diff --git a/config.py b/config.py
index e77b1e4..6a66211 100644
--- a/config.py
+++ b/config.py
@@ -27,6 +27,17 @@ DEFAULT_CONFIG = {
"auto_analyze": True,
"refresh_interval": 5, # 页面刷新间隔（秒）
"display_limit": 20, # 显示最近多少条
+
+ # 检测算法开关
+ "use_haar_cascade": True, # Haar Cascade 人体检测
+ "use_mediapipe_face": True, # MediaPipe 人脸检测
+ "use_face_recognition": True, # face_recognition 人脸识别
+
+ # AI大模型分析开关
+ "use_vision_api": False, # 是否使用大模型分析（默认关闭）
+ "vision_api_trigger": "person_change", # 触发条件：person_change/motion/brightness/always
+
+ # Vision API 配置
"vision_api_url": os.environ.get("VISION_API_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1"),
"vision_api_key": os.environ.get("VISION_API_KEY", "sk-lm-fuP5tGU8:Hi7YU87jHyDP6Ay8Tl2j"),
"vision_model": os.environ.get("VISION_MODEL", "qwen-vl-plus")
diff --git a/local_analyzer.py b/local_analyzer.py
index d47e5d4..7a39ddb 100644
--- a/local_analyzer.py
+++ b/local_analyzer.py
@@ -19,6 +19,8 @@ import os
# 添加项目路径
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from config import config_mgr
+
try:
from person_manager import person_manager
HAS_PERSON_MANAGER = True
@@ -26,6 +28,12 @@ except ImportError:
HAS_PERSON_MANAGER = False
print("[LocalAnalyzer] PersonManager not available")
+try:
+ import mediapipe as mp
+ HAS_MEDIAPIPE = True
+except ImportError:
+ HAS_MEDIAPIPE = False
+
class LocalAnalyzer:
"""本地视觉分析器"""
@@ -37,7 +45,7 @@ class LocalAnalyzer:
self.prev_human_count = 0 # 记录前一帧人数
# 初始化人体检测器
- self._init_human_detector()
+ self._init_detectors()
# 阈值配置
self.config = {
@@ -53,23 +61,23 @@ class LocalAnalyzer:
self.frame_count = 0
self.motion_count = 0
self.human_count = 0
-
- def _init_human_detector(self):
- """初始化人体检测器"""
+ self.person_change_count = 0 # 人员变化次数
+
+ def _init_detectors(self):
+ """初始化检测器"""
+ # Haar Cascade 人体检测
try:
- # 使用 OpenCV 内置的 HOG 人体检测器
- self.hog = cv2.HOGDescriptor()
- self.hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
-
- # 或者使用 Haar Cascade（更快但精度稍低）
cascade_path = cv2.data.haarcascades + 'haarcascade_fullbody.xml'
if Path(cascade_path).exists():
self.human_cascade = cv2.CascadeClassifier(cascade_path)
-
- print("[LocalAnalyzer] Human detector initialized")
+ print("[LocalAnalyzer] Haar Cascade body detector initialized")
except Exception as e:
- print(f"[LocalAnalyzer] Human detector init failed: {e}")
-
+ print(f"[LocalAnalyzer] Haar Cascade init failed: {e}")
+
+ # MediaPipe 人脸检测状态（由 PersonManager 管理）
+ if HAS_PERSON_MANAGER:
+ print("[LocalAnalyzer] PersonManager available (MediaPipe face detection)")
+
def analyze(self, image_path, prev_image_path=None):
"""
分析单张图片
@@ -118,20 +126,26 @@ class LocalAnalyzer:
# 2. 人员检测与识别
person_result = {'persons': [], 'total_count': 0, 'new_count': 0, 'known_count': 0}
+ haar_result = {'count': 0, 'positions': []}
- if HAS_PERSON_MANAGER:
- print(f"[LocalAnalyzer] Using PersonManager for face detection...")
+ # 获取检测算法配置
+ use_haar = config_mgr.get('use_haar_cascade', True)
+ use_mediapipe = config_mgr.get('use_mediapipe_face', True)
+
+ # 方法1：MediaPipe 人脸检测 + 人员识别（优先）
+ if HAS_PERSON_MANAGER and use_mediapipe:
+ print(f"[LocalAnalyzer] Using MediaPipe face detection...")
person_result = person_manager.analyze_image(image_path, save_new_person=True)
metrics['person_count'] = person_result['total_count']
metrics['new_persons'] = person_result['new_count']
metrics['known_persons'] = person_result['known_count']
- # 记录人员变化
- prev_person_count = self.prev_human_count # 用之前的变量名
+ prev_person_count = self.prev_human_count
person_count_change = person_result['total_count'] - prev_person_count
metrics['person_count_change'] = person_count_change
+ # 记录人员事件
for person in person_result['persons']:
if person['is_new']:
events.append({
@@ -141,10 +155,11 @@ class LocalAnalyzer:
'source': 'local'
})
self.human_count += 1
+ self.person_change_count += 1
else:
events.append({
'event_type': '人物活动',
- 'description': f'已知人员: {person["name"]}，已访问 {person_manager.persons.get(person["person_id"], {}).get("visit_count", 1)} 次',
+ 'description': f'已知人员: {person["name"]}',
'confidence': '高',
'source': 'local'
})
@@ -157,6 +172,7 @@ class LocalAnalyzer:
'confidence': '高',
'source': 'local'
})
+ self.person_change_count += 1
elif person_count_change < 0:
events.append({
'event_type': '人员进出',
@@ -164,42 +180,44 @@ class LocalAnalyzer:
'confidence': '高',
'source': 'local'
})
+ self.person_change_count += 1
- # 更新前一帧人数
self.prev_human_count = person_result['total_count']
+
+ # 方法2：Haar Cascade 人体检测（备用或并行）
+ if use_haar and self.human_cascade is not None:
+ print(f"[LocalAnalyzer] Using Haar Cascade body detection...")
+ haar_result = self._detect_human(current_frame)
- else:
- # 使用传统人体检测（备用）
- human_result = self._detect_human(current_frame)
- metrics['human_count'] = human_result['count']
-
- human_count_change = human_result['count'] - self.prev_human_count
- metrics['human_count_change'] = human_count_change
-
- if human_count_change > 0:
- events.append({
- 'event_type': '人物活动',
- 'description': f'检测到 {human_count_change} 人进入，当前共 {human_result["count"]} 人',
- 'confidence': '高',
- 'source': 'local'
- })
- self.human_count += human_count_change
- elif human_count_change < 0:
- events.append({
- 'event_type': '人物活动',
- 'description': f'检测到 {abs(human_count_change)} 人离开，当前剩 {human_result["count"]} 人',
- 'confidence': '高',
- 'source': 'local'
- })
- elif human_result['count'] > 0:
- events.append({
- 'event_type': '人物活动',
- 'description': f'检测到 {human_result["count"]} 个人（无变化）',
- 'confidence': '低',
- 'source': 'local'
- })
-
- self.prev_human_count = human_result['count']
+ # 如果 MediaPipe 没检测到，用 Haar Cascade 结果
+ if not (HAS_PERSON_MANAGER and use_mediapipe):
+ metrics['human_count'] = haar_result['count']
+
+ human_count_change = haar_result['count'] - self.prev_human_count
+ metrics['human_count_change'] = human_count_change
+
+ if human_count_change > 0:
+ events.append({
+ 'event_type': '人员进出',
+ 'description': f'检测到 {human_count_change} 人进入（Haar）',
+ 'confidence': '中',
+ 'source': 'local'
+ })
+ self.human_count += human_count_change
+ self.person_change_count += 1
+ elif human_count_change < 0:
+ events.append({
+ 'event_type': '人员进出',
+ 'description': f'检测到 {abs(human_count_change)} 人离开（Haar）',
+ 'confidence': '中',
+ 'source': 'local'
+ })
+ self.person_change_count += 1
+
+ self.prev_human_count = haar_result['count']
+ else:
+ # 并行运行时，记录 Haar 结果但不作为主要判断
+ metrics['haar_count'] = haar_result['count']
# 3. 亮度检测
brightness_result = self._detect_brightness_change(current_gray, prev_image_path)
@@ -367,28 +385,44 @@ class LocalAnalyzer:
def _should_call_model(self, metrics, events):
"""判断是否需要调用大模型"""
- # 条件1：人数变化（最重要）
- current_person_count = metrics.get('person_count', metrics.get('human_count', 0))
- person_count_change = metrics.get('person_count_change', metrics.get('human_count_change', 0))
+ # 检查大模型是否启用
+ use_vision_api = config_mgr.get('use_vision_api', False)
+ if not use_vision_api:
+ print("[LocalAnalyzer] Vision API disabled, skipping model call")
+ return False
- # 更新前一帧人数（如果还没更新）
- if abs(person_count_change) >= self.config['human_count_change_threshold']:
- print(f"[LocalAnalyzer] Person count changed: {current_person_count - person_count_change} -> {current_person_count}, triggering model")
- return True
+ # 获取触发条件配置
+ trigger_condition = config_mgr.get('vision_api_trigger', 'person_change')
- # 条件2：检测到新人
- if metrics.get('new_persons', 0) > 0:
- print(f"[LocalAnalyzer] New person detected: {metrics.get('new_persons', 0)}, triggering model")
- return True
+ # 条件1：人员变化（person_change 模式）
+ if trigger_condition in ['person_change', 'always']:
+ current_person_count = metrics.get('person_count', metrics.get('human_count', 0))
+ person_count_change = metrics.get('person_count_change', metrics.get('human_count_change', 0))
+
