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Upload streamlit_app.py
Browse files- streamlit_app.py +216 -132
streamlit_app.py
CHANGED
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@@ -1,4 +1,4 @@
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# streamlit_app.py — AI LightBox · Beauty (v0.3 UI
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# Packshot → Padding (square/canvas) → Try-on (lips/eyes/face/nails/hair/brow/body/lifestyle) · SR · (optional) Video
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import os, io, zipfile, requests, streamlit as st
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@@ -6,9 +6,10 @@ from PIL import Image
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from pathlib import Path
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# ================= Env & API (robust) =================
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def _env(k):
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return (os.getenv(k) or "").strip().strip("'\"")
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API_BASE = (
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_env("AI_BEAUTYBOX_API") or
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_env("AI_LIGHTBOX_API") or
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@@ -17,8 +18,8 @@ API_BASE = (
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).rstrip("/")
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HF_TOKEN = (
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_env("AI_BEAUTYBOX_TOKEN") or
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_env("AI_LIGHTBOX_TOKEN") or
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_env("BeautyBoxAI_TOKEN") or
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_env("AI_BEAUTY_TOKEN")
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)
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HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"} if HF_TOKEN else {}
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PREVIEW_SIZE = int(os.getenv("PREVIEW_SIZE", "512"))
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APP_DIR = Path(__file__).parent
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# ================= Demo dosyaları (yalnızca yerel klasör) =================
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DEMO_INPUT = str(APP_DIR / "input.jpg")
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DEMO_TRYON = str(APP_DIR / "tryon.jpg")
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# ================= Session State (ilk yükte) =================
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defaults = {
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"results": None,
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"job_counter": 0,
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"duration": "6",
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# input.jpg ve tryon.jpg varsa demo otomatik açık başlar
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"demo_on": (Path(DEMO_INPUT).is_file() and Path(DEMO_TRYON).is_file()),
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}
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for k, v in defaults.items():
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if k not in st.session_state:
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@@ -58,6 +52,7 @@ HAIR = {"hair_color"}
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REGIONS = ["auto","lips","eyes","face","nails","hand","hair","brow","body","lifestyle"]
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def tryon_label(category: str, region_override: str, sr: bool) -> str:
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r = (region_override or "auto").lower()
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if r != "auto":
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base = {
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"lifestyle":"Lifestyle"
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}.get(r, "Try-on")
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return f"{base} (SR)" if sr else base
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c = (category or "auto").lower()
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if c in LIPS: base = "On-Lips"
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elif c in EYES: base = "On-Eyes"
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@@ -80,6 +76,25 @@ def tryon_label(category: str, region_override: str, sr: bool) -> str:
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def _needs_auth(url: str) -> bool:
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return url.startswith(API_BASE) or url.startswith("outputs/")
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def backend_ok() -> bool:
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try:
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r = requests.get(f"{API_BASE}/health", headers=HEADERS if HF_TOKEN else None, timeout=10)
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return r.json()
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def post_video(image_url: str, duration="6", resolution="768P", prompt_optimizer=False):
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payload = {
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r = requests.post(f"{API_BASE}/v1/video/from-image", data=payload,
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headers=HEADERS if HF_TOKEN else None, timeout=600)
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r.raise_for_status()
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return r.json()
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@st.cache_data(ttl=300, show_spinner=False)
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def fetch_bytes(url_or_path: str):
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if not url_or_path: return None
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p = Path(url_or_path)
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if p.is_file():
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try: return p.read_bytes()
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except Exception: return None
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# outputs/ veya URL
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try:
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url = f"{API_BASE}/{url_or_path}" if url_or_path.startswith("outputs/") else url_or_path
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headers = (HEADERS if (_needs_auth(url) and HF_TOKEN) else None)
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r = requests.get(url, headers=headers, timeout=180)
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r.raise_for_status()
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return r.content
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except Exception:
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return None
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@st.cache_data(ttl=300, show_spinner=False)
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def image_size_from_bytes(b: bytes):
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try:
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im = Image.open(io.BytesIO(b))
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except Exception:
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return None
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try:
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im = Image.open(io.BytesIO(data))
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fmt = (im.format or "JPEG").lower()
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return "." + {"jpeg":"jpg","jpg":"jpg","png":"png","webp":"webp"}.get(fmt, "jpg")
