274 lines
9.8 KiB
Python
274 lines
9.8 KiB
Python
import os
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import cv2
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import torch
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import numpy as np
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from redis import Redis
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from ultralytics import YOLO
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import json
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from kafka import KafkaConsumer
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import threading
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import redis
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from config import *
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# 配置
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MODEL_PATH = FALL_MODEL_PATH
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KAFKA_BROKER = KAFKA_BROKER
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KAFKA_TOPIC = WORKER_CONFIGS["fall"]["kafka_topic"]
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KAFKA_GROUP_ID = f"fall_{KAFKA_GROUP_ID_PREFIX}"
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REDIS_HOST = REDIS_HOST
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REDIS_PORT = REDIS_PORT
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REDIS_PASSWORD = REDIS_PASSWORD
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REDIS_DB = WORKER_CONFIGS["fall"]["redis_db"] # Worker使用的Redis DB
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MAIN_REDIS_DB = MAIN_REDIS_DB # 主Redis DB
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UPLOAD_DIR = UPLOAD_DIR
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RESULT_DIR = RESULT_DIR
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# 确保目录存在
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os.makedirs(UPLOAD_DIR, exist_ok=True)
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os.makedirs(RESULT_DIR, exist_ok=True)
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# 初始化 Kafka
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consumer = KafkaConsumer(
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KAFKA_TOPIC,
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bootstrap_servers=[KAFKA_BROKER],
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group_id=KAFKA_GROUP_ID,
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auto_offset_reset='latest',
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enable_auto_commit=True,
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value_deserializer=lambda x: json.loads(x.decode('utf-8'))
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)
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# 初始化 Redis
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redis_client = Redis(
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host=REDIS_HOST,
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port=REDIS_PORT,
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password=REDIS_PASSWORD,
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db=REDIS_DB
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)
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main_redis_client = Redis(
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host=REDIS_HOST,
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port=REDIS_PORT,
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password=REDIS_PASSWORD,
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db=MAIN_REDIS_DB
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)
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class fallDetector:
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def __init__(self, model_path):
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self.model = YOLO(model_path)
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def detect(self, frame):
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results = self.model(frame)
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return results
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def format_results(self, results):
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formatted_results = []
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for r in results:
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if not hasattr(r, 'boxes') or len(r.boxes) == 0:
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print("没有检测到任何对象")
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return [{"message": "No objects detected"}]
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boxes = r.boxes
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names = getattr(r, 'names', {})
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for i in range(len(boxes)):
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box = boxes[i]
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if not hasattr(box, 'cls') or not hasattr(box, 'conf') or not hasattr(box, 'xyxy'):
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print(f"警告: 第 {i} 个框缺少必要的属性")
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continue
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try:
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class_id = int(box.cls.item())
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formatted_result = {
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"bbox": box.xyxy.tolist()[0],
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"confidence": box.conf.item(),
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"class_id": class_id,
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"class": names.get(class_id, f"Unknown-{class_id}")
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}
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formatted_results.append(formatted_result)
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except Exception as e:
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print(f"处理第 {i} 个框时出错: {str(e)}")
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# print("格式化后的结果:", formatted_results)
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return formatted_results
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def draw_results(self, frame, results):
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for r in results:
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annotated_frame = r.plot()
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return annotated_frame
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detector = fallDetector(MODEL_PATH)
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def process_image(image_data, filename):
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try:
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img = cv2.imdecode(np.frombuffer(image_data, np.uint8), cv2.IMREAD_COLOR)
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results = detector.detect(img)
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# Format results for JSON
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json_results = detector.format_results(results)
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# Draw results on image
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annotated_img = detector.draw_results(img, results)
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# Save annotated image
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annotated_filename = f"fall_{filename}"
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annotated_path = os.path.join(RESULT_DIR, annotated_filename)
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cv2.imwrite(annotated_path, annotated_img)
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return json_results, annotated_filename
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except Exception as e:
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print(f"Error processing image: {str(e)}")
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return None, None
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def process_video(video_data, filename):
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try:
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temp_video_path = os.path.join(UPLOAD_DIR, f"fall_{filename}")
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with open(temp_video_path, 'wb') as temp_video:
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temp_video.write(video_data)
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cap = cv2.VideoCapture(temp_video_path)
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frame_count = 0
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json_results = []
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# Get video properties
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fps = int(cap.get(cv2.CAP_PROP_FPS))
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width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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# Create output video file
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annotated_filename = f"fall_{filename}"
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output_path = os.path.join(RESULT_DIR, annotated_filename)
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out = cv2.VideoWriter(output_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (width, height))
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while cap.isOpened():
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ret, frame = cap.read()
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if not ret:
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break
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results = detector.detect(frame)
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frame_json_results = detector.format_results(results)
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json_results.append({"frame": frame_count, "detections": frame_json_results})
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annotated_frame = detector.draw_results(frame, results)
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out.write(annotated_frame)
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frame_count += 1
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cap.release()
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out.release()
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# Clean up temporary input video file
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os.remove(temp_video_path)
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return json_results, annotated_filename
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except Exception as e:
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print(f"Error processing video: {str(e)}")
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return None, None
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def process_task():
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print("开始处理任务,等待Kafka消息...")
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for message in consumer:
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print(f"收到Kafka消息: topic={message.topic}, partition={message.partition}, offset={message.offset}")
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task = message.value
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task_id = task['task_id']
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filename = task['filename']
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file_type = task['file_type']
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print(f"解析任务信息: ID={task_id}, 文件名={filename}, 类型={file_type}")
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file_path = os.path.join(UPLOAD_DIR, filename)
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# 检查键类型并更新状态
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task_key = f"task:{task_id}"
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try:
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key_type = main_redis_client.type(task_key)
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if key_type != b'hash':
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main_redis_client.delete(task_key)
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main_redis_client.hset(f"task:{task_id}", "status", "processing")
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print(f"任务 {task_id} 状态更新为 'processing'")
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except redis.exceptions.ResponseError as e:
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print(f"更新任务 {task_id} 状态时出错: {str(e)}")
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continue # 跳过这个任务，继续处理下一个
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try:
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if file_type == "image":
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print(f"开始处理图像: {filename}")
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with open(file_path, 'rb') as f:
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image_data = f.read()
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json_results, annotated_filename = process_image(image_data, filename)
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if json_results and annotated_filename is not None:
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result_path = os.path.join(RESULT_DIR, annotated_filename)
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redis_client.hset(f"fall_result:{task_id}", mapping={
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"result": json.dumps(json_results),
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"result_file": annotated_filename
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})
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main_redis_client.hset(f"task:{task_id}", "status", "completed")
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main_redis_client.hset(f"task:{task_id}", "result_type", "fall")
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main_redis_client.hset(f"task:{task_id}", "result_key", f"fall_result:{task_id}")
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print(f"图像 {filename} 处理完成,结果已保存")
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else:
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print(f"图像 {filename} 处理失败")
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main_redis_client.hset(f"task:{task_id}", "status", "failed")
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else: # video
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print(f"开始处理视频: {filename}")
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with open(file_path, 'rb') as f:
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video_data = f.read()
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json_results, annotated_filename = process_video(video_data, filename)
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if json_results and annotated_filename:
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redis_client.hset(f"fall_result:{task_id}", mapping={
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"result": json.dumps(json_results),
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"result_file": annotated_filename
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})
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main_redis_client.hset(f"task:{task_id}", "status", "completed")
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main_redis_client.hset(f"task:{task_id}", "result_type", "fall")
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main_redis_client.hset(f"task:{task_id}", "result_key", f"fall_result:{task_id}")
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print(f"视频 {filename} 处理完成,结果已保存")
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else:
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print(f"视频 {filename} 处理失败")
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main_redis_client.hset(f"task:{task_id}", "status", "failed")
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except Exception as e:
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print(f"处理任务 {task_id} 时出错: {str(e)}")
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main_redis_client.hset(f"task:{task_id}", {
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"status": "failed",
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"error": str(e)
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})
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print(f"任务 {task_id} 处理完毕,等待下一个Kafka消息...")
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def listen_redis_changes():
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pubsub = redis_client.pubsub()
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pubsub.psubscribe('__keyspace@3__:fall_result:*') # 监听所有fall_result键的变化
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for message in pubsub.listen():
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if message['type'] == 'pmessage':
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key = message['channel'].decode('utf-8').split(':')[-1]
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operation = message['data'].decode('utf-8')
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if operation == 'hset':
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value = redis_client.hgetall(f"fall_result:{key}")
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if value:
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result = {k.decode(): v.decode() for k, v in value.items()}
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print(f"Result update for task {key}: {result}")
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if __name__ == "__main__":
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print("fall处理程序启动...")
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# 启动处理任务的线程
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task_thread = threading.Thread(target=process_task, daemon=True)
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task_thread.start()
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print("任务处理线程已启动")
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# 启动Redis监听线程
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redis_thread = threading.Thread(target=listen_redis_changes, daemon=True)
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redis_thread.start()
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print("Redis监听线程已启动")
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print("主程序进入等待状态...")
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# 保持主线程运行
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task_thread.join()
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redis_thread.join() |