华荣三照明、合信、荣欣八组合馈电

QT5_Project/Shared_CODE/CameraThread.py

@@ -0,0 +1,443 @@
+# import sys
+# import cv2
+# import os
+# import time
+# from PyQt5.QtCore import QThread, pyqtSignal, QObject
+# import face_recognition
+
+# current_dir = os.path.dirname(__file__)
+# share_code_dir = os.path.abspath(os.path.join(current_dir, '..', '..'))
+# sys.path.append(share_code_dir)
+
+# from print_color import *
+
+# DEFAULT_VIDEO_SLEEP_MS = 20
+
+# # 图像处理线程
+# class ImageProcessingThread(QThread):
+#     processed_image_signal = pyqtSignal(object)
+
+#     def __init__(self):
+#         super().__init__()
+
+#     def run(self):
+#         while True:
+#             # 在这里添加图像处理代码
+#             # 这里暂时只是将图像传递给下一个线程
+#             time.sleep(0.01)
+#             self.processed_image_signal.emit(None)
+
+# # 摄像头采集线程
+# class CameraThread(QThread):
+#     image_signal = pyqtSignal(object)
+
+#     def __init__(self, camera_url, circuit_id: int = 0):
+#         super().__init__()
+
+#         self.camera_url = camera_url  # 摄像头url地址, 整数 或者 字符串
+#         self.face_detection: bool = False
+
+#         if isinstance(camera_url, int):
+#             self.camera_url_str = str(camera_url)
+#         else:
+#             self.camera_url_str = camera_url
+
+#         self.cap: cv2.VideoCapture = None
+#         self.running: bool = True
+
+#         self.fps = 0
+
+#         self.cycle_limit = DEFAULT_VIDEO_SLEEP_MS
+#         self.cycle_ms = 0
+#         self.circuit_id = circuit_id  # 摄像头对应的回路, 组合开关每一个回路都有对应的摄像头
+#         self.is_signal_connect = False
+#         self.is_emit = False
+
+#         self.set_video_cycle_ms(2000)
+
+#     def signal_connect(self, slot_func):
+#         self.image_signal.connect(slot_func)
+#         self.is_signal_connect = True
+
+#     def signal_disconnect(self):
+#         # 判断信号是否已连接
+#         if self.is_signal_connect:
+#             self.image_signal.disconnect()
+#             self.is_signal_connect = False
+
+#     def set_video_cycle_ms(self, cycle_ms: int = 10):
+#         if self.cycle_limit != cycle_ms:
+#             if cycle_ms <= DEFAULT_VIDEO_SLEEP_MS:
+#                 self.cycle_limit = DEFAULT_VIDEO_SLEEP_MS
+#             else:
+#                 self.cycle_limit = cycle_ms
+
+#     # 新建函数，改变函数延时方法
+#     def change_camera_url(self, camera_url: str):
+#         if self.circuit_id == camera_url:
+#             self.set_video_cycle_ms(DEFAULT_VIDEO_SLEEP_MS)
+#         else:
+#             self.set_video_cycle_ms(1000)
+
+#     def close(self):
+#         if self.cap == None:  # 初始化一直未完成
+#             self.terminate()
+#         self.running = False
+
+#     def run(self):
+#         process_count = 0
+#         fps_time = 0
+
+#         while self.running == True:
+#             inform_msg = "cameral init start, url = " + self.camera_url_str
+#             print_inform_msg(inform_msg)
+
+#             try:
+#                 if isinstance(self.camera_url, int):
+#                     # 在 Windows 平台下，使用默认的 cv2.VideoCapture 接口
+#                     self.cap = cv2.VideoCapture(self.camera_url, cv2.CAP_DSHOW)
+#                 else:
+#                     # 在 Linux 平台下，使用默认的 cv2.VideoCapture 接口
+#                     self.cap = cv2.VideoCapture(self.camera_url)
+
+#                 if self.cap != None:
+#                     inform_msg = "cameral Init Success, url = " + self.camera_url_str
+#                     self.is_emit = True
+#                     print_inform_msg(inform_msg)
+#                 else:
+#                     inform_msg = "cameral connection timeout, url = " + self.camera_url_str
+#                     print_inform_msg(inform_msg)
+
+#             except Exception as e:
+#                 self.cap = None
+#                 inform_msg = "cameral camera Init Fail, url = " + self.camera_url_str
+#                 print_error_msg(inform_msg)
+
+#             base_time = time.time()
+
+#             while self.running and self.cap != None:
+#                 # 延时20ms
