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from deepface import DeepFace
from PIL import Image
import insightface
import numpy as np
def extract_face_prompt(img_path):
# Load image as numpy array
img = Image.open(img_path).convert("RGB")
img_np = np.array(img)
# DeepFace analysis
deepface_result = DeepFace.analyze(
img_path, actions=['age', 'gender', 'race', 'emotion'], enforce_detection=False
)
age = deepface_result['age']
gender = deepface_result['dominant_gender']
race = deepface_result['dominant_race']
emotion = deepface_result['dominant_emotion']
# InsightFace analysis
model = insightface.app.FaceAnalysis(name='buffalo_l', providers=['CPUExecutionProvider'])
model.prepare(ctx_id=0)
faces = model.get(img_np)
face_attrs = {}
if faces:
face = faces[0]
face_attrs['glasses'] = face.get('glass', 0) > 0
face_attrs['beard'] = face.get('beard', 0) > 0
face_attrs['mustache'] = face.get('mustache', 0) > 0
attr_parts = []
if face_attrs.get('glasses'):
attr_parts.append("wearing glasses")
if face_attrs.get('beard'):
attr_parts.append("has a beard")
if face_attrs.get('mustache'):
attr_parts.append("has a mustache")
attr_str = ", ".join(attr_parts) if attr_parts else ""
prompt = (
f"A chibi-style digital sticker of a {gender.lower()} with {race} skin, "
f"{'smiling' if emotion=='happy' else emotion}, approximately {age} years old"
)
if attr_str:
prompt += f", {attr_str}"
prompt += ", closeup, cute, expressive face, white outline, transparent background"
return prompt
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