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| # streamlit_app.py — AI LightBox · Beauty (v0.3 UI) | |
| # Packshot → Padding (square/canvas) → Try-on (lips/eyes/face/nails/hair/brow/body/lifestyle) · SR · (optional) Video | |
| import os, io, zipfile, requests, streamlit as st | |
| from PIL import Image | |
| from pathlib import Path | |
| # ================= Env & API (robust) ================= | |
| def _env(k): | |
| return (os.getenv(k) or "").strip().strip("'\"") | |
| # Desteklenen env anahtarları (öncelik sırası) | |
| API_BASE = ( | |
| _env("AI_BEAUTYBOX_API") or | |
| _env("AI_LIGHTBOX_API") or | |
| _env("BeautyBoxAI_API") or | |
| _env("AI_BEAUTY_API") | |
| ).rstrip("/") | |
| HF_TOKEN = ( | |
| _env("AI_BEAUTYBOX_TOKEN") or | |
| _env("AI_LIGHTBOX_TOKEN") or | |
| _env("BeautyBoxAI_TOKEN") or | |
| _env("AI_BEAUTY_TOKEN") | |
| ) | |
| if not API_BASE: | |
| st.error("API_BASE bulunamadı. Settings > Variables: AI_BEAUTYBOX_API veya AI_LIGHTBOX_API tanımlayın.") | |
| st.stop() | |
| HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"} if HF_TOKEN else {} | |
| PREVIEW_SIZE = int(os.getenv("PREVIEW_SIZE", "512")) | |
| # ================= Session State (ilk yükte) ================= | |
| defaults = { | |
| "results": None, | |
| "job_counter": 0, | |
| "duration": "6", | |
| } | |
| for k, v in defaults.items(): | |
| if k not in st.session_state: | |
| st.session_state[k] = v | |
| # ================= Kategori/Region eşleme ================= | |
| LIPS = {"lipstick","lipgloss","lipliner"} | |
| EYES = {"eyeshadow","eyeliner","mascara","brow","false_lashes"} | |
| FACE = {"foundation","concealer","blush","bronzer","contour","highlighter","body_makeup"} | |
| HANDS = {"nail_polish"} | |
| LIFESTYLE = {"skincare","perfume","tools","set","haircare","shampoo","conditioner","body_lotion","body_care"} | |
| HAIR = {"hair_color"} | |
| REGIONS = ["auto","lips","eyes","face","nails","hand","hair","brow","body","lifestyle"] | |
| def tryon_label(category: str, region_override: str, sr: bool) -> str: | |
| # Region override önce gelir | |
| r = (region_override or "auto").lower() | |
| if r != "auto": | |
| base = { | |
| "lips":"On-Lips","eyes":"On-Eyes","face":"On-Face","nails":"On-Nails", | |
| "hand":"On-Hand","hair":"On-Hair","brow":"On-Brows","body":"On-Body", | |
| "lifestyle":"Lifestyle" | |
| }.get(r, "Try-on") | |
| return f"{base} (SR)" if sr else base | |
| c = (category or "auto").lower() | |
| if c in LIPS: base = "On-Lips" | |
| elif c in EYES: base = "On-Eyes" | |
| elif c in HANDS: base = "On-Nails" | |
| elif c in HAIR: base = "On-Hair" | |
| elif c in FACE: base = "On-Face" | |
| elif c in LIFESTYLE: base = "Lifestyle" | |
| else: base = "Try-on" | |
| return f"{base} (SR)" if sr else base | |
| # ================= Yardımcılar ================= | |
| def _needs_auth(url: str) -> bool: | |
| return url.startswith(API_BASE) or url.startswith("outputs/") | |
| def fetch_bytes(url_or_path: str): | |
| """URL, outputs/ yolu ya da mevcut klasördeki yerel dosyayı okuyabilir.""" | |
| if not url_or_path: | |
| return None | |
| try: | |
| # 1) Mevcut klasörde yerel dosya? | |
| p = Path(url_or_path) | |
| if p.is_file(): | |
| return p.read_bytes() | |
| # 2) outputs/ için API_BASE ön ekini uygula | |
| url = f"{API_BASE}/{url_or_path}" if url_or_path.startswith("outputs/") else url_or_path | |
| headers = (HEADERS if (_needs_auth(url) and HF_TOKEN) else None) | |