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except Exception:
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return ".jpg"
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@st.cache_data(ttl=300, show_spinner=False)
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def square_preview_bytes(img_bytes: bytes, size: int = PREVIEW_SIZE, bg_rgb=(255, 255, 255)) -> bytes:
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im = Image.open(io.BytesIO(img_bytes)).convert("RGBA")
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w, h = im.size
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new_w, new_h = max(1, int(w * scale)), max(1, int(h * scale))
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im_resized = im.resize((new_w, new_h), Image.LANCZOS)
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canvas = Image.new("RGBA", (size, size), (*bg_rgb, 255))
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buf = io.BytesIO(); canvas.save(buf, format="PNG"); return buf.getvalue()
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def clamp(v: float, lo: float, hi: float) -> float:
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try:
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return max(lo, min(hi, v))
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def first_present(d: dict, keys: list, default=None):
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for k in keys:
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v = d.get(k)
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if v:
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return default
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def show_tile(col, title, url: str | None, bg_rgb=(255,255,255), filename_stub="image", key_prefix=""):
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col.subheader(title)
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if not url:
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placeholder = Image.new("RGBA", (PREVIEW_SIZE, PREVIEW_SIZE), (0,0,0,0))
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col.image(placeholder, use_container_width=True)
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b = fetch_bytes(url)
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if not b:
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col.warning("Görsel yüklenemedi")
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pv = square_preview_bytes(b, size=PREVIEW_SIZE, bg_rgb=bg_rgb)
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col.image(pv, use_container_width=True)
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sz = image_size_from_bytes(b)
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if sz:
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ext = infer_ext(b)
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mime = "image/jpeg" if ext.lower() in [".jpg",".jpeg"] else ("image/png" if ext.lower()==".png" else "image/webp")
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col.download_button(
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return url, b
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def make_zip(named_bytes: list[tuple[str, bytes]]) -> bytes:
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buf = io.BytesIO()
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with zipfile.ZipFile(buf, "w", compression=zipfile.ZIP_DEFLATED) as z:
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for fname, b in named_bytes:
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if b:
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# ================= Sayfa =================
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st.set_page_config(page_title="AI LightBox · Beauty", layout="wide", page_icon="💄")
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# ================= Üst Kontrol Şeridi =================
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ok = backend_ok()
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col1, col2, col3, col4, col5, col6, col7 = st.columns([1.8, 1.6, 1.4, 1.3, 0.9, 1.1, 0.9])
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with col1:
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file_list = st.file_uploader("Product image (upload)", type=["jpg","jpeg","png","webp"], accept_multiple_files=True, key="file_upl")
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with col2:
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image_url = st.text_input("or Product URL", key="image_url")
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with col3:
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category = st.selectbox(
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with col4:
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padding_ratio_val = st.number_input(
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with col5:
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upscale = st.checkbox("Super Resolution", False, key="upscale")
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with col6:
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with col7:
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upscale_factor = st.selectbox("SR factor", ["2","4"], index=0, key="upscale_factor")
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t1, t2, t3, t4 = st.columns([1.15, 1.15, 1.2, 1.5])
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with t1:
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canvas_policy = st.selectbox("Canvas", ["fixed_1200","match_long_edge","keep_input"], index=0, key="canvas_policy")
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with b3:
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identity_lock = st.checkbox("Identity lock", True, key="identity_lock")
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# ============ DEMO PREVIEW (input.jpg & tryon.jpg
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st.markdown("---")
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# ================= Alt kontrol şeridi =================
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cA, cB = st.columns([1.0, 1.0])
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with cA:
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st.info(f"Backend: {'Online' if ok else 'Offline'}", icon="🔌")
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with cB:
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run = st.button("Run", type="primary", use_container_width=True, key="run_btn"
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# ================= Girdi Önizleme
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white_bg = (255, 255, 255)
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input_preview_bytes = None
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if file_list:
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try:
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if input_preview_bytes:
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try:
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sz = Image.open(io.BytesIO(input_preview_bytes)).size
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except Exception:
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else:
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show_tile(
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# ================ Koş & Sonuçları Kaydet ================
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if run:
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if not ok:
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st.error("Backend erişilemiyor. API_BASE / TOKEN kontrol edin.")
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elif not (file_list or
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st.error("En az bir product görseli girin (upload veya URL).")