+#                 time.sleep(DEFAULT_VIDEO_SLEEP_MS / 1000)
+#                 if self.cycle_ms + DEFAULT_VIDEO_SLEEP_MS < self.cycle_limit:
+#                     self.cycle_ms += DEFAULT_VIDEO_SLEEP_MS
+#                     self.cap.grab()  # 抛弃多余的帧，保持最新帧
+#                     continue
+#                 else:
+#                     self.cycle_ms = 0
+
+#                 try:
+#                     ret, frame = self.cap.read()
+#                     cur_time = time.time()
+
+#                     execution_time = cur_time - base_time
+#                     base_time = cur_time
+#                     process_count += 1
+
+#                     fps_time += execution_time
+
+#                     if fps_time >= 1:
+#                         self.fps = process_count
+#                         process_count = 0
+#                         fps_time = 0
+
+#                     if execution_time < 5:
+#                         image_object: QObject = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+#                         self.image_signal.emit(image_object)
+#                     else:  # 时间差大于5秒, 表示网络可能中断过, 退出并重新连接
+#                         err_message = "cameral read timeout, url = " + self.camera_url_str
+#                         print_error_msg(err_message)
+#                         break
+#                 except Exception as e:
+#                     err_message = "cameral read timeout, url = " + self.camera_url_str
+#                     self.is_emit = False
+#                     print_error_msg(err_message)
+#                     if self.running == True:
+#                         time.sleep(2)
+#                     break
+
+#             print_inform_msg("cameral connection End")
+#             time.sleep(0.01)
+
+#             if self.cap != None:
+#                 self.cap.release()
+#                 self.cap = None
+# - * - coding:utf - 8 - * -
+import sys
+import cv2
+import os
+import time
+import subprocess
+import face_recognition
+import numpy as np
+from PIL import Image, ImageDraw, ImageFont
+from PyQt5.QtCore import QThread, pyqtSignal, QObject
+from print_color import * 
+current_dir = os.path.dirname(__file__)
+share_code_dir = os.path.abspath(os.path.join(current_dir, '..', '..'))
+sys.path.append(share_code_dir)
+
+DEFAULT_VIDEO_SLEEP_MS = 20
+
+# 定义路径常量
+npy_file_path = os.path.abspath(os.path.join(os.path.dirname(__file__), 'face_data/face_data.npy'))
+image_folder_path = os.path.abspath(os.path.join(os.path.dirname(__file__), 'face_data'))
+font_path = os.path.abspath(os.path.join(os.path.dirname(__file__), 'font/hanzi.ttc'))
+def load_face_data():
+    face_data = {}
+    try:
+        face_data = np.load(npy_file_path, allow_pickle=True).item()
+        print_debug_msg(f"Loaded {len(face_data)} face encodings from {npy_file_path}.")
+    except Exception as e:
+        print_error_msg(f"Error loading face encodings: {e}")
+
+    current_images = [f for f in os.listdir(image_folder_path) if f.endswith('.jpg')]
+    current_image_set = set(os.path.splitext(f)[0] for f in current_images)
+    known_image_set = set(face_data.keys())
+
+    added_images = current_image_set - known_image_set
+    removed_images = known_image_set - current_image_set
+
+    for image_name in added_images:
+        image_path = os.path.join(image_folder_path, f"{image_name}.jpg")
+        try:
+            image = face_recognition.load_image_file(image_path)
+            face_encodings = face_recognition.face_encodings(image)
+            if face_encodings:
+                face_data[image_name] = face_encodings[0].tolist()
+                print_debug_msg(f"Added encoding for {image_name}.")
+            else:
+                print_warning_msg(f"[WARNING] No face detected in {image_name}.jpg.")
+        except Exception as e:
+            print_error_msg(f"[ERROR] Error processing {image_name}.jpg: {e}")
+
+    for removed_image in removed_images:
+        del face_data[removed_image]
+        print_debug_msg(f"Removed encoding for {removed_image}.")
