From 523dbf77d19ddf96bd6a22cead54d60637563db5 Mon Sep 17 00:00:00 2001
From: Sergey Revyakin <revyakin8800@gmail.com>
Date: Thu, 9 Apr 2026 11:22:12 +0700
Subject: [PATCH] =?UTF-8?q?=D0=B4=D0=BE=D0=B1=D0=B0=D0=B2=D0=B8=D0=BB=20dr?=
 =?UTF-8?q?one=5Fstreaks?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 NN_server/server.py | 51 +++++++++++++++++++++++++++++++++++----------
 1 file changed, 40 insertions(+), 11 deletions(-)

diff --git a/NN_server/server.py b/NN_server/server.py
index d5d1c06..067f849 100644
--- a/NN_server/server.py
+++ b/NN_server/server.py
@@ -3,6 +3,7 @@ from dotenv import dotenv_values
 from common.runtime import load_root_env, validate_env, as_int, as_str
 import os
 import sys
+import re
 import matplotlib.pyplot as plt
 from Model import Model
 import numpy as np
@@ -49,13 +50,47 @@ validate_env("NN_server/server.py", {
 })
 config = dict(dotenv_values(ROOT_ENV))
 
+
+def is_model_config_key(key, value):
+    return bool(re.fullmatch(r"NN_\d+", key or "")) and isinstance(value, str) and " && " in value
+
+
+def get_required_drone_streak(freq):
+    raw_value = config.get(f"DRONE_STREAK_{freq}", "1")
+    try:
+        return max(1, int(raw_value))
+    except (TypeError, ValueError):
+        logging.warning("Invalid DRONE_STREAK_%s=%r, falling back to 1", freq, raw_value)
+        return 1
+
+
+def update_drone_streak(freq, prediction):
+    if prediction == "drone":
+        drone_streaks[freq] = drone_streaks.get(freq, 0) + 1
+    else:
+        drone_streaks[freq] = 0
+
+    required = get_required_drone_streak(freq)
+    triggered = prediction == "drone" and drone_streaks[freq] >= required
+    logging.info(
+        "NN alarm gate freq=%s prediction=%s streak=%s/%s triggered=%s",
+        freq,
+        prediction,
+        drone_streaks[freq],
+        required,
+        triggered,
+    )
+    return 8 if triggered else 0
+
+
 if not config:
     raise RuntimeError("[NN_server/server.py] .env was loaded but no keys were parsed")
-if not any(key.startswith("NN_") for key in config):
+if not any(is_model_config_key(key, value) for key, value in config.items()):
     raise RuntimeError("[NN_server/server.py] no NN_* model entries configured")
 logging.info("NN config loaded from %s", ROOT_ENV)
 gen_server_ip = config['GENERAL_SERVER_IP']
 gen_server_port = config['GENERAL_SERVER_PORT']
+drone_streaks = {}
 
 def init_data_for_inference():
     try:
@@ -71,9 +106,9 @@ def init_data_for_inference():
 
     try:
         global model_list
-        for key in config.keys():
-            if key.startswith('NN_'):
-                params = config[key].split(' && ')
+        for key, value in config.items():
+            if is_model_config_key(key, value):
+                params = value.split(' && ')
                 module = importlib.import_module('Models.' + params[4])
                 classes = {}
                 for value in params[9][1:-1].split(','):
@@ -137,13 +172,7 @@ def receive_data():
                 print()
                 
                 try:
-                    result = 0
-                    if (int(freq) == 2400 and (prediction_list[0] in ['drone', 'drone_noise'] or (prediction_list[0] == 'wifi' and float(probability) >= 0.95))) or (int(freq) == 1200 and (prediction_list[0] in ['drone'] and float(probability) >= 0.95)):
-                        result += 8
-                    if int(freq) in [915]:
-                        result = 0
-                    if int(freq) in []:
-                        result = 8
+                    result = update_drone_streak(freq, prediction_list[0])
                     data_to_send={
                         'freq': str(freq),
                         'amplitude': result