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else:
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try:
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padding_ratio = clamp(padding_ratio_val, 0.30, 0.95)
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data = {
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"category":
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"edit_prompt": "",
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"num_images": "1",
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"image_urls": (
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"mannequin_image_url": (model_ref_url or ""),
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"padding_ratio": str(padding_ratio),
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"identity_lock": "true" if identity_lock else "false",
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"canvas_size": str(int(canvas_size or 1200)),
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"shade_hex": (shade_hex or "").strip() or None,
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"shade_swatch_url": (shade_swatch_url or "").strip() or None,
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"apply_region":
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"upscale": "true" if upscale else "false",
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"upscale_factor": st.session_state["upscale_factor"],
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"upscale_stage": st.session_state["upscale_stage"],
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packshot_url = None
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try:
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imgs = out["packshot_step"]["result"]["images"]
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if imgs:
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padded_url = None
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try:
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padded_url = out.get("padding_step", {}).get("saved_file")
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if not padded_url:
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pads = out.get("packshot_step", {}).get("padded_urls") or out.get("padded_urls") or []
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if pads:
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packshot_sr_list = first_present(out.get("packshot_step", {}), [
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"upscaled_packshot_urls", "upscaled_packshot_files"
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placed_url = None
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try:
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imgs = out["image_step"]["result"]["images"]
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if imgs:
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final_sr_list = first_present(out.get("image_step", {}), [
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"upscaled_final_urls", "upscaled_final_files"
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"video_url": None,
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"api_base": API_BASE,
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"has_auth_header": bool(HEADERS),
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"
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}
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except requests.HTTPError as e:
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key_prefix = f"job{st.session_state['job_counter']}"
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p_title = "Packshot (SR)" if res.get("packshot_sr_url") else "Packshot"
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p_url, p_bytes = show_tile(
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shown_final_url = res.get("placed_sr_url") or res.get("placed_url")
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m_title = tryon_label(res.get("category","auto"), res.get("apply_region","auto"), bool(res.get("placed_sr_url")))
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m_url, m_bytes = show_tile(
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# ---- Video (final görselden) ----
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st.markdown("---")
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st.warning("Video için final görsel yok.")
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else:
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with st.spinner("Generating video…"):
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v = post_video(
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vurl = (v.get("result") or {}).get("video", {}).get("url")
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if vurl:
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vurl = st.session_state["results"].get("video_url")
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if vurl:
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vb = fetch_bytes(vurl)
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if vb:
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vbytes = vb
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st.download_button(
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else:
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st.info("Video URL var ama içerik indirilemedi.")
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if vbytes: named.append(("video.mp4", vbytes))
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if named:
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zip_bytes = make_zip(named)
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st.download_button(
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with st.expander("Debug"):
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st.json({
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"job_id": res.get("job_id"),
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@@ -471,10 +551,14 @@ with st.sidebar:
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st.caption("Auth header: " + ("ON" if HF_TOKEN else "OFF"))
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if st.button("Ping /health"):
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try:
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-
r = requests.get(f"{API_BASE}/health",
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st.write(r.status_code)
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-
try:
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-
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except Exception as e:
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st.error(f"Health error: {e}")
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if st.button("Clear cache"):
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+
# streamlit_app.py — AI LightBox · Beauty (v0.3 UI)
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# Packshot → Padding (square/canvas) → Try-on (lips/eyes/face/nails/hair/brow/body/lifestyle) · SR · (optional) Video
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import os, io, zipfile, requests, streamlit as st
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from pathlib import Path
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# ================= Env & API (robust) =================
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def _env(k):
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return (os.getenv(k) or "").strip().strip("'\"")
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# Desteklenen env anahtarları (öncelik sırası)
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API_BASE = (
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_env("AI_BEAUTYBOX_API") or
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_env("AI_LIGHTBOX_API") or
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).rstrip("/")
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HF_TOKEN = (
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_env("AI_BEAUTYBOX_TOKEN") or
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_env("AI_LIGHTBOX_TOKEN") or
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_env("BeautyBoxAI_TOKEN") or
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_env("AI_BEAUTY_TOKEN")
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)
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HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"} if HF_TOKEN else {}
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PREVIEW_SIZE = int(os.getenv("PREVIEW_SIZE", "512"))
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# ================= Session State (ilk yükte) =================
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defaults = {
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"results": None,
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"job_counter": 0,
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"duration": "6",
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}
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for k, v in defaults.items():
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if k not in st.session_state:
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REGIONS = ["auto","lips","eyes","face","nails","hand","hair","brow","body","lifestyle"]
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def tryon_label(category: str, region_override: str, sr: bool) -> str:
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# Region override önce gelir
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r = (region_override or "auto").lower()
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if r != "auto":
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base = {
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"lifestyle":"Lifestyle"
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}.get(r, "Try-on")
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return f"{base} (SR)" if sr else base
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+
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c = (category or "auto").lower()
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if c in LIPS: base = "On-Lips"
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elif c in EYES: base = "On-Eyes"
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def _needs_auth(url: str) -> bool:
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return url.startswith(API_BASE) or url.startswith("outputs/")
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@st.cache_data(ttl=300, show_spinner=False)
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def fetch_bytes(url_or_path: str):
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"""URL, outputs/ yolu ya da mevcut klasördeki yerel dosyayı okuyabilir."""
