From a68247f748ea097fd480cea7fe81025299477714 Mon Sep 17 00:00:00 2001 From: liuwei Date: Mon, 14 Apr 2025 12:02:28 +0800 Subject: [PATCH] =?UTF-8?q?feature=EF=BC=9A=E5=8A=A0=E5=85=A5=E5=8A=9F?= =?UTF-8?q?=E8=83=BD=EF=BC=8C=E5=B0=8F=E6=9C=8B=E5=8F=8B=E4=BA=BA=E8=84=B8?= =?UTF-8?q?=E8=AF=86=E5=88=AB=E4=B8=8E=E5=88=86=E7=B1=BB=E3=80=82?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- plugins/kid_photo_extractor/main.py | 140 +++++++++++++++------------- 1 file changed, 76 insertions(+), 64 deletions(-) diff --git a/plugins/kid_photo_extractor/main.py b/plugins/kid_photo_extractor/main.py index a1619ce..bbfc1e0 100644 --- a/plugins/kid_photo_extractor/main.py +++ b/plugins/kid_photo_extractor/main.py @@ -30,6 +30,7 @@ class FaceAnalyzer: """人脸分析器，负责检测和分析人脸""" def __init__(self, kid_age_threshold=14): + # 保留参数但不再使用 self.kid_age_threshold = kid_age_threshold self.logger = logging.getLogger("Plugin.KidPhotoExtractor.FaceAnalyzer") @@ -47,18 +48,32 @@ class FaceAnalyzer: if img is None: self.logger.error(f"无法读取图片: {image_path}") return [] + + # 打印图片信息以便调试 + self.logger.info(f"图片尺寸: {img.shape}, 类型: {img.dtype}") except Exception as e: self.logger.error(f"读取图片失败: {image_path}, 错误: {e}") return [] - faces = DeepFace.extract_faces(img_path=image_path, enforce_detection=False) + # 使用更宽松的人脸检测参数 + faces = DeepFace.extract_faces( + img_path=image_path, + enforce_detection=False, + detector_backend='opencv', # 使用更快的opencv检测器 + align=True + ) + + # 记录检测到的人脸数量 + self.logger.info(f"在图片 {image_path} 中检测到 {len(faces)} 个人脸") + return faces except Exception as e: self.logger.error(f"人脸检测失败: {image_path}, 错误: {e}") + self.logger.error(traceback.format_exc()) # 打印完整的错误堆栈 return [] def analyze_face(self, image_path, face_area=None): - """分析人脸，获取年龄和特征向量""" + """分析人脸，获取特征向量""" try: # 检查文件是否存在 if not os.path.exists(image_path): @@ -85,15 +100,15 @@ class FaceAnalyzer: self.logger.error(f"读取图片失败: {image_path}, 错误: {e}") return None - # 分析人脸属性 - analysis = DeepFace.analyze(img_path=image_path, - actions=['age', 'gender'], - enforce_detection=False) - # 提取人脸特征向量用于后续比对 - embedding = DeepFace.represent(img_path=image_path, - model_name='Facenet', - enforce_detection=False) + embedding = DeepFace.represent( + img_path=image_path, + model_name='Facenet', + enforce_detection=False, + detector_backend='opencv' # 使用更快的opencv检测器 + ) + + self.logger.info(f"成功提取人脸特征向量: {image_path}") # 如果使用了临时文件，删除它 if face_area and os.path.exists(f"{image_path}.temp.jpg"): @@ -102,24 +117,21 @@ class FaceAnalyzer: except Exception as e: self.logger.warning(f"删除临时文件失败: {e}") + # 不再进行年龄判断，直接返回特征向量 return { - 'age': analysis[0]['age'], - 'gender': analysis[0]['gender'], - 'is_kid': analysis[0]['age'] < self.kid_age_threshold, - 'embedding': embedding + 'embedding': embedding, + 'is_kid': True # 默认所有人脸都处理 } - except IndexError as e: - self.logger.error(f"人脸分析结果索引错误: {image_path}, 错误: {e}") - return None except Exception as e: self.logger.error(f"人脸分析失败: {image_path}, 错误: {e}") + self.logger.error(traceback.format_exc()) # 打印完整的错误堆栈 return None def is_kid(self, face_info): - """判断是否为小朋友""" + """判断是否为小朋友 - 现在总是返回True""" if not face_info: return False - return face_info.get('is_kid', False) + return True # 所有人脸都视为需要处理 class FaceGrouper: @@ -486,9 +498,9 @@ class KidPhotoExtractorPlugin(MessagePluginInterface): "total_images": 0, "processed_images": 0, "total_faces": 0, - "kid_faces": 0, - "kid_groups": 0, - "kids": {}, + "face_groups": 0, # 改名，不再是kid_faces + "groups": 0, # 改名，不再是kid_groups + "persons": {}, # 改名，不再是kids "is_full": is_full } @@ -544,9 +556,9 @@ class KidPhotoExtractorPlugin(MessagePluginInterface): progress_interval = 5 # 每5秒更新一次进度 # 处理每张图片 - kid_faces = [] # 存储所有小朋友的人脸特征 - kid_face_images = [] # 存储对应的图片路径 - kid_face_regions = [] # 存储人脸区域 + all_faces = [] # 存储所有的人脸特征，不再区分小朋友 + face_images = [] # 存储对应的图片路径 + face_regions = [] # 存储人脸区域 # 记录本次处理的照片 newly_processed_photos = [] @@ -571,12 +583,12 @@ class KidPhotoExtractorPlugin(MessagePluginInterface): face_region = face.get('facial_area', None) face_info = self.face_analyzer.analyze_face(image_path, face_region) - if face_info and self.face_analyzer.is_kid(face_info): - # 是小朋友的人脸 - kid_faces.append(face_info['embedding']) - kid_face_images.append(image_path) - kid_face_regions.append(face_region) - result["kid_faces"] += 1 + if face_info: # 不再判断是否为小朋友 + # 保存人脸特征 + all_faces.append(face_info['embedding']) + face_images.append(image_path) + face_regions.append(face_region) + result["face_groups"] += 1 # 更新计数器名称 result["total_faces"] += 1 @@ -609,49 +621,50 @@ class KidPhotoExtractorPlugin(MessagePluginInterface): # 更新最后处理时间 self.kid_photo_db.save_last_process_time(group_key) - # 如果没有找到小朋友人脸 - if not kid_faces: - wcf.send_text("⚠️未检测到任何小朋友的人脸", target, sender) + # 如果没有找到人脸 + if not all_faces: + wcf.send_text("⚠️未检测到任何人脸", target, sender) self.analysis_tasks[group_key]["running"] = False - + # 保存分析结果 result["end_time"] = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S") result["duration"] = time.time() - start_time self._save_analysis_result(group_key, result) - + return - - # 对小朋友人脸进行聚类分组 - wcf.send_text("🧩正在对小朋友人脸进行分组...", target, sender) - cluster_labels = self.face_grouper.cluster_faces(kid_faces) - + + # 对人脸进行聚类分组 + wcf.send_text("🧩正在对人脸进行分组...", target, sender) + cluster_labels = self.face_grouper.cluster_faces(all_faces) + # 统计每个分组的人脸数量 - kid_groups = {} + face_groups = {} for i, label in enumerate(cluster_labels): - if label not in kid_groups: - kid_groups[label] = [] - kid_groups[label].append((kid_face_images[i], kid_face_regions[i])) + if label not in face_groups: + face_groups[label] = [] + face_groups[label].append((face_images[i], face_regions[i])) + + result["groups"] = len(face_groups) - result["kid_groups"] = len(kid_groups) + # 为每个人创建文件夹并复制照片 + wcf.send_text(f"📁正在创建分类文件夹，共有{len(face_groups)}个人...", target, sender) - # 为每个小朋友创建文件夹并复制照片 - wcf.send_text(f"📁正在创建分类文件夹，共有{len(kid_groups)}个小朋友...", target, sender) - - for kid_id, faces in kid_groups.items(): - # 创建小朋友文件夹 - kid_folder = self.photo_classifier.create_kid_folder(output_dir, kid_id) + for person_id, faces in face_groups.items(): + # 创建人物文件夹 + person_folder = os.path.join(output_dir, f"person_{person_id}") + os.makedirs(person_folder, exist_ok=True) # 复制照片 copied_photos = [] for image_path, _ in faces: - if self.photo_classifier.copy_photo(image_path, kid_folder): + if self.photo_classifier.copy_photo(image_path, person_folder): copied_photos.append(os.path.basename(image_path)) # 保存照片映射关系 if self.kid_photo_db: - self.kid_photo_db.save_photo_mapping(group_key, f"kid_{kid_id}", image_path) + self.kid_photo_db.save_photo_mapping(group_key, f"person_{person_id}", image_path) # 记录结果 - result["kids"][f"kid_{kid_id}"] = { + result["persons"][f"person_{person_id}"] = { "photo_count": len(copied_photos), "photos": copied_photos } @@ -794,21 +807,20 @@ class KidPhotoExtractorPlugin(MessagePluginInterface): def _generate_analysis_summary(self, result, output_dir): """生成分析结果摘要""" - summary = "📊小朋友照片分析结果：\n\n" + summary = "📊人脸照片分析结果：\n\n" # 更改标题 # 基本信息 summary += f"📷 总照片数: {result.get('total_images', 0)}\n" summary += f"👤 处理照片数: {result.get('processed_images', 0)}\n" summary += f"😊 检测到的人脸: {result.get('total_faces', 0)}\n" - summary += f"👶 小朋友人脸: {result.get('kid_faces', 0)}\n" - summary += f"👪 小朋友分组: {result.get('kid_groups', 0)}\n\n" + summary += f"👪 人脸分组: {result.get('groups', 0)}\n\n" # 更新字段名 - # 小朋友分组信息 - kids = result.get('kids', {}) - if kids: - summary += "🧒 小朋友照片统计：\n" - for kid_id, kid_info in kids.items(): - summary += f" - {kid_id}: {kid_info.get('photo_count', 0)}张照片\n" + # 人物分组信息 + persons = result.get('persons', {}) # 更新字段名 + if persons: + summary += "🧒 人物照片统计：\n" # 更新描述 + for person_id, person_info in persons.items(): # 更新变量名 + summary += f" - {person_id}: {person_info.get('photo_count', 0)}张照片\n" # 分析时间 start_time = result.get('start_time', '')