change a alot
This commit is contained in:
parent
78a0579039
commit
bf34ce90c5
252
main.py
252
main.py
@ -28,6 +28,7 @@ if not GEMINI_API_KEY:
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raise RuntimeError("GEMINI_API_KEY not set")
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IMAGE_MODEL = "gemini-2.5-flash-image"
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IDENTITY_MODEL = "gemini-1.5-flash" # text/vision model for identity check
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AUTH_KEY = os.getenv("AIFIT_AUTH_KEY")
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@ -79,6 +80,76 @@ def find_first_image_part(resp):
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return None
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def faces_match_strict(original_bytes: bytes, edited_bytes: bytes) -> bool:
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"""
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Second Gemini call: compare ORIGINAL vs EDITED and decide
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if identity/face has changed. Returns True if it's clearly
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the same person, False otherwise.
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"""
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try:
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original_part = Part.from_bytes(
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data=original_bytes,
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mime_type="image/jpeg",
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)
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edited_part = Part.from_bytes(
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data=edited_bytes,
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mime_type="image/png",
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)
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prompt = """
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You are an identity consistency checker.
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You receive TWO photos:
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- FIRST: original_user (the real human photo from the user)
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- SECOND: generated_tryon (the AI-edited try-on result)
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Task:
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1. Decide if the TWO images clearly show the SAME PERSON.
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2. Focus on:
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- overall facial structure and proportions
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- jawline, chin, cheekbones
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- nose shape
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- eye / brow region
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- beard/moustache presence, shape, and density
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- hairline and hairstyle
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3. Ignore clothing changes. We ONLY care about whether the face/identity changed.
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Instructions:
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- If the SECOND image looks like a different model, or the face/identity is noticeably altered
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(different jaw, nose, beard, hairline, etc.), you MUST treat it as a DIFFERENT person.
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- Do NOT be generous. If you are not sure, assume the identity has changed.
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Output format:
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Answer with EXACTLY ONE WORD:
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- "OK" → clearly the same person, acceptable tiny rendering noise
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- "CHANGE" → different person OR visibly altered identity
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No explanations. No extra text.
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"""
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resp = client.models.generate_content(
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model=IDENTITY_MODEL,
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contents=[prompt, original_part, edited_part],
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)
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text = ""
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if getattr(resp, "candidates", None):
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cand = resp.candidates[0]
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if hasattr(cand, "content") and getattr(cand.content, "parts", None):
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for part in cand.content.parts:
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if getattr(part, "text", None):
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text += part.text
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answer = (text or "").strip().upper()
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print(f"[DEBUG] Identity check raw answer: {answer!r}")
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return answer == "OK"
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except Exception as e:
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# If identity check fails for any reason, be SAFE and treat as mismatch
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print(f"[ERROR] Identity check failed: {e!r}")
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return False
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@app.get("/health")
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def health():
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return {"status": "ok"}
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@ -102,9 +173,7 @@ async def try_on(
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if AUTH_KEY:
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client_key = request.headers.get("X-AIFIT-Key")
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if not client_key or client_key != AUTH_KEY:
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raise HTTPException(
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status_code=401, detail="Invalid or missing authentication key"
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)
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raise HTTPException(status_code=401, detail="Invalid or missing authentication key")
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# ---- Read files ----
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user_bytes = await user_photo.read()
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@ -126,17 +195,13 @@ async def try_on(
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metadata_text = json.dumps(meta, indent=2, ensure_ascii=False)
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# Try common key names for the UUID
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request_id = (
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meta.get("request_id") or meta.get("id") or meta.get("uuid")
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)
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request_id = meta.get("request_id") or meta.get("id") or meta.get("uuid")
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# ---- Dynamic behavior based on bottom/top type ----
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extra_sections = []
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# Bottom: shorts
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bottom = meta.get("bottom") or {}
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bottom_type = (bottom.get("type") or "").lower()
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if bottom_type == "shorts":
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extra_sections.append(
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"""
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@ -155,18 +220,9 @@ SPECIAL RULE FOR SHORTS (INSANELY STRICT, ZERO TOLERANCE – DO NOT IGNORE):
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)
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# Top: t-shirt / tee / short-sleeve
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top = (
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meta.get("top")
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or meta.get("upper")
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or meta.get("outer_layer")
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or {}
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)
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top = meta.get("top") or meta.get("inner_layer") or meta.get("upper") or meta.get("outer_layer") or {}
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top_type = (top.get("type") or "").lower()
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if any(
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token in top_type
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for token in ["t-shirt", "tshirt", "tee", "t shirt"]
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):
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if any(token in top_type for token in ["t-shirt", "tshirt", "tee", "t shirt"]):
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extra_sections.append(
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"""
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SPECIAL RULE FOR T-SHIRT / TOP (EXTREMELY STRICT, ZERO TOLERANCE):
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@ -192,7 +248,7 @@ SPECIAL RULE FOR T-SHIRT / TOP (EXTREMELY STRICT, ZERO TOLERANCE):
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except Exception:
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metadata_text = metadata.strip()
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# ---- Build Prompt (new, ultra strict version) ----
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# ---- Build Prompt (strict identity + clothing) ----
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prompt = f"""
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You are performing a **strict outfit replacement operation** on the FIRST image using the clothing and accessories from the SECOND image and the metadata provided.