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if not url_or_path:
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return None
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try:
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# 1) Mevcut klasörde yerel dosya?
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p = Path(url_or_path)
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if p.is_file():
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return p.read_bytes()
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# 2) outputs/ için API_BASE ön ekini uygula
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url = f"{API_BASE}/{url_or_path}" if url_or_path.startswith("outputs/") else url_or_path
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headers = (HEADERS if (_needs_auth(url) and HF_TOKEN) else None)
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r = requests.get(url, headers=headers, timeout=180)
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r.raise_for_status()
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return r.content
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except Exception:
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return None
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def backend_ok() -> bool:
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try:
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r = requests.get(f"{API_BASE}/health", headers=HEADERS if HF_TOKEN else None, timeout=10)
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return r.json()
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def post_video(image_url: str, duration="6", resolution="768P", prompt_optimizer=False):
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payload = {
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"image_url": image_url,
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"duration": duration,
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"resolution": resolution,
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"prompt_optimizer": "true" if prompt_optimizer else "false",
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}
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r = requests.post(f"{API_BASE}/v1/video/from-image", data=payload,
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headers=HEADERS if HF_TOKEN else None, timeout=600)
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r.raise_for_status()
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return r.json()
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@st.cache_data(ttl=300, show_spinner=False)
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def image_size_from_bytes(b: bytes):
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try:
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im = Image.open(io.BytesIO(b))
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return im.size
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except Exception:
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return None
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try:
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im = Image.open(io.BytesIO(data))
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fmt = (im.format or "JPEG").lower()
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return "." + {"jpeg": "jpg", "jpg": "jpg", "png": "png", "webp": "webp"}.get(fmt, "jpg")
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except Exception:
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return ".jpg"
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@st.cache_data(ttl=300, show_spinner=False)
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def square_preview_bytes(img_bytes: bytes, size: int = PREVIEW_SIZE, bg_rgb=(255, 255, 255)) -> bytes:
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im = Image.open(io.BytesIO(img_bytes)).convert("RGBA")
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w, h = im.size
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scale = min(size / w, size / h)
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new_w, new_h = max(1, int(w * scale)), max(1, int(h * scale))
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im_resized = im.resize((new_w, new_h), Image.LANCZOS)
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canvas = Image.new("RGBA", (size, size), (*bg_rgb, 255))
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buf = io.BytesIO(); canvas.save(buf, format="PNG"); return buf.getvalue()
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def clamp(v: float, lo: float, hi: float) -> float:
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try:
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v = float(v)
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except Exception:
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v = (lo + hi) / 2.0
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return max(lo, min(hi, v))
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def first_present(d: dict, keys: list, default=None):
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for k in keys:
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v = d.get(k)
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if v:
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return v
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return default
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def show_tile(col, title, url: str | None, bg_rgb=(255,255,255), filename_stub="image", key_prefix=""):
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col.subheader(title)
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if not url:
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placeholder = Image.new("RGBA", (PREVIEW_SIZE, PREVIEW_SIZE), (0, 0, 0, 0))
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col.image(placeholder, use_container_width=True)
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col.caption("—")
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return None, None
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b = fetch_bytes(url)
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if not b:
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col.warning("Görsel yüklenemedi")
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return None, None
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pv = square_preview_bytes(b, size=PREVIEW_SIZE, bg_rgb=bg_rgb)
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col.image(pv, use_container_width=True)
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sz = image_size_from_bytes(b)
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if sz:
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col.caption(f"Gerçek çözünürlük: {sz[0]}×{sz[1]} px")
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ext = infer_ext(b)
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mime = "image/jpeg" if ext.lower() in [".jpg", ".jpeg"] else ("image/png" if ext.lower()==".png" else "image/webp")
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col.download_button(
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"İndir (tam kalite)",
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data=b,
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file_name=f"{filename_stub}{ext}",
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mime=mime,
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key=f"{key_prefix}_{filename_stub}_dl"
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)
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return url, b
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def make_zip(named_bytes: list[tuple[str, bytes]]) -> bytes:
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buf = io.BytesIO()
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with zipfile.ZipFile(buf, "w", compression=zipfile.ZIP_DEFLATED) as z:
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for fname, b in named_bytes:
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if b:
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z.writestr(fname, b)
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buf.seek(0)
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return buf.read()
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# ================= Sayfa =================
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st.set_page_config(page_title="AI LightBox · Beauty", layout="wide", page_icon="💄")
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# ================= Üst Kontrol Şeridi =================
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ok = backend_ok()
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col1, col2, col3, col4, col5, col6, col7 = st.columns([1.8, 1.6, 1.4, 1.3, 0.9, 1.1, 0.9])
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+
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with col1:
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file_list = st.file_uploader("Product image (upload)", type=["jpg","jpeg","png","webp"], accept_multiple_files=True, key="file_upl")
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with col2:
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image_url = st.text_input("or Product URL", key="image_url")
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with col3:
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category = st.selectbox(
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"Category",
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[
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# Lips
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"auto","lipstick","lipgloss","lipliner",
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# Eyes
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"eyeshadow","eyeliner","mascara","brow","false_lashes",
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# Face/complexion
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"foundation","concealer","blush","bronzer","contour","highlighter","body_makeup",
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# Nails
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"nail_polish",
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# Lifestyle
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"skincare","perfume","tools","set",
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# Hair/Body care
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"hair_color","haircare","shampoo","conditioner","body_lotion","body_care",
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],
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index=0, key="category"
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)
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with col4:
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padding_ratio_val = st.number_input(
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"Content scale (0.30–0.95)",
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min_value=0.30, max_value=0.95, value=0.50, step=0.01,
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help="Kare tuvalde ürünün uzun kenarı = tuval × bu oran.",
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key="padding_ratio"
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)
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with col5:
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upscale = st.checkbox("Super Resolution", False, key="upscale")
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with col6:
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with col7:
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upscale_factor = st.selectbox("SR factor", ["2","4"], index=0, key="upscale_factor")
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# == Tuval & Try-on kontrolleri ==
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t1, t2, t3, t4 = st.columns([1.15, 1.15, 1.2, 1.5])
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with t1:
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canvas_policy = st.selectbox("Canvas", ["fixed_1200","match_long_edge","keep_input"], index=0, key="canvas_policy")
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with b3:
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identity_lock = st.checkbox("Identity lock", True, key="identity_lock")
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# ============ DEMO PREVIEW (mevcut klasörden input.jpg & tryon.jpg) ============
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st.markdown("---")
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st.subheader("Demo preview (çalıştırmadan önce örnek)")
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st.caption("Bu bölüm sadece örnektir; aşağıdaki iki görsel mevcut klasörden okunur: input.jpg ve tryon.jpg.")