| r = requests.get(url, headers=headers, timeout=180) | |
| r.raise_for_status() | |
| return r.content | |
| except Exception: | |
| return None | |
| def backend_ok() -> bool: | |
| try: | |
| r = requests.get(f"{API_BASE}/health", headers=HEADERS if HF_TOKEN else None, timeout=10) | |
| r.raise_for_status() | |
| return True | |
| except Exception: | |
| return False | |
| def post_chain(data: dict, files_payload): | |
| data = {**data, "to_video": "false"} | |
| r = requests.post(f"{API_BASE}/v1/tryon/chain", data=data, files=files_payload or None, | |
| headers=HEADERS if HF_TOKEN else None, timeout=600) | |
| r.raise_for_status() | |
| return r.json() | |
| def post_video(image_url: str, duration="6", resolution="768P", prompt_optimizer=False): | |
| payload = { | |
| "image_url": image_url, | |
| "duration": duration, | |
| "resolution": resolution, | |
| "prompt_optimizer": "true" if prompt_optimizer else "false", | |
| } | |
| r = requests.post(f"{API_BASE}/v1/video/from-image", data=payload, | |
| headers=HEADERS if HF_TOKEN else None, timeout=600) | |
| r.raise_for_status() | |
| return r.json() | |
| def image_size_from_bytes(b: bytes): | |
| try: | |
| im = Image.open(io.BytesIO(b)) | |
| return im.size | |
| except Exception: | |
| return None | |
| def infer_ext(data: bytes) -> str: | |
| try: | |
| im = Image.open(io.BytesIO(data)) | |
| fmt = (im.format or "JPEG").lower() | |
| return "." + {"jpeg": "jpg", "jpg": "jpg", "png": "png", "webp": "webp"}.get(fmt, "jpg") | |
| except Exception: | |
| return ".jpg" | |
| def square_preview_bytes(img_bytes: bytes, size: int = PREVIEW_SIZE, bg_rgb=(255, 255, 255)) -> bytes: | |
| im = Image.open(io.BytesIO(img_bytes)).convert("RGBA") | |
| w, h = im.size | |
| scale = min(size / w, size / h) | |
| new_w, new_h = max(1, int(w * scale)), max(1, int(h * scale)) | |
| im_resized = im.resize((new_w, new_h), Image.LANCZOS) | |
| canvas = Image.new("RGBA", (size, size), (*bg_rgb, 255)) | |
| off = ((size - new_w) // 2, (size - new_h) // 2) | |
| canvas.paste(im_resized, off, im_resized) | |
| buf = io.BytesIO(); canvas.save(buf, format="PNG"); return buf.getvalue() | |
| def clamp(v: float, lo: float, hi: float) -> float: | |
| try: | |
| v = float(v) | |
| except Exception: | |
| v = (lo + hi) / 2.0 | |
| return max(lo, min(hi, v)) | |
| def first_present(d: dict, keys: list, default=None): | |
| for k in keys: | |
| v = d.get(k) | |
| if v: | |
| return v | |
| return default | |
| def show_tile(col, title, url: str | None, bg_rgb=(255,255,255), filename_stub="image", key_prefix=""): | |
| col.subheader(title) | |
| if not url: | |
| placeholder = Image.new("RGBA", (PREVIEW_SIZE, PREVIEW_SIZE), (0, 0, 0, 0)) | |
| col.image(placeholder, use_container_width=True) | |
| col.caption("—") | |
| return None, None | |
| b = fetch_bytes(url) | |
| if not b: | |
| col.warning("Görsel yüklenemedi") | |
| return None, None | |
| pv = square_preview_bytes(b, size=PREVIEW_SIZE, bg_rgb=bg_rgb) | |
| col.image(pv, use_container_width=True) | |
| sz = image_size_from_bytes(b) | |
| if sz: | |
| col.caption(f"Gerçek çözünürlük: {sz[0]}×{sz[1]} px") | |
| ext = infer_ext(b) | |
| mime = "image/jpeg" if ext.lower() in [".jpg", ".jpeg"] else ("image/png" if ext.lower()==".png" else "image/webp") | |
| col.download_button( | |
| "İndir (tam kalite)", | |
| data=b, | |
| file_name=f"{filename_stub}{ext}", | |