+ if abs(person_count_change) >= self.config['human_count_change_threshold']:
+ print(f"[LocalAnalyzer] Person change detected: {person_count_change}, triggering model")
+ return True
+
+ # 检测到新人
+ if metrics.get('new_persons', 0) > 0:
+ print(f"[LocalAnalyzer] New person detected: {metrics.get('new_persons', 0)}, triggering model")
+ return True
- # 条件3：运动面积超过阈值（排除有人但不动的情况）
- if metrics.get('motion_ratio', 0) > self.config['trigger_model_threshold'] * 2:
- print(f"[LocalAnalyzer] Large motion detected: {metrics.get('motion_ratio', 0):.2%}")
- return True
+ # 条件2：运动检测（motion 模式）
+ if trigger_condition in ['motion', 'always']:
+ if metrics.get('motion_ratio', 0) > self.config['trigger_model_threshold'] * 2:
+ print(f"[LocalAnalyzer] Large motion detected: {metrics.get('motion_ratio', 0):.2%}")
+ return True
- # 条件4：亮度大幅变化（灯开关等）
- if abs(metrics.get('brightness_change', 0)) > self.config['brightness_change_threshold'] * 2:
- print(f"[LocalAnalyzer] Brightness changed: {metrics.get('brightness_change', 0)}")
+ # 条件3：亮度变化（brightness 模式）
+ if trigger_condition in ['brightness', 'always']:
+ if abs(metrics.get('brightness_change', 0)) > self.config['brightness_change_threshold'] * 2:
+ print(f"[LocalAnalyzer] Brightness changed: {metrics.get('brightness_change', 0)}")
+ return True
+
+ # always 模式：总是调用
+ if trigger_condition == 'always':
+ print("[LocalAnalyzer] Always trigger mode enabled")
return True
return False
diff --git a/web/static/app.js b/web/static/app.js
index 455d08b..20050f1 100644
--- a/web/static/app.js
+++ b/web/static/app.js
@@ -505,6 +505,17 @@ function loadSettingsForm() {
document.getElementById('setting-auto-analyze').checked = config.auto_analyze !== false;
document.getElementById('setting-display-limit').value = config.display_limit || 20;
document.getElementById('setting-refresh-interval').value = config.refresh_interval || 5;
+
+ // Detection algorithm settings
+ document.getElementById('setting-use-haar').checked = config.use_haar_cascade !== false;
+ document.getElementById('setting-use-mediapipe').checked = config.use_mediapipe_face !== false;
+ document.getElementById('setting-use-face-rec').checked = config.use_face_recognition !== false;
+
+ // Vision API settings
+ document.getElementById('setting-use-vision-api').checked = config.use_vision_api === true;
+ document.getElementById('setting-vision-trigger').value = config.vision_api_trigger || 'person_change';
+
+ // API config
document.getElementById('setting-api-url').value = config.vision_api_url || '';
document.getElementById('setting-api-key').value = config.vision_api_key || '';
document.getElementById('setting-model').value = config.vision_model || '';
@@ -520,6 +531,17 @@ function saveSettings() {
auto_analyze: document.getElementById('setting-auto-analyze').checked,
display_limit: parseInt(document.getElementById('setting-display-limit').value),
refresh_interval: parseInt(document.getElementById('setting-refresh-interval').value),
+
+ // Detection algorithms
+ use_haar_cascade: document.getElementById('setting-use-haar').checked,
+ use_mediapipe_face: document.getElementById('setting-use-mediapipe').checked,
+ use_face_recognition: document.getElementById('setting-use-face-rec').checked,
+
+ // Vision API
+ use_vision_api: document.getElementById('setting-use-vision-api').checked,
+ vision_api_trigger: document.getElementById('setting-vision-trigger').value,
+
+ // API config
vision_api_url: document.getElementById('setting-api-url').value,
vision_api_key: document.getElementById('setting-api-key').value,
vision_model: document.getElementById('setting-model').value
@@ -533,14 +555,13 @@ function saveSettings() {
.then(function(res) { return res.json(); })
.then(function(data) {
if (data.success) {
- alert('Settings saved!');
+ showToast('Settings saved!', 1500);
closeSettingsModal();
- // Reload config to apply new refresh interval
loadConfig();
refreshAll();
}
})
- .catch(function(e) { alert('Error: ' + e.message); });
+ .catch(function(e) { showToast('Error: ' + e.message, 3000); });
}
function browseImagesDir() {
diff --git a/web/static/index.html b/web/static/index.html
index 1b21255..7444501 100644
--- a/web/static/index.html
+++ b/web/static/index.html
@@ -137,6 +137,43 @@
+
+
+
+
AI大模型分析
+
+
+
+ 调用 Vision API 详细分析
+
+
+
+
+
+
API 设置
diff --git a/web/static/style.css b/web/static/style.css
index 6830864..e1a0b7f 100644
--- a/web/static/style.css
+++ b/web/static/style.css
@@ -649,6 +649,16 @@ button {
gap: 10px;
}
+.person-actions {
+ display: flex;
+ gap: 10px;
+}
+
+.setting-desc {
+ color: #888;
+ font-size: 12px;
+}
+
@media (max-width: 768px) {
.control-panel {
flex-direction: column;