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@ -217,7 +273,6 @@ These identity rules are STRONGER than all other instructions. If you cannot fol
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• lips and mouth shape
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• facial hair (beard / moustache) style and density
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• hair style and hairline
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• ears
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• body proportions
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• pose
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EXACTLY as they are.
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@ -227,33 +282,9 @@ ABSOLUTE FACE LOCK (READ-ONLY REGION):
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- Treat the entire face, head, ears, and visible neck area of the FIRST image as a **READ-ONLY REGION**.
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- You MUST NOT re-render, redraw, regenerate, beautify, smooth, reshape, de-age, re-gender,
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or otherwise alter the face in any way.
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- You MUST NOT change:
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• beard thickness or shape
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• moustache presence or shape
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• hairline or hairstyle
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• skin texture or tone on the face
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• teeth alignment or smile shape
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- The face region in the final image must be **indistinguishable** from the original FIRST image,
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except for tiny unavoidable differences at the clothing boundaries (e.g. collar touching neck).
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IDENTITY FAILURE CONDITION:
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- If completing the clothing replacement would require you to change the user's face, head,
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or identity in any way, you MUST NOT generate an image.
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- In that situation, you must respond with TEXT ONLY explaining that identity rules prevented
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you from generating an image.
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- You are not allowed to "approximate" the face. Either:
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• keep the original face exactly, OR
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• do not output an image at all.
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- You are **FORBIDDEN** to:
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• change the face or body of the person in the FIRST image,
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• beautify, smooth, reshape, de-age, re-gender, or re-style the face,
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• swap the person with someone else,
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• blend or mix the FIRST and SECOND person,
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• recreate a new face that only "resembles" the original,
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• copy the second person's moustache, beard, jawline, nose, or hairstyle.
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If there is ANY conflict between clothing instructions and identity protection:
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YOU MUST PROTECT THE FIRST PERSON'S IDENTITY and only adjust clothing areas.
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If identity cannot be preserved, DO NOT generate an image.
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@ -293,47 +324,12 @@ The replacement must be:
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- Seamlessly integrated
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- Physically correct
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If you leave **ANY** part of the original outfit visible in an area that should be replaced,
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the result is considered **WRONG and FAILED**.
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-----------------------------------------------------
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👤 DO NOT CHANGE ANYTHING ABOUT THE USER (FIRST IMAGE)
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Strictly preserve:
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- Face and identity (see ABSOLUTE FACE LOCK above)
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- Skin tone
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- Hair
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- Expression
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- Body proportions
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- Pose
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- Hands
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- Phone
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- Non-clothing jewelry
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- Background and environment
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- Lighting and shadows
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- Camera angle, framing, and composition
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- Depth of field and bokeh
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The edited image must look like the same person photographed in the same moment, but wearing the uploaded outfit.
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-----------------------------------------------------
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👕 OUTFIT SOURCES YOU MUST FOLLOW
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You MUST use BOTH sources:
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1) SECOND IMAGE (OUTFIT PHOTO) – PRIMARY VISUAL SOURCE
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- Carefully inspect ALL clothing and accessories.
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- Transfer EVERY clothing item visible in the outfit photo to the user:
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• Outer layers (jackets, hoodies, coats)
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• Inner layers (shirts, t-shirts, tops)
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• Bottoms (pants, shorts, skirts)
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• Footwear
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• Accessories (hats, glasses, glasses holder strap around the neck, necklaces, etc.)