| mime=mime, | |
| key=f"{key_prefix}_{filename_stub}_dl" | |
| ) | |
| return url, b | |
| def make_zip(named_bytes: list[tuple[str, bytes]]) -> bytes: | |
| buf = io.BytesIO() | |
| with zipfile.ZipFile(buf, "w", compression=zipfile.ZIP_DEFLATED) as z: | |
| for fname, b in named_bytes: | |
| if b: | |
| z.writestr(fname, b) | |
| buf.seek(0) | |
| return buf.read() | |
| # ================= Sayfa ================= | |
| st.set_page_config(page_title="AI LightBox · Beauty", layout="wide", page_icon="💄") | |
| st.title("💄 AI LightBox · Beauty") | |
| st.caption("Packshot → Padding (canvas) → Try-on (lips/eyes/face/nails/hair/brow/body/lifestyle) · Super Resolution · (optional) Video") | |
| # ================= Üst Kontrol Şeridi ================= | |
| ok = backend_ok() | |
| col1, col2, col3, col4, col5, col6, col7 = st.columns([1.8, 1.6, 1.4, 1.3, 0.9, 1.1, 0.9]) | |
| with col1: | |
| file_list = st.file_uploader("Product image (upload)", type=["jpg","jpeg","png","webp"], accept_multiple_files=True, key="file_upl") | |
| with col2: | |
| image_url = st.text_input("or Product URL", key="image_url") | |
| with col3: | |
| category = st.selectbox( | |
| "Category", | |
| [ | |
| # Lips | |
| "auto","lipstick","lipgloss","lipliner", | |
| # Eyes | |
| "eyeshadow","eyeliner","mascara","brow","false_lashes", | |
| # Face/complexion | |
| "foundation","concealer","blush","bronzer","contour","highlighter","body_makeup", | |
| # Nails | |
| "nail_polish", | |
| # Lifestyle | |
| "skincare","perfume","tools","set", | |
| # Hair/Body care | |
| "hair_color","haircare","shampoo","conditioner","body_lotion","body_care", | |
| ], | |
| index=0, key="category" | |
| ) | |
| with col4: | |
| padding_ratio_val = st.number_input( | |
| "Content scale (0.30–0.95)", | |
| min_value=0.30, max_value=0.95, value=0.50, step=0.01, | |
| help="Kare tuvalde ürünün uzun kenarı = tuval × bu oran.", | |
| key="padding_ratio" | |
| ) | |
| with col5: | |
| upscale = st.checkbox("Super Resolution", False, key="upscale") | |
| with col6: | |
| upscale_stage = st.selectbox("SR stage", ["both","final","packshot"], index=0, help="Default: both", key="upscale_stage") | |
| with col7: | |
| upscale_factor = st.selectbox("SR factor", ["2","4"], index=0, key="upscale_factor") | |
| # == Tuval & Try-on kontrolleri == | |
| t1, t2, t3, t4 = st.columns([1.15, 1.15, 1.2, 1.5]) | |
| with t1: | |
| canvas_policy = st.selectbox("Canvas", ["fixed_1200","match_long_edge","keep_input"], index=0, key="canvas_policy") | |
| with t2: | |
| canvas_size = st.number_input("Canvas size (px)", min_value=256, max_value=8192, value=1200, step=64, key="canvas_size") | |
| with t3: | |
| apply_region = st.selectbox("Apply region", REGIONS, index=0, key="apply_region") | |
| with t4: | |
| shade_hex = st.text_input("Shade HEX (optional, e.g. #C6A27A)", value="", key="shade_hex") | |
| b1, b2, b3 = st.columns([1.6, 1.6, 1.0]) | |
| with b1: | |
| shade_swatch_url = st.text_input("Shade swatch URL (optional)", value="", key="shade_swatch_url") | |
| with b2: | |
| model_ref_url = st.text_input("Model image URL (face/hand/eyes/hair/body — optional)", key="face_url") | |
| with b3: | |
| identity_lock = st.checkbox("Identity lock", True, key="identity_lock") | |
| # ============ DEMO PREVIEW (mevcut klasörden input.jpg & tryon.jpg) ============ | |
| st.markdown("---") | |
| st.subheader("Demo preview (çalıştırmadan önce örnek)") | |
