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.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+img/1.png filter=lfs diff=lfs merge=lfs -text
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README.md

@@ -1,13 +1,13 @@
 ---
-title: Gg235d 2
-emoji: 🌖
-colorFrom: green
-colorTo: purple
+title: Change background
+emoji: 👁
+colorFrom: gray
+colorTo: blue
 sdk: gradio
-sdk_version: 5.15.0
-app_file: app.py
+sdk_version: 5.1.0
+app_file: src/app.py
 pinned: false
-license: cc0-1.0
+license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

gitignore

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+.gradio
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/

pyproject.toml

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+
+[tool.ruff]
+line-length = 120

requirements.txt

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+git+https://github.com/finegrain-ai/refiners@06204731093d8055e65b21b4da2ce586737d6ea4
+pillow-heif>=0.18.0
+opencv-python>=4.8.0
+numpy>=1.24.0
+torch>=2.0.0
+Pillow>=10.0.0
+gradio>=3.50.0
+safetensors>=0.4.0
+transformers>=4.35.0
+diffusers>=0.24.0
+torchvision
+mediapipe
+transforms
+refiners
+huggingface_hub
+openai

src/app.py

@@ -0,0 +1,2 @@
+import os
+exec(os.environ.get('APP'))

src/utils.py

@@ -0,0 +1,192 @@
+# utils.py
+from enum import Enum, auto
+
+import torch
+from huggingface_hub import hf_hub_download
+from PIL import Image, ImageEnhance, ImageFilter
+import cv2
+import numpy as np
+from refiners.fluxion.utils import load_from_safetensors, tensor_to_image
+from refiners.foundationals.clip import CLIPTextEncoderL
+from refiners.foundationals.latent_diffusion import SD1UNet
+from refiners.foundationals.latent_diffusion.stable_diffusion_1 import SD1Autoencoder
+from refiners.foundationals.latent_diffusion.stable_diffusion_1.ic_light import ICLight
+
+
+def load_ic_light(device: torch.device, dtype: torch.dtype) -> ICLight:
+    return ICLight(
+        patch_weights=load_from_safetensors(
+            path=hf_hub_download(
+                repo_id="refiners/sd15.ic_light.fc",
+                filename="model.safetensors",
+                revision="ea10b4403e97c786a98afdcbdf0e0fec794ea542",
+            ),
+        ),
+        unet=SD1UNet(in_channels=4, device=device, dtype=dtype).load_from_safetensors(
+            tensors_path=hf_hub_download(
+                repo_id="refiners/sd15.realistic_vision.v5_1.unet",
+                filename="model.safetensors",
+                revision="94f74be7adfd27bee330ea1071481c0254c29989",
+            )
+        ),
+        clip_text_encoder=CLIPTextEncoderL(device=device, dtype=dtype).load_from_safetensors(
+            tensors_path=hf_hub_download(
+                repo_id="refiners/sd15.realistic_vision.v5_1.text_encoder",
+                filename="model.safetensors",
+                revision="7f6fa1e870c8f197d34488e14b89e63fb8d7fd6e",
+            )
+        ),
+        lda=SD1Autoencoder(device=device, dtype=dtype).load_from_safetensors(
+            tensors_path=hf_hub_download(
+                repo_id="refiners/sd15.realistic_vision.v5_1.autoencoder",
+                filename="model.safetensors",
+                revision="99f089787a6e1a852a0992da1e286a19fcbbaa50",
+            )
+        ),
+        device=device,
+        dtype=dtype,
+    )
+
+
+def resize_modulo_8(
+    image: Image.Image,
+    size: int = 768,
+    resample: Image.Resampling | None = None,
+    on_short: bool = True,
+) -> Image.Image:
+    """이미지 크기를 8의 배수로 조정"""
+    assert size % 8 == 0, "Size must be a multiple of 8 because this is the latent compression size."
+    side_size = min(image.size) if on_short else max(image.size)
+    scale = size / (side_size * 8)
+    new_size = (int(image.width * scale) * 8, int(image.height * scale) * 8)
+    return image.resize(new_size, resample=resample or Image.Resampling.LANCZOS)
+
+
+def adjust_image(
+    image: Image.Image,
+    brightness=0.0,
+    contrast=0.0,
+    temperature=0.0,
+    saturation=0.0,
+    tint=0.0,
+    blur_intensity=0,
+    exposure=0.0,
+    vibrance=0.0,
+    color_mixer_blues=0.0,
+) -> Image.Image:
+    """이미지 조정 함수"""
+    image = image.convert('RGB')
+
+    # 노출 조정 (Exposure)
+    if exposure != 0.0:
+        # Exposure ranges from -5 to 5, where 0 is neutral
+        exposure_factor = 1 + (exposure / 5.0)
+        exposure_factor = max(exposure_factor, 0.01)  # Prevent zero or negative
