82 lines
1.8 KiB
Python
82 lines
1.8 KiB
Python
# config.py
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import os
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# Kafka配置
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KAFKA_BROKER = "222.186.10.253:9092"
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KAFKA_GROUP_ID_PREFIX = "group"
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# Redis配置
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REDIS_HOST = "150.158.144.159"
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REDIS_PORT = 13003
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REDIS_PASSWORD = "Obscura@2024"
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MAIN_REDIS_DB = 0
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REDIS_API_DB = 2
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REDIS_API_USAGE_DB = 3
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# 目录配置
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UPLOAD_DIR = "/obscura/task/upload"
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RESULT_DIR = "/obscura/task/result"
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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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# 模型配置
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YOLO_MODEL_PATH = "/obscura/models/yolov8x.pt"
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POSE_MODEL_PATH = "/obscura/models/yolov8x-pose.pt"
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QWEN_MODEL_PATH = "/obscura/models/qwen/Qwen2-VL-2B-Instruct"
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FALL_MODEL_PATH = "/obscura/models/yolov8n-fall.pt"
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FACE_MODEL_PATH = "/obscura/models/yolov8n-face.pt"
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MEDIAPIPE_MODEL_PATH = "/obscura/models/face_landmarker.task"
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# COMPARE_MODEL_PATH = "/obscura/models/insightface/insw_r100_glint360k.onnx"
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# Ollama配置
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OLLAMA_URL = "http://127.0.0.1:11434/api/generate"
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# 各个worker的配置
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WORKER_CONFIGS = {
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"yolo": {
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"kafka_topic": "yolo",
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"redis_db": 4,
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},
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"pose": {
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"kafka_topic": "pose",
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"redis_db": 5,
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},
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"qwenvl": {
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"kafka_topic": "qwenvl",
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"redis_db": 9,
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},
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"qwenvl_analyze": {
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"kafka_topic": "qwenvl_analyze",
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"redis_db": 32,
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},
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"cpm": {
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"kafka_topic": "cpm",
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"redis_db": 8,
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},
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"cpm_analyze": {
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"kafka_topic": "cpm_analyze",
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"redis_db": 31,
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},
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"fall": {
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"kafka_topic": "fall",
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"redis_db": 6,
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},
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"face": {
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"kafka_topic": "face",
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"redis_db": 7,
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},
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"mediapipe": {
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"kafka_topic": "mediapipe",
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"redis_db": 10,
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},
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"compare": {
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"kafka_topic": "compare",
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"redis_db": 30,
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}
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}
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# GPU设置
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CUDA_DEVICE_0 = "cuda:0"
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CUDA_DEVICE_1 = "cuda:1"
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