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- Copy exactly:
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• Colors and hues (no tinting)
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• Patterns and their scale (no warping or stretching)
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• Textures, weave, and material type
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• Stitching, seams, hems, cuffs, collars, zippers, buttons, pockets, labels, prints, logos, trims
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• Shape, silhouette, and fabric density
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- Transfer EVERY clothing item visible in the outfit photo.
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2) METADATA (DESCRIPTIVE SOURCE AND HARD CHECKLIST)
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The following metadata describes the outfit and items:
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@ -342,57 +338,7 @@ You MUST use BOTH sources:
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{extra_rules}
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You MUST treat the metadata as a **STRICT CHECKLIST**:
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- Every clothing item described in metadata that differs from the FIRST image MUST be updated in the final image.
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- Do NOT skip or ignore ANY listed item (top, bottom, shoes, accessories, straps, etc.).
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- If something is mentioned in metadata for replacement and you leave the original visible,
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the result is **INCORRECT**.
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- Use metadata to:
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• Confirm all clothing layers and components.
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• Ensure no item mentioned in metadata is forgotten.
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• Validate colors, patterns, and materials.
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• Resolve ambiguous details from the outfit photo.
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- If metadata mentions items not clearly visible, prefer the metadata description,
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but do NOT invent a style that contradicts the outfit photo.
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3) COMBINED BEHAVIOR
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- Outfit photo is the main visual truth.
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- Metadata is the strict checklist and description to avoid missing items.
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- The final result MUST:
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• Include ALL clothing and accessories visible in the outfit photo.
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• Include ALL relevant items mentioned in metadata that are consistent with the outfit photo.
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• Remove the original garments completely wherever replacement is implied.
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-----------------------------------------------------
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🧵 STRICT CLOTHING REPLACEMENT RULES
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1. REMOVE original clothing completely from the FIRST image before placing replacements.
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- No underlayers or ghost fabrics.
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- No visible seams, colors, or textures from the old outfit.
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2. APPLY the new outfit exactly as shown in the SECOND image:
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- Perfect color match (no hue or saturation shift).
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- Original pattern scale and orientation.
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- Correct sleeve length, collar height, garment length, and silhouette.
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- Only scale garments enough to fit the body while preserving pattern proportions.
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3. NATURAL, PHYSICS-AWARE FIT:
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- Fabric drapes according to gravity and the model’s pose.
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- Folds and creases look realistic but do NOT distort patterns or design.
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4. PERFECT INTEGRATION:
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- Lighting and reflections must match the original scene.
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- Contact shadows and occlusion must be consistent.
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- No haloing, floating edges, or mismatched shadow direction.
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5. ACCESSORIES:
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- Apply all visible accessories from the outfit photo.
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- If metadata mentions a glasses holder strap around the neck, it must appear naturally placed
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according to anatomy and perspective.
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6. NO NEW DESIGN ELEMENTS:
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- Do NOT invent new zippers, seams, logos, or prints.
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- Do NOT remove real logos or prints that exist on the uploaded outfit unless clearly obstructed.
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Treat metadata as a strict checklist: any item marked for change MUST be changed.
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-----------------------------------------------------
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📸 PHOTOREALISM REQUIREMENTS
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@ -400,17 +346,17 @@ You MUST use BOTH sources:
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- Maintain original exposure, contrast, and white balance.
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- Preserve original depth of field (DOF) and perspective.
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- Do NOT stylize, cartoonize, or apply filters.
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- Avoid blurring, smoothing, or “AI look”.
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- Avoid blurring, smoothing, or "AI look".
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- The final render must look like a real photo from the same camera and setup.
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-----------------------------------------------------
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🚫 FORBIDDEN ACTIONS
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- Do NOT alter the user’s face, identity, or body.
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- Do NOT alter the user's face, identity, or body.
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- Do NOT change background, environment, camera angle, or lighting direction.
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- Do NOT add or remove body parts or tattoos.
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- Do NOT generate a different model.
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- Do NOT copy the second person’s face or body.
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- Do NOT copy the second person's face or body.
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- Do NOT output multiple images or side-by-side comparisons.
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- Do NOT output any text in the image.
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- Do NOT ignore the outfit photo or metadata.
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@ -423,9 +369,6 @@ Generate ONE single high-resolution, hyper-realistic edited image where:
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- All clothing and accessories are replaced according to the outfit photo and metadata.
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- The person, pose, background, and scene remain identical except for clothes and accessories.
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If you cannot satisfy the IDENTITY LOCK and ABSOLUTE FACE LOCK rules,
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you MUST NOT generate an image and should respond with TEXT ONLY explaining why.
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FIRST image = user_photo (to edit).
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SECOND image = outfit_photo (outfit reference).
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"""
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@ -440,8 +383,8 @@ SECOND image = outfit_photo (outfit reference).
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mime_type=outfit_photo.content_type or "image/jpeg",
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)
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# ---- Call Gemini ----
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print(f"\n[DEBUG] Using model: {IMAGE_MODEL}")
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# ---- Call Gemini (image model) ----
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print(f"\n[DEBUG] Using image model: {IMAGE_MODEL}")
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print(f"[DEBUG] Metadata received: {metadata[:200] if metadata else '(empty)'}")
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try:
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@ -456,11 +399,7 @@ SECOND image = outfit_photo (outfit reference).
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)
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except Exception as e:
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error_msg = str(e)
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if (
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"API key" in error_msg
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or "INVALID_ARGUMENT" in error_msg
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or "API_KEY" in error_msg
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):
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if "API key" in error_msg or "INVALID_ARGUMENT" in error_msg or "API_KEY" in error_msg:
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raise HTTPException(
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status_code=401,
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detail=(
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@ -469,7 +408,6 @@ SECOND image = outfit_photo (outfit reference).
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),
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)
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import traceback
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print(f"[ERROR] Gemini API error: {error_msg}")
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print(traceback.format_exc())
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raise HTTPException(status_code=502, detail=f"Gemini error: {error_msg}")
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@ -486,9 +424,7 @@ SECOND image = outfit_photo (outfit reference).
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print(f"[DEBUG] Safety ratings: {getattr(cand, 'safety_ratings', None)}")
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if hasattr(cand, "content") and getattr(cand.content, "parts", None):
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print(
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f"[DEBUG] Parts in first candidate ({len(cand.content.parts)} total):"
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)
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print(f"[DEBUG] Parts in first candidate ({len(cand.content.parts)} total):")
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for i, part in enumerate(cand.content.parts):
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part_type = type(part).__name__
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print(f" Part {i}: type={part_type}")
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@ -502,9 +438,7 @@ SECOND image = outfit_photo (outfit reference).
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if inline:
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data_size = len(getattr(inline, "data", b""))
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mime = getattr(inline, "mime_type", "unknown")
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print(
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f" INLINE_DATA: mime={mime}, size={data_size} bytes"
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)
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print(f" INLINE_DATA: mime={mime}, size={data_size} bytes")
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if hasattr(part, "blob"):
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blob = part.blob
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@ -553,7 +487,7 @@ SECOND image = outfit_photo (outfit reference).
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raw = img_part.data
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# Ensure valid image
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# Ensure valid image bytes
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try:
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Image.open(BytesIO(raw))
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except Exception as e:
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@ -562,6 +496,18 @@ SECOND image = outfit_photo (outfit reference).
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detail=f"Returned image is invalid: {e}. Image size: {len(raw)} bytes",
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)
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# ---- SECOND CALL: IDENTITY VALIDATION ----
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print("[DEBUG] Running identity consistency check...")
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same_identity = faces_match_strict(user_bytes, raw)
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print(f"[DEBUG] Identity check result: same_identity={same_identity}")
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if not same_identity:
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# Hard fail: we do NOT return the image if identity changed
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raise HTTPException(
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status_code=502,
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detail="Model changed user identity; try-on result rejected by identity guard.",
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)
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headers = {}
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if request_id:
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headers["X-TryOn-Request-Id"] = str(request_id)
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30
prompts/identity_check_prompt.txt
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30
prompts/identity_check_prompt.txt
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@ -0,0 +1,30 @@
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You are an identity-protection validator.
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You receive two images:
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1. original_user: the original human photo from the user (this identity must NEVER change)
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2. generated_tryon: the try-on output image generated by another model
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Your job:
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- Compare faces
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- Compare facial structure, beard, hairline, skin tone, nose shape, jaw shape
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- Check if the generated image kept the SAME identity
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- Detect if the AI replaced the face with a model
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- Detect if the AI adjusted or beautified the face too much
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- Detect if body proportions changed unnaturally
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Return STRICT JSON ONLY:
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{
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"identity_match_score": 0–100,
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"identity_changed": true/false,
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"reason": "string explaining mismatch",
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"safe_to_use": true/false
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}
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Rules:
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- If identity_match_score < 85 → identity_changed must be true
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- If anything seems suspicious → safe_to_use must be false
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- No extra text, no explanations outside the JSON
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Loading…
Reference in New Issue
Block a user