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d_in, d_pack, d_pad, d_try = st.columns(4)
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# Input preview
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in_bytes = fetch_bytes("input.jpg")
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if in_bytes:
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d_in.subheader("Input")
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d_in.image(square_preview_bytes(in_bytes, size=PREVIEW_SIZE, bg_rgb=(255,255,255)), use_container_width=True)
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sz = image_size_from_bytes(in_bytes)
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if sz:
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d_in.caption(f"Input resolution: {sz[0]}×{sz[1]} px")
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d_in.download_button(
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"İndir (tam kalite)", data=in_bytes,
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file_name=f"input{infer_ext(in_bytes)}",
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mime="image/jpeg", key="demo_input_dl"
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)
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else:
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show_tile(d_in, "Input", None)
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+
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# Packshot & Padded columnları bu demoda boş
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show_tile(d_pack, "Packshot", None)
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show_tile(d_pad, "Padded", None)
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# On-Hair / final try-on preview
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try_bytes = fetch_bytes("tryon.jpg")
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if try_bytes:
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d_try.subheader("On-Hair")
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d_try.image(square_preview_bytes(try_bytes, size=PREVIEW_SIZE, bg_rgb=(255,255,255)), use_container_width=True)
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sz2 = image_size_from_bytes(try_bytes)
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if sz2:
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d_try.caption(f"Gerçek çözünürlük: {sz2[0]}×{sz2[1]} px")
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d_try.download_button(
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"İndir (tam kalite)", data=try_bytes,
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file_name=f"tryon{infer_ext(try_bytes)}",
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mime="image/jpeg", key="demo_tryon_dl"
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)
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else:
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show_tile(d_try, "On-Hair", None)
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# ================= Alt kontrol şeridi =================
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cA, cB = st.columns([1.0, 1.0])
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with cA:
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st.info(f"Backend: {'Online' if ok else 'Offline'}", icon="🔌")
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with cB:
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run = st.button("Run", type="primary", use_container_width=True, key="run_btn")
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# ================= Girdi Önizleme =================
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c_in, c_pack, c_pad, c_try = st.columns(4)
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white_bg = (255, 255, 255)
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input_preview_bytes = None
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if file_list:
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try:
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input_preview_bytes = file_list[0].getvalue()
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except Exception:
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input_preview_bytes = None
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elif image_url:
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input_preview_bytes = fetch_bytes(image_url)
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if input_preview_bytes:
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c_in.subheader("Input")
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c_in.image(square_preview_bytes(input_preview_bytes, size=PREVIEW_SIZE, bg_rgb=white_bg), use_container_width=True)
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try:
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sz = Image.open(io.BytesIO(input_preview_bytes)).size
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c_in.caption(f"Input resolution: {sz[0]}×{sz[1]} px")
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except Exception:
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c_in.caption("—")
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else:
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show_tile(c_in, "Input", None)
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# ================ Koş & Sonuçları Kaydet ================
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if run:
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if not ok:
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st.error("Backend erişilemiyor. API_BASE / TOKEN kontrol edin.")
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+
elif not (file_list or image_url):
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st.error("En az bir product görseli girin (upload veya URL).")
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else:
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try:
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padding_ratio = clamp(padding_ratio_val, 0.30, 0.95)
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data = {
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"category": category,
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"edit_prompt": "",
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"num_images": "1",
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"image_urls": (image_url or ""),
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"mannequin_image_url": (model_ref_url or ""),