+
+    np.save(npy_file_path, face_data)
+    print_debug_msg(f"Updated face data saved with {len(face_data)} entries.")
+    return face_data
+
+class ImageProcessingThread(QThread):
+    processed_image_signal = pyqtSignal(object)
+
+    def __init__(self, frame=None):
+        super().__init__()
+        self.frame = frame  # 添加 frame 参数
+        self.face_encodings = []
+        self.face_names = []
+        self.face_locations = []
+        self.face_data = load_face_data()
+        self.total_image_name = list(self.face_data.keys())
+        self.total_face_encoding = [np.array(self.face_data[name]) for name in self.total_image_name]
+
+    def process_frame(self, frame):
+        """实时处理帧，匹配已知人脸"""
+        self.face_locations = face_recognition.face_locations(frame)
+        face_encodings = face_recognition.face_encodings(frame, self.face_locations)
+        names = []
+        for face_encoding in face_encodings:
+            name = "Unknown"
+            face_distances = face_recognition.face_distance(self.total_face_encoding, face_encoding)
+
+            if face_distances.size > 0:
+                min_distance = np.min(face_distances)
+                best_match_index = np.argmin(face_distances)
+
+                if min_distance < self.dynamic_tolerance():  # 使用动态容忍度
+                    name = self.total_image_name[best_match_index]
+
+            names.append(name)
+
+        self.face_names = names
+        return frame
+
+    def dynamic_tolerance(self):
+        # 动态调整容忍度，可以基于一些规则来调整，如帧内错误率、识别准确率等
+        error_rate = self.calculate_error_rate()
+        if error_rate > 0.1:
+            return 0.5  # 高容忍度以减少错误
+        else:
+            return 0.4  # 适中容忍度
+
+    def calculate_error_rate(self):
+        # 计算识别错误率，作为动态调整容忍度的依据
+        total_faces = len(self.total_face_encoding)
+        unmatched_faces = sum(1 for name in self.face_names if name == "Unknown")
+        return unmatched_faces / total_faces if total_faces > 0 else 0
+
+    def set_frame(self, frame):
+        self.frame = frame
+
+    def run(self):
+        while True:
+            if self.frame is not None:
+                self.process_frame(self.frame)
+                self.processed_image_signal.emit(self.frame)
+            time.sleep(0.01)  # 控制帧率
+
+
+# 摄像头采集线程
+class CameraThread(QThread):
+    image_signal = pyqtSignal(object)
+
+    def __init__(self, camera_url, circuit_id: int = 0):
+        super().__init__()
+        self.camera_url = camera_url
+        self.face_detection: bool = True
+
+        if isinstance(camera_url, int):
+            self.camera_url_str = str(camera_url)
+        else:
+            self.camera_url_str = camera_url
+
+        self.cap: cv2.VideoCapture = None
+        self.running: bool = True
+
+        self.fps = 0
+        self.frame_count = 0
+        self.fps_time = 0
+
+        self.cycle_limit = DEFAULT_VIDEO_SLEEP_MS
+        self.cycle_ms = 0
+        self.circuit_id = circuit_id
+        self.is_signal_connect = False
+        self.is_emit = False
+
+        self.set_video_cycle_ms(2000)
+
+    def signal_connect(self, slot_func):
+        self.image_signal.connect(slot_func)
+        self.is_signal_connect = True
+
+    def signal_disconnect(self):
+        if self.is_signal_connect:
+            self.image_signal.disconnect()
+            self.is_signal_connect = False
+
+    def set_video_cycle_ms(self, cycle_ms: int = 10):
+        if self.cycle_limit != cycle_ms:
+            if cycle_ms <= DEFAULT_VIDEO_SLEEP_MS:
+                self.cycle_limit = DEFAULT_VIDEO_SLEEP_MS
+            else:
+                self.cycle_limit = cycle_ms
+
+    def change_camera_url(self, camera_url: str):
+        if self.circuit_id == camera_url:
+            self.set_video_cycle_ms(DEFAULT_VIDEO_SLEEP_MS)
+        else:
+            self.set_video_cycle_ms(1000)
+
+    def close(self):
+        if self.cap is None:
+            self.terminate()
+        self.running = False
+
+    def run(self):
+        process_count = 0
+        fps_time = 0
+        face_thread = ImageProcessingThread()
+        face_thread.start()
+
+        self.match_count = 0  # 初始化匹配帧数计数器
+
+        while self.running:
+            inform_msg = "Camera init start, URL = " + self.camera_url_str
+            print_inform_msg(inform_msg)
+
+            try:
+                self.cap = cv2.VideoCapture(self.camera_url)  # 强制使用 BGR 格式
+                if self.cap.isOpened():
