{"id":521,"date":"2025-12-29T10:21:47","date_gmt":"2025-12-29T02:21:47","guid":{"rendered":"https:\/\/seantang.cn\/?p=521"},"modified":"2025-12-29T15:26:16","modified_gmt":"2025-12-29T07:26:16","slug":"face-scan","status":"publish","type":"post","link":"https:\/\/seantang.cn\/?p=521","title":{"rendered":"Face Scan"},"content":{"rendered":"\n

Python<\/strong>
python -m venv face_scan
face_scan\\Scripts\\activate<\/p>\n\n\n\n

\u5b89\u88c5\u4f9d\u8d56\uff08GPU \u7248\uff09<\/strong>
pip install –upgrade pip
pip install insightface onnxruntime-gpu opencv-python numpy tqdm<\/p>\n\n\n\n

\u51c6\u5907\u672c\u4eba\u7684\u4eba\u8138\u7279\u5f81<\/strong>
1. \u76ee\u5f55\u7ed3\u6784\u5efa\u8bae<\/p>\n\n\n\n

project\/ \u2502
\u251c\u2500 me\/ # \u653e\u4f60\u7684 5\u201310 \u5f20\u4e2a\u4eba\u7167\u7247
\u2502 \u251c\u2500 1.jpg
\u2502 \u251c\u2500 2.jpg
\u251c\u2500 scan_and_copy.py
\u251c\u2500 my_face.npy<\/p>\n\n\n\n

\u751f\u6210\u4eba\u8138\u7279\u5f81\uff08\u4e00\u6b21\u6027\u6267\u884c\uff09<\/strong>
import cv2
import numpy as np
from insightface.app import FaceAnalysis
from pathlib import Path<\/p>\n\n\n\n

app = FaceAnalysis(name=”buffalo_l”, providers=[“CUDAExecutionProvider”])
app.prepare(ctx_id=0, det_size=(640, 640))<\/p>\n\n\n\n

embeddings = []<\/p>\n\n\n\n

for img_path in Path(“me”).glob(“*”):
img = cv2.imread(str(img_path))
faces = app.get(img)
if faces:
embeddings.append(faces[0].embedding)<\/p>\n\n\n\n

if not embeddings:
raise RuntimeError(“\u672a\u68c0\u6d4b\u5230\u4f60\u7684\u4eba\u8138”)<\/p>\n\n\n\n

my_face = np.mean(embeddings, axis=0)
np.save(“my_face.npy”, my_face)
print(“\u672c\u4eba\u7279\u5f81\u5df2\u751f\u6210\uff1amy_face.npy”)<\/p>\n\n\n\n

\u626b\u63cf\u6587\u4ef6\u5939\u5e76\u62f7\u8d1d\u9ad8\u5ea6\u7591\u4f3c\u672c\u4eba\u7167\u7247<\/strong>
import os
import shutil
import cv2
import numpy as np
from insightface.app import FaceAnalysis
from PIL import Image
import pillow_heif<\/p>\n\n\n\n

# \u6ce8\u518c HEIC \/ HEIF \u652f\u6301<\/h6>\n\n\n\n

pillow_heif.register_heif_opener()<\/p>\n\n\n\n

#================== \u914d\u7f6e\u533a ==================<\/h6>\n\n\n\n

SCAN_ROOT = r”C:\\Users\\Downloads” # \u2190 \u6539\u6210\u4f60\u7684\u6e90\u76ee\u5f55 \/ \u516c\u5171\u76d8
OUTPUT_ROOT = r”C:\\Picture”<\/p>\n\n\n\n

#\u5206\u7ea7\u9608\u503c\uff08ArcFace \u7ecf\u9a8c\u503c\uff09<\/h6>\n\n\n\n

THRESH_SURE = 0.38 # \u51e0\u4e4e 100% \u662f\u4f60
THRESH_LIKELY = 0.33 # \u9ad8\u6982\u7387\u662f\u4f60
THRESH_REVIEW = 0.30 # \u503c\u5f97\u4eba\u5de5\u770b\u4e00\u773c<\/p>\n\n\n\n

image_ext = (
“.jpg”, “.jpeg”, “.png”, “.bmp”, “.tiff”,
“.jfif”, “.heic”, “.heif”
)<\/p>\n\n\n\n