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"padding_ratio": str(padding_ratio),
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"identity_lock": "true" if identity_lock else "false",
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+
# Canvas
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"canvas_policy": canvas_policy,
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"canvas_size": str(int(canvas_size or 1200)),
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# Shade / Region
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"shade_hex": (shade_hex or "").strip() or None,
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"shade_swatch_url": (shade_swatch_url or "").strip() or None,
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+
"apply_region": apply_region,
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# SR
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"upscale": "true" if upscale else "false",
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"upscale_factor": st.session_state["upscale_factor"],
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"upscale_stage": st.session_state["upscale_stage"],
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packshot_url = None
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try:
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imgs = out["packshot_step"]["result"]["images"]
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if imgs:
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packshot_url = imgs[0].get("url")
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except Exception:
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pass
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padded_url = None
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try:
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padded_url = out.get("padding_step", {}).get("saved_file")
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if not padded_url:
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pads = out.get("packshot_step", {}).get("padded_urls") or out.get("padded_urls") or []
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if pads:
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padded_url = pads[0]
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except Exception:
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pass
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packshot_sr_list = first_present(out.get("packshot_step", {}), [
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"upscaled_packshot_urls", "upscaled_packshot_files"
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placed_url = None
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try:
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imgs = out["image_step"]["result"]["images"]
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if imgs:
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| 410 |
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placed_url = imgs[0].get("url")
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+
except Exception:
|
| 412 |
+
pass
|
| 413 |
|
| 414 |
final_sr_list = first_present(out.get("image_step", {}), [
|
| 415 |
"upscaled_final_urls", "upscaled_final_files"
|
|
|
|
| 432 |
"video_url": None,
|
| 433 |
"api_base": API_BASE,
|
| 434 |
"has_auth_header": bool(HEADERS),
|
| 435 |
+
# UI state snapshot (etiket/isimlendirme için)
|
| 436 |
+
"category": category,
|
| 437 |
+
"apply_region": apply_region,
|
| 438 |
}
|
| 439 |
|
| 440 |
except requests.HTTPError as e:
|
|
|
|
| 449 |
key_prefix = f"job{st.session_state['job_counter']}"
|
| 450 |
|
| 451 |
p_title = "Packshot (SR)" if res.get("packshot_sr_url") else "Packshot"
|
| 452 |
+
p_url, p_bytes = show_tile(
|
| 453 |
+
c_pack, p_title, res.get("packshot_sr_url") or res.get("packshot_url"),
|
| 454 |
+
bg_rgb=white_bg, filename_stub="packshot", key_prefix=key_prefix
|
| 455 |
+
)
|
| 456 |
+
|
| 457 |
+
pad_url, pad_bytes = show_tile(
|
| 458 |
+
c_pad, "Padded", res.get("padded_url"),
|
| 459 |
+
bg_rgb=white_bg, filename_stub="padded", key_prefix=key_prefix
|
| 460 |
+
)
|
| 461 |
|
| 462 |
shown_final_url = res.get("placed_sr_url") or res.get("placed_url")
|
| 463 |
m_title = tryon_label(res.get("category","auto"), res.get("apply_region","auto"), bool(res.get("placed_sr_url")))
|
| 464 |
+
m_url, m_bytes = show_tile(
|
| 465 |
+
c_try, m_title, shown_final_url,
|
| 466 |
+
bg_rgb=white_bg, filename_stub="tryon", key_prefix=key_prefix
|
| 467 |
+
)
|
| 468 |
|
| 469 |
# ---- Video (final görselden) ----
|
| 470 |
st.markdown("---")
|
|
|
|
| 482 |
st.warning("Video için final görsel yok.")
|
| 483 |
else:
|
| 484 |
with st.spinner("Generating video…"):
|
| 485 |
+
v = post_video(
|
| 486 |
+
src_for_video,
|
| 487 |
+
duration=st.session_state.get("duration_select","6"),
|
| 488 |
+
resolution="768P",
|
| 489 |
+
prompt_optimizer=False
|
| 490 |
+
)
|
| 491 |
vurl = (v.get("result") or {}).get("video", {}).get("url")
|
| 492 |
+
if vurl:
|
| 493 |
+
st.session_state["results"]["video_url"] = vurl
|
| 494 |
+
else:
|
| 495 |
+
st.info("Video URL gelmedi.")
|
| 496 |
|
| 497 |
vurl = st.session_state["results"].get("video_url")
|
| 498 |
if vurl:
|
|
|
|
| 501 |
vb = fetch_bytes(vurl)
|
| 502 |
if vb:
|
| 503 |
vbytes = vb
|
| 504 |
+
st.download_button(
|
| 505 |
+
"Download video (MP4)",
|
| 506 |
+
data=vb,
|
| 507 |
+
file_name="ai_lightbox_video.mp4",
|
| 508 |
+
mime="video/mp4",
|
| 509 |
+
key=f"{key_prefix}_video_dl"
|
| 510 |
+
)
|
| 511 |
else:
|
| 512 |
st.info("Video URL var ama içerik indirilemedi.")
|
| 513 |
|
|
|
|
| 519 |
if vbytes: named.append(("video.mp4", vbytes))
|
| 520 |
if named:
|
| 521 |
zip_bytes = make_zip(named)
|
| 522 |
+
st.download_button(
|
| 523 |
+
"Download all (ZIP)",
|
| 524 |
+
data=zip_bytes,
|
| 525 |
+
file_name="ai_lightbox_beauty_outputs.zip",
|
| 526 |
+
mime="application/zip",
|
| 527 |
+
key=f"{key_prefix}_zip_dl"
|
| 528 |
+
)
|
| 529 |
+
|
| 530 |
+
# Debug
|
| 531 |
with st.expander("Debug"):
|
| 532 |
st.json({
|
| 533 |
"job_id": res.get("job_id"),
|
|
|
|
| 551 |
st.caption("Auth header: " + ("ON" if HF_TOKEN else "OFF"))
|
| 552 |
if st.button("Ping /health"):
|
| 553 |
try:
|
| 554 |
+
r = requests.get(f"{API_BASE}/health",
|
| 555 |
+
headers=HEADERS if HF_TOKEN else None,
|
| 556 |
+
timeout=10)
|
| 557 |
st.write(r.status_code)
|
| 558 |
+
try:
|
| 559 |
+
st.json(r.json())
|
| 560 |
+
except Exception:
|
| 561 |
+
st.code((r.text or "")[:1000])
|
| 562 |
except Exception as e:
|
| 563 |
st.error(f"Health error: {e}")
|
| 564 |
if st.button("Clear cache"):
|