+                    inform_msg = "Camera Init Success, URL = " + self.camera_url_str
+                    self.is_emit = True
+                    print_inform_msg(inform_msg)
+                else:
+                    inform_msg = "Camera connection timeout, URL = " + self.camera_url_str
+                    print_error_msg(inform_msg)
+
+            except Exception as e:
+                self.cap = None
+                inform_msg = "Camera Init Fail, URL = " + self.camera_url_str
+                print_error_msg(inform_msg)
+
+            base_time = time.time()
+
+            while self.running and self.cap:
+                time.sleep(DEFAULT_VIDEO_SLEEP_MS / 1000)
+
+                if self.cycle_ms + DEFAULT_VIDEO_SLEEP_MS < self.cycle_limit:
+                    self.cycle_ms += DEFAULT_VIDEO_SLEEP_MS
+                    self.cap.grab()
+                    continue
+                else:
+                    self.cycle_ms = 0
+
+                try:
+                    ret, frame = self.cap.read()
+                    if not ret:
+                        break
+
+                    face_thread.set_frame(frame)
+
+                    cur_time = time.time()
+                    execution_time = cur_time - base_time
+                    base_time = cur_time
+                    process_count += 1
+
+                    fps_time += execution_time
+                    if fps_time >= 1:  # 每隔1秒重新计算 FPS
+                        self.fps = process_count
+                        process_count = 0
+                        fps_time = 0
+
+                    if execution_time < 5:
+                        frame: QObject = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+                        for (top, right, bottom, left), name in zip(face_thread.face_locations, face_thread.face_names):
+                            if name != "Unknown":  # 只绘制已匹配的结果
+                                self.match_count += 1  # 计数成功匹配的帧
+                                # cv2.rectangle(frame, (left, top), (right, bottom), (0, 255, 0), 2)
+                                # cv2.putText(frame, name, (left + 6, bottom - 6), cv2.FONT_HERSHEY_DUPLEX, 1.0, (255, 255, 255), 1)
+
+                                # 将OpenCV图像转换为PIL图像格式（注意要转换色彩空间，OpenCV是BGR，PIL是RGB）
+                                pil_image = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
+                                draw = ImageDraw.Draw(pil_image)
+                                # 这里选择合适的中文字体文件路径，比如系统自带的宋体（不同系统路径可能有差异），并设置字体大小
+                                font = ImageFont.truetype(font_path, 15)
+                                # 在指定位置绘制中文
+                                draw.text((left + 12, bottom + 12), name, font=font, fill=(255, 255, 255))
+                                # 再将PIL图像转换回OpenCV图像格式
+                                frame = cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
+                                cv2.rectangle(frame, (left, top), (right, bottom), (0, 255, 0), 2)
+                            else:
+                                name = "未在人脸库中，无操作权限" 
+                                pil_image = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
+                                draw = ImageDraw.Draw(pil_image)
+                                #设置字体大小
+                                font = ImageFont.truetype(font_path, 15)
+                                # 在指定位置绘制中文
+                                draw.text((left + 12, bottom + 12), name, font=font, fill=(255, 255, 255))
+                                # 再将PIL图像转换回OpenCV图像格式
+                                frame = cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
+                                cv2.rectangle(frame, (left, top), (right, bottom), (255, 0, 0), 2)
+                        self.image_signal.emit(frame)
+                    else:
+                        err_message = "Camera read timeout, URL = " + self.camera_url_str
+                        print_error_msg(err_message)
+                        break
+
+                except Exception as e:
+                    err_message = "Camera read exception, URL = " + self.camera_url_str
+                    print_error_msg(err_message)
+                    if self.running:
+                        time.sleep(2)
+                    break
+
+            if self.cap:
+                self.cap.release()
+                self.cap = None
+
+            print_inform_msg("Camera connection ended")
+            time.sleep(0.01)
+
+
+