| d_in, d_pack, d_pad, d_try = st.columns(4) | |
| # Input preview | |
| in_bytes = fetch_bytes("input.jpg") | |
| if in_bytes: | |
| d_in.subheader("Input") | |
| d_in.image(square_preview_bytes(in_bytes, size=PREVIEW_SIZE, bg_rgb=(255,255,255)), use_container_width=True) | |
| sz = image_size_from_bytes(in_bytes) | |
| if sz: | |
| d_in.caption(f"Input resolution: {sz[0]}×{sz[1]} px") | |
| d_in.download_button( | |
| "İndir (tam kalite)", data=in_bytes, | |
| file_name=f"input{infer_ext(in_bytes)}", | |
| mime="image/jpeg", key="demo_input_dl" | |
| ) | |
| else: | |
| show_tile(d_in, "Input", None) | |
| # Packshot & Padded columnları bu demoda boş | |
| show_tile(d_pack, "Packshot", None) | |
| show_tile(d_pad, "Padded", None) | |
| # On-Hair / final try-on preview | |
| try_bytes = fetch_bytes("tryon.jpg") | |
| if try_bytes: | |
| d_try.subheader("On-Hair") | |
| d_try.image(square_preview_bytes(try_bytes, size=PREVIEW_SIZE, bg_rgb=(255,255,255)), use_container_width=True) | |
| sz2 = image_size_from_bytes(try_bytes) | |
| if sz2: | |
| d_try.caption(f"Gerçek çözünürlük: {sz2[0]}×{sz2[1]} px") | |
| d_try.download_button( | |
| "İndir (tam kalite)", data=try_bytes, | |
| file_name=f"tryon{infer_ext(try_bytes)}", | |
| mime="image/jpeg", key="demo_tryon_dl" | |
| ) | |
| else: | |
| show_tile(d_try, "On-Hair", None) | |
| # ================= Alt kontrol şeridi ================= | |
| cA, cB = st.columns([1.0, 1.0]) | |
| with cA: | |
| st.info(f"Backend: {'Online' if ok else 'Offline'}", icon="🔌") | |
| with cB: | |
| run = st.button("Run", type="primary", use_container_width=True, key="run_btn") | |
| # ================= Girdi Önizleme ================= | |
| c_in, c_pack, c_pad, c_try = st.columns(4) | |
| white_bg = (255, 255, 255) | |
| input_preview_bytes = None | |
| if file_list: | |
| try: | |
| input_preview_bytes = file_list[0].getvalue() | |
| except Exception: | |
| input_preview_bytes = None | |
| elif image_url: | |
| input_preview_bytes = fetch_bytes(image_url) | |
| if input_preview_bytes: | |
| c_in.subheader("Input") | |
| c_in.image(square_preview_bytes(input_preview_bytes, size=PREVIEW_SIZE, bg_rgb=white_bg), use_container_width=True) | |
| try: | |
| sz = Image.open(io.BytesIO(input_preview_bytes)).size | |
| c_in.caption(f"Input resolution: {sz[0]}×{sz[1]} px") | |
| except Exception: | |
| c_in.caption("—") | |
| else: | |
| show_tile(c_in, "Input", None) | |
| # ================ Koş & Sonuçları Kaydet ================ | |
| if run: | |
| if not ok: | |
| st.error("Backend erişilemiyor. API_BASE / TOKEN kontrol edin.") | |
| elif not (file_list or image_url): | |
| st.error("En az bir product görseli girin (upload veya URL).") | |
| else: | |
| try: | |
| padding_ratio = clamp(padding_ratio_val, 0.30, 0.95) | |
| data = { | |
| "category": category, | |
| "edit_prompt": "", | |
| "num_images": "1", | |
| "image_urls": (image_url or ""), | |
| "mannequin_image_url": (model_ref_url or ""), | |
| "padding_ratio": str(padding_ratio), | |
| "identity_lock": "true" if identity_lock else "false", | |
| # Canvas | |
| "canvas_policy": canvas_policy, | |
| "canvas_size": str(int(canvas_size or 1200)), | |
| # Shade / Region | |
| "shade_hex": (shade_hex or "").strip() or None, | |
| "shade_swatch_url": (shade_swatch_url or "").strip() or None, | |
| "apply_region": apply_region, | |
| # SR | |