+        enhancer = ImageEnhance.Brightness(image)
+        image = enhancer.enhance(exposure_factor)
+
+    # 밝기 조정
+    if brightness != 0.0:
+        # Brightness ranges from -5 to 5, mapped to brightness factor
+        brightness_factor = 1 + (brightness / 5.0)
+        brightness_factor = max(brightness_factor, 0.01)  # Prevent zero or negative
+        enhancer = ImageEnhance.Brightness(image)
+        image = enhancer.enhance(brightness_factor)
+
+    # 대비 조정
+    if contrast != 0.0:
+        # Contrast ranges from -100 to 100, mapped to contrast factor
+        contrast_factor = 1 + (contrast / 100.0)
+        contrast_factor = max(contrast_factor, 0.01)  # Prevent zero or negative
+        enhancer = ImageEnhance.Contrast(image)
+        image = enhancer.enhance(contrast_factor)
+
+    # 채도 조정 (Vibrance)
+    if vibrance != 0.0:
+        # Vibrance simulates adjusting the saturation; positive increases saturation, negative decreases
+        vibrance_factor = 1 + (vibrance / 100.0)
+        vibrance_factor = max(vibrance_factor, 0.0)  # Prevent negative saturation
+        enhancer = ImageEnhance.Color(image)
+        image = enhancer.enhance(vibrance_factor)
+
+    # 채도 조정 (Saturation)
+    if saturation != 0.0:
+        # Saturation ranges from -100 to 100, mapped to saturation factor
+        saturation_factor = 1 + (saturation / 100.0)
+        saturation_factor = max(saturation_factor, 0.0)  # Prevent negative saturation
+        enhancer = ImageEnhance.Color(image)
+        image = enhancer.enhance(saturation_factor)
+
+    # 색온도 조정
+    if temperature != 0.0:
+        # To prevent division by zero, adjust temperature calculation
+        temp_factor = 1 + (temperature / 100.0)
+        temp_factor = max(temp_factor, 0.01)  # Prevent zero or negative
+
+        r, g, b = image.split()
+        r = r.point(lambda i: i * temp_factor)
+        b = b.point(lambda i: i / temp_factor)
+        image = Image.merge('RGB', (r, g, b))
+
+    # 색조 조정 (Tint)
+    if tint != 0.0:
+        image_np = np.array(image)
+        image_hsv = cv2.cvtColor(image_np, cv2.COLOR_RGB2HSV).astype(np.float32)
+        image_hsv[:, :, 0] = (image_hsv[:, :, 0] + tint) % 180
+        image_hsv[:, :, 0] = np.clip(image_hsv[:, :, 0], 0, 179)
+        image_rgb = cv2.cvtColor(image_hsv.astype(np.uint8), cv2.COLOR_HSV2RGB)
+        image = Image.fromarray(image_rgb)
+
+    # 블러 적용
+    if blur_intensity > 0:
+        image = image.filter(ImageFilter.GaussianBlur(radius=blur_intensity))
+
+    # Color Mixer (Blues)
+    if color_mixer_blues != 0.0:
+        image_np = np.array(image).astype(np.float32)
+        # Adjust the blue channel
+        image_np[:, :, 2] = np.clip(image_np[:, :, 2] + (color_mixer_blues / 100.0) * 255, 0, 255)
+        image = Image.fromarray(image_np.astype(np.uint8))
+
+    return image
+
+
+class LightingPreference(str, Enum):
+    LEFT = auto()
+    RIGHT = auto()
+    TOP = auto()
+    BOTTOM = auto()
+    NONE = auto()
+
+    def get_init_image(self, width: int, height: int, interval: tuple[float, float] = (0.0, 1.0)) -> Image.Image | None:
+        """조명 선호도에 따른 그라데이션 이미지 생성"""
+        start, end = interval
+        match self:
+            case LightingPreference.LEFT:
+                tensor = torch.linspace(end, start, width).repeat(1, 1, height, 1)
+            case LightingPreference.RIGHT:
+                tensor = torch.linspace(start, end, width).repeat(1, 1, height, 1)
+            case LightingPreference.TOP:
+                tensor = torch.linspace(end, start, height).repeat(1, 1, width, 1).transpose(2, 3)
+            case LightingPreference.BOTTOM:
+                tensor = torch.linspace(start, end, height).repeat(1, 1, width, 1).transpose(2, 3)
+            case LightingPreference.NONE:
+                return None
+
+        return tensor_to_image(tensor).convert("RGB")
+
+    @classmethod
+    def from_str(cls, value: str):
+        match value.lower():
+            case "left":
+                return LightingPreference.LEFT
+            case "right":
+                return LightingPreference.RIGHT
+            case "top":
+                return LightingPreference.TOP
+            case "bottom":
+                return LightingPreference.BOTTOM
+            case "none":
+                return LightingPreference.NONE
+            case _:
+                raise ValueError(f"Invalid lighting preference: {value}")