#===========================================<\/h6>\n\n\n\n
#\u521b\u5efa\u8f93\u51fa\u76ee\u5f55<\/h6>\n\n\n\n

for sub in [“sure”, “likely”, “review”]:
os.makedirs(os.path.join(OUTPUT_ROOT, sub), exist_ok=True)<\/p>\n\n\n\n

#\u52a0\u8f7d\u672c\u4eba\u7279\u5f81<\/h6>\n\n\n\n

my_face = np.load(“my_face.npy”)<\/p>\n\n\n\n

#\u521d\u59cb\u5316 InsightFace\uff08CPU\uff09<\/h6>\n\n\n\n

app = FaceAnalysis(
name=”buffalo_l”,
providers=[“CPUExecutionProvider”]
)
app.prepare(ctx_id=-1, det_size=(640, 640))<\/p>\n\n\n\n

def cosine_similarity(a, b):
return np.dot(a, b) \/ (np.linalg.norm(a) * np.linalg.norm(b))<\/p>\n\n\n\n

def read_image_any_format(path):
“””
\u652f\u6301 JPG \/ PNG \/ HEIC \/ HEIF
\u8fd4\u56de OpenCV BGR \u56fe\u50cf
“””
try:
img = Image.open(path).convert(“RGB”)
return cv2.cvtColor(np.array(img), cv2.COLOR_RGB2BGR)
except Exception:
return None<\/p>\n\n\n\n

#================== \u626b\u63cf\u5f00\u59cb ==================<\/h6>\n\n\n\n

for root, _, files in os.walk(SCAN_ROOT):
for file in files:
if not file.lower().endswith(image_ext):
continue

img_path = os.path.join(root, file)
img = read_image_any_format(img_path)

if img is None:
continue

faces = app.get(img)
if not faces:
continue

best_score = -1.0
for face in faces:
score = cosine_similarity(face.embedding, my_face)
if score > best_score:
best_score = score

if best_score >= THRESH_SURE:
subdir = “sure”
elif best_score >= THRESH_LIKELY:
subdir = “likely”
elif best_score >= THRESH_REVIEW:
subdir = “review”
else:
continue

dst = os.path.join(
OUTPUT_ROOT,
subdir,
f”{best_score:.3f}_{file}”
)

shutil.copy2(img_path, dst)
print(f”[COPY] {best_score:.3f} -> {dst}”)<\/p>\n\n\n\n

print(“\u626b\u63cf\u5b8c\u6210\uff08\u652f\u6301 HEIC\uff0cCPU\uff09”)<\/p>\n\n\n\n

\u8fd9\u5957\u811a\u672c\u5df2\u7ecf\u53ef\u4ee5\uff1a<\/strong><\/p>\n\n\n\n

    \n
  • \u2714 \u626b JPG + iPhone HEIC \u539f\u56fe<\/strong><\/li>\n\n\n\n
  • \u2714 \u652f\u6301\u591a\u4eba\u5408\u5f71\uff08\u53ea\u8981\u6709\u4f60\u5c31\u62f7\uff09<\/li>\n\n\n\n
  • \u2714 \u4e0d\u6f0f\u6389\u4f60\uff08\u4f4e\u9608\u503c\u515c\u5e95\uff09<\/li>\n\n\n\n
  • \u2714 \u81ea\u52a8\u5206\u7ea7\uff0c\u4eba\u5de5\u6210\u672c\u6781\u4f4e<\/li>\n\n\n\n
  • \u2714 \u5b8c\u5168\u672c\u5730\u3001\u53ef\u5ba1\u8ba1\u3001\u53ef\u89e3\u91ca<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"

    Pythonpython -m venv face_scanface_scan\\Scripts\\activat […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[25],"tags":[21],"class_list":["post-521","post","type-post","status-publish","format-standard","hentry","category-25","tag-21"],"_links":{"self":[{"href":"https:\/\/seantang.cn\/index.php?rest_route=\/wp\/v2\/posts\/521","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/seantang.cn\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/seantang.cn\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/seantang.cn\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/seantang.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=521"}],"version-history":[{"count":0,"href":"https:\/\/seantang.cn\/index.php?rest_route=\/wp\/v2\/posts\/521\/revisions"}],"wp:attachment":[{"href":"https:\/\/seantang.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=521"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/seantang.cn\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=521"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/seantang.cn\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=521"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}