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PYTHON WORLD ( PYTHON | JAVA | C | C++ | HTML )

PYTHON WORLD ( PYTHON | JAVA | C | C++ | HTML )

前往频道在 Telegram

Senior Analyst at Capgemini Channel link :- https://t.me/python_world_in (You can share with friends) 👉 Get materials for MNC's. 👉 Off campus recruitment updates. 👉 Interview Experiences. 👉 And all the placement related information at

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📈 Telegram 频道 PYTHON WORLD ( PYTHON | JAVA | C | C++ | HTML ) 的分析概览

频道 PYTHON WORLD ( PYTHON | JAVA | C | C++ | HTML ) (@python_world_in) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 14 403 名订阅者,在 技术与应用 类别中位列第 8 985,并在 印度 地区排名第 29 819

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 14 403 名订阅者。

根据 18 六月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 -183,过去 24 小时变化为 -8,整体触达仍然可观。

  • 认证状态: 未认证
  • 互动率 (ER): 平均受众互动率为 8.41%。内容发布后 24 小时内通常能获得 1.92% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 1 212 次浏览,首日通常累积 277 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 2
  • 主题关注点: 内容集中在 internship, engineer, graduate, intern, