
+
)
|
801 |
+
|
802 |
+
with gr.Row():
|
803 |
+
with gr.Column(scale=1):
|
804 |
+
font_choice = gr.Dropdown(
|
805 |
+
choices=["Default", "Korean Regular"], # "Korean Son" 제거
|
806 |
+
|
807 |
+
value="Default",
|
808 |
+
label="Font Selection",
|
809 |
+
interactive=True
|
810 |
+
)
|
811 |
+
|
812 |
+
|
813 |
+
font_size = gr.Slider(
|
814 |
+
minimum=10,
|
815 |
+
maximum=200,
|
816 |
+
value=40,
|
817 |
+
step=5,
|
818 |
+
label="Font Size"
|
819 |
+
)
|
820 |
+
color_dropdown = gr.Dropdown(
|
821 |
+
choices=["White", "Black", "Red", "Green", "Blue", "Yellow", "Purple"],
|
822 |
+
value="White",
|
823 |
+
label="Text Color"
|
824 |
+
)
|
825 |
+
thickness = gr.Slider(
|
826 |
+
minimum=0,
|
827 |
+
maximum=10,
|
828 |
+
value=1,
|
829 |
+
step=1,
|
830 |
+
label="Text Thickness"
|
831 |
+
)
|
832 |
+
with gr.Column(scale=1):
|
833 |
+
opacity_slider = gr.Slider(
|
834 |
+
minimum=0,
|
835 |
+
maximum=255,
|
836 |
+
value=255,
|
837 |
+
step=1,
|
838 |
+
label="Opacity"
|
839 |
+
)
|
840 |
+
x_position = gr.Slider(
|
841 |
+
minimum=0,
|
842 |
+
maximum=100,
|
843 |
+
value=50,
|
844 |
+
step=1,
|
845 |
+
label="Left(0%)~Right(100%)"
|
846 |
+
)
|
847 |
+
y_position = gr.Slider(
|
848 |
+
minimum=0,
|
849 |
+
maximum=100,
|
850 |
+
value=50,
|
851 |
+
step=1,
|
852 |
+
label="High(0%)~Low(100%)"
|
853 |
+
)
|
854 |
+
add_text_btn = gr.Button("Apply Text", variant="primary")
|
855 |
+
|
856 |
+
extracted_image = gr.Image(
|
857 |
+
label="Extracted Object",
|
858 |
+
show_download_button=True,
|
859 |
+
type="pil",
|
860 |
+
height=200
|
861 |
+
)
|
862 |
+
|
863 |
+
# CSS 클래스를 위한 스타일 추가
|
864 |
+
gr.HTML("""
|
865 |
+
<style>
|
866 |
+
.position-btn.selected {
|
867 |
+
background-color: #2196F3 !important;
|
868 |
+
color: white !important;
|
869 |
+
}
|
870 |
+
</style>
|
871 |
+
""")
|
872 |
+
|
873 |
+
# 버튼 클릭 이벤트 바인딩
|
874 |
+
position_mapping = {
|
875 |
+
btn_top_left: "top-left",
|
876 |
+
btn_top_center: "top-center",
|
877 |
+
btn_top_right: "top-right",
|
878 |
+
btn_middle_left: "middle-left",
|
879 |
+
btn_middle_center: "middle-center",
|
880 |
+
btn_middle_right: "middle-right",
|
881 |
+
btn_bottom_left: "bottom-left",
|
882 |
+
btn_bottom_center: "bottom-center",
|
883 |
+
btn_bottom_right: "bottom-right"
|
884 |
+
}
|
885 |
+
|
886 |
+
for btn, pos in position_mapping.items():
|
887 |
+
btn.click(
|
888 |
+
fn=lambda pos=pos: update_position(pos), # 클로저 문제 해결을 위해 수정
|
889 |
+
outputs=position
|
890 |
+
)
|
891 |
+
|
892 |
+
|
893 |
+
# 이벤트 바인딩
|
894 |
+
bg_prompt.change(
|
895 |
+
fn=update_controls,
|
896 |
+
inputs=bg_prompt,
|
897 |
+
outputs=[aspect_ratio, object_controls],
|
898 |
+
queue=False
|
899 |
+
)
|
900 |
+
|
901 |
+
input_image.change(
|
902 |
+
fn=update_process_button,
|
903 |
+
inputs=[input_image, text_prompt],
|
904 |
+
outputs=process_btn,
|
905 |
+
queue=False
|
906 |
+
)
|
907 |
+
|
908 |
+
text_prompt.change(
|
909 |
+
fn=update_process_button,
|
910 |
+
inputs=[input_image, text_prompt],
|
911 |
+
outputs=process_btn,
|
912 |
+
queue=False
|
913 |
+
)
|
914 |
+
|
915 |
+
process_btn.click(
|
916 |
+
fn=process_prompt,
|
917 |
+
inputs=[
|
918 |
+
input_image,
|
919 |
+
text_prompt,
|
920 |
+
bg_prompt,
|
921 |
+
aspect_ratio,
|
922 |
+
position,
|
923 |
+
scale_slider
|
924 |
+
],
|
925 |
+
outputs=[combined_image, extracted_image],
|
926 |
+
queue=True
|
927 |
+
)
|
928 |
+
|
929 |
+
# 이벤트 바인딩 부분에서
|
930 |
+
add_text_btn.click(
|
931 |
+
fn=add_text_to_image,
|
932 |
+
inputs=[
|
933 |
+
combined_image, # 첫 번째 인자로 이미지
|
934 |
+
text_input, # 두 번째 인자로 텍스트
|
935 |
+
font_size,
|
936 |
+
color_dropdown,
|
937 |
+
opacity_slider,
|
938 |
+
x_position,
|
939 |
+
y_position,
|
940 |
+
thickness,
|
941 |
+
text_position_type,
|
942 |
+
font_choice
|
943 |
+
],
|
944 |
+
outputs=combined_image,
|
945 |
+
api_name="add_text" # API 이름 추가
|
946 |
+
)
|
947 |
+
|
948 |
+
|
949 |
+
|
950 |
+
demo.queue(max_size=5)
|
951 |
+
demo.launch(
|
952 |
+
server_name="0.0.0.0",
|
953 |
+
server_port=7860,
|
954 |
+
share=False,
|
955 |
+
max_threads=2
|
956 |
+
)
|