| "upscale": "true" if upscale else "false", | |
| "upscale_factor": st.session_state["upscale_factor"], | |
| "upscale_stage": st.session_state["upscale_stage"], | |
| } | |
| files_payload = [] | |
| if file_list: | |
| for f in file_list: | |
| files_payload.append(("files", (f.name, f.getvalue(), f.type or "image/jpeg"))) | |
| with st.spinner("Running chain…"): | |
| out = post_chain(data, files_payload) | |
| # ---- Çıktıları topla ---- | |
| packshot_url = None | |
| try: | |
| imgs = out["packshot_step"]["result"]["images"] | |
| if imgs: | |
| packshot_url = imgs[0].get("url") | |
| except Exception: | |
| pass | |
| padded_url = None | |
| try: | |
| padded_url = out.get("padding_step", {}).get("saved_file") | |
| if not padded_url: | |
| pads = out.get("packshot_step", {}).get("padded_urls") or out.get("padded_urls") or [] | |
| if pads: | |
| padded_url = pads[0] | |
| except Exception: | |
| pass | |
| packshot_sr_list = first_present(out.get("packshot_step", {}), [ | |
| "upscaled_packshot_urls", "upscaled_packshot_files" | |
| ], default=[]) or [] | |
| packshot_sr_url = packshot_sr_list[0] if packshot_sr_list else None | |
| placed_url = None | |
| try: | |
| imgs = out["image_step"]["result"]["images"] | |
| if imgs: | |
| placed_url = imgs[0].get("url") | |
| except Exception: | |
| pass | |
| final_sr_list = first_present(out.get("image_step", {}), [ | |
| "upscaled_final_urls", "upscaled_final_files" | |
| ], default=[]) or [] | |
| placed_sr_url = final_sr_list[0] if final_sr_list else None | |
| st.session_state["job_counter"] += 1 | |
| st.session_state["results"] = { | |
| "job_id": out.get("job_id"), | |
| "schema_version": out.get("schema_version"), | |
| "final_canvas": ( | |
| out.get("packshot_step", {}).get("final_canvas") | |
| or out.get("padding_step", {}).get("final_canvas") | |
| ), | |
| "packshot_url": packshot_url, | |
| "packshot_sr_url": packshot_sr_url, | |
| "padded_url": padded_url, | |
| "placed_url": placed_url, | |
| "placed_sr_url": placed_sr_url, | |
| "video_url": None, | |
| "api_base": API_BASE, | |
| "has_auth_header": bool(HEADERS), | |
| # UI state snapshot (etiket/isimlendirme için) | |
| "category": category, | |
| "apply_region": apply_region, | |
| } | |
| except requests.HTTPError as e: | |
| st.error(f"HTTP {e.response.status_code}") | |
| except Exception as e: | |
| st.error(f"Hata: {e}") | |
| # ================ Sonuçları Göster (kalıcı) ================ | |
| res = st.session_state.get("results") | |
| vbytes = None | |
| if res: | |
| key_prefix = f"job{st.session_state['job_counter']}" | |
| p_title = "Packshot (SR)" if res.get("packshot_sr_url") else "Packshot" | |
| p_url, p_bytes = show_tile( | |
| c_pack, p_title, res.get("packshot_sr_url") or res.get("packshot_url"), | |
| bg_rgb=white_bg, filename_stub="packshot", key_prefix=key_prefix | |
| ) | |
| pad_url, pad_bytes = show_tile( | |
| c_pad, "Padded", res.get("padded_url"), | |
| bg_rgb=white_bg, filename_stub="padded", key_prefix=key_prefix | |
| ) | |
| shown_final_url = res.get("placed_sr_url") or res.get("placed_url") | |
| m_title = tryon_label(res.get("category","auto"), res.get("apply_region","auto"), bool(res.get("placed_sr_url"))) | |
| m_url, m_bytes = show_tile( | |
| c_try, m_title, shown_final_url, | |
| bg_rgb=white_bg, filename_stub="tryon", key_prefix=key_prefix | |
| ) | |
| # ---- Video (final görselden) ---- | |
| st.markdown("---") | |
