upload

Former-commit-id: 3af1a19b5b0e0bb4dbc367468b36c62aa8762a91

tmp.py

@@ -1,80 +1,23 @@
-import numpy as np
-
-class DistributionChangeDetector:
-    def __init__(self, baseline_windows: list[np.ndarray]):
-        """
-        参数 baseline_windows: List of arrays，代表初始稳定期的多个窗口
-        """
-        self.baseline = self._compute_baseline(baseline_windows)
-
-    def _compute_stats(self, window: np.ndarray) -> tuple[float, float, float]:
-        """返回 (P_under30, std, mode)"""
-        p_under30 = np.mean(window < 30)
-        std = np.std(window, ddof=1)
-        
-        # 快速估计众数：最大 bin 的中心
-        hist, bin_edges = np.histogram(window, bins=50)
-        max_bin_index = np.argmax(hist)
-        mode_est = (bin_edges[max_bin_index] + bin_edges[max_bin_index + 1]) / 2
-        return p_under30, std, mode_est
-
-    def _compute_baseline(self, windows: list[np.ndarray]) -> tuple[np.ndarray, np.ndarray]:
-        """
-        返回 baseline 向量 (P0, σ0, mode0) 和对应标准差（用于归一化）
-        """
-        stats = np.array([self._compute_stats(w) for w in windows])
-        mean = stats.mean(axis=0)
-        std = stats.std(axis=0) + 1e-6  # 防止除0
-        return mean, std
-
-    def update(self, window: np.ndarray) -> float:
-        """
-        输入：当前窗口数据（长度 = 窗口大小）
-        输出：变化分数（越大表示分布越偏离基准）
-        """
-        x = np.array(self._compute_stats(window))
-        mean, std = self.baseline
-        norm_diff = (x - mean) / std
-        change_score = np.linalg.norm(norm_diff)
-        return float(change_score)
+from datetime import datetime
+import json
+import requests
+import time
+from utils import login_to_platform,send_data_to_platform
 
 
-import cv2
-def gen_data():
-    cap = cv2.VideoCapture()
-    cap.open(1)
-    while True:
-        ret, frame = cap.read()
-        cv2.imshow("Camera Feed", frame)
-        if not ret:
-            break
-        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
-        s = hsv[:, :, 1]  # 直接提取饱和度通道
-        s = s[s > 0]  # 只保留非零饱和度值，减少噪声
-        yield s
-        if cv2.waitKey(1) & 0xFF == ord('a'):
-            break
+token = login_to_platform("13504022184","password")
 
+def format_date_time(timestamp):
+    return datetime.fromtimestamp(timestamp).strftime("%Y-%m-%d %H:%M:%S")
 
-gen = gen_data()
-baseline_data = [gen.__next__() for _ in range(5)]  # 获取10个窗口作为基线
-
-det = DistributionChangeDetector(baseline_data)
-
-
-
-results = []
-for x in gen:
-    out = det.update(x)
-    if out is not None:
-        results.append(out)
-
-
-# 作图查看
-import matplotlib.pyplot as plt
-plt.plot(results, label="ChangeScore")
-plt.xlabel("Window index")
-plt.ylabel("Score")
-plt.title("Streaming Change Detection")
-plt.legend()
-plt.show()
+print(token)
+final_data ={
+    'start_time': '2025-06-17 14:59:33', 
+    'end_time': '2025-06-17 15:01:18', 
+    'volume_record': '[0.8, 1.6, 2.4000000000000004, 3.2, 4.0, 4.8, 5.6, 6.3999999999999995, 7.199999999999999, 7.999999999999999, 8.799999999999999, 9.6, 10.4, 11.200000000000001, 12.000000000000002, 12.800000000000002, 13.200000000000003, 13.600000000000003, 14.000000000000004, 14.400000000000004, 14.800000000000004, 15.200000000000005, 15.600000000000005, 16.000000000000004, 16.400000000000002, 16.8, 17.2, 17.599999999999998, 17.999999999999996, 18.399999999999995, 18.799999999999994, 19.199999999999992, 19.59999999999999, 19.99999999999999, 20.399999999999988, 20.799999999999986, 21.199999999999985, 21.599999999999984, 21.999999999999982, 22.39999999999998, 22.79999999999998, 23.199999999999978, 23.599999999999977, 23.999999999999975, 24.399999999999974, 24.799999999999972, 25.19999999999997, 25.59999999999997, 25.999999999999968, 26.399999999999967, 26.799999999999965, 27.199999999999964, 27.599999999999962, 27.99999999999996, 28.39999999999996, 28.447450351715048, 28.49745035171505, 28.54745035171505, 28.59745035171505, 28.98371173143383, 28.781944286823233, 28.761131591796836]',
+    'voltage_record': "[]", 
+    'color_record': "['transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'transport', 'middle', 'transport', 'transport', 'transport', 'transport', 'middle', 'colored']", 
+    'final_volume': "28.761131591796836"
+}
+# print(json.dumps(final_data))
+send_data_to_platform(token, final_data, "im.jpg")