| colv1, colv2, colv3 = st.columns([1.1, 1.0, 1.2]) | |
| with colv1: | |
| gen_video = st.checkbox("Generate video from this result", value=False, key="video_toggle") | |
| with colv2: | |
| st.selectbox("Video sec", ["6","10"], index=(0 if st.session_state["duration"]=="6" else 1), key="duration_select") | |
| with colv3: | |
| go_video = st.button("Create video", use_container_width=True, key="video_btn") | |
| if gen_video and go_video: | |
| src_for_video = res.get("placed_sr_url") or res.get("placed_url") | |
| if not src_for_video: | |
| st.warning("Video için final görsel yok.") | |
| else: | |
| with st.spinner("Generating video…"): | |
| v = post_video( | |
| src_for_video, | |
| duration=st.session_state.get("duration_select","6"), | |
| resolution="768P", | |
| prompt_optimizer=False | |
| ) | |
| vurl = (v.get("result") or {}).get("video", {}).get("url") | |
| if vurl: | |
| st.session_state["results"]["video_url"] = vurl | |
| else: | |
| st.info("Video URL gelmedi.") | |
| vurl = st.session_state["results"].get("video_url") | |
| if vurl: | |
| st.subheader("Video") | |
| st.video(vurl, format="video/mp4") | |
| vb = fetch_bytes(vurl) | |
| if vb: | |
| vbytes = vb | |
| st.download_button( | |
| "Download video (MP4)", | |
| data=vb, | |
| file_name="ai_lightbox_video.mp4", | |
| mime="video/mp4", | |
| key=f"{key_prefix}_video_dl" | |
| ) | |
| else: | |
| st.info("Video URL var ama içerik indirilemedi.") | |
| # ---- ZIP indir ---- | |
| named = [] | |
| if p_bytes: named.append((f"packshot{infer_ext(p_bytes)}", p_bytes)) | |
| if pad_bytes: named.append((f"padded{infer_ext(pad_bytes)}", pad_bytes)) | |
| if m_bytes: named.append((f"tryon{infer_ext(m_bytes)}", m_bytes)) | |
| if vbytes: named.append(("video.mp4", vbytes)) | |
| if named: | |
| zip_bytes = make_zip(named) | |
| st.download_button( | |
| "Download all (ZIP)", | |
| data=zip_bytes, | |
| file_name="ai_lightbox_beauty_outputs.zip", | |
| mime="application/zip", | |
| key=f"{key_prefix}_zip_dl" | |
| ) | |
| # Debug | |
| with st.expander("Debug"): | |
| st.json({ | |
| "job_id": res.get("job_id"), | |
| "schema_version": res.get("schema_version"), | |
| "final_canvas": res.get("final_canvas"), | |
| "api_base": res.get("api_base"), | |
| "has_auth_header": res.get("has_auth_header"), | |
| "category": res.get("category"), | |
| "apply_region": res.get("apply_region"), | |
| "packshot_url": res.get("packshot_url"), | |
| "packshot_sr_url": res.get("packshot_sr_url"), | |
| "padded_url": res.get("padded_url"), | |
| "placed_url": res.get("placed_url"), | |
| "placed_sr_url": res.get("placed_sr_url"), | |
| "video_url": res.get("video_url"), | |
| }) | |
| # ================= Sidebar (teşhis) ================= | |
| with st.sidebar: | |
| st.caption(f"Resolved API_BASE: {API_BASE}") | |
| st.caption("Auth header: " + ("ON" if HF_TOKEN else "OFF")) | |
| if st.button("Ping /health"): | |
| try: | |
| r = requests.get(f"{API_BASE}/health", | |
| headers=HEADERS if HF_TOKEN else None, | |
| timeout=10) | |
| st.write(r.status_code) | |
| try: | |
| st.json(r.json()) | |
| except Exception: | |
| st.code((r.text or "")[:1000]) | |
| except Exception as e: | |
| st.error(f"Health error: {e}") | |
| if st.button("Clear cache"): | |
| st.cache_data.clear(); st.success("Cache cleared.") | |
| if st.button("Clear results"): | |
| st.session_state["results"] = None; st.success("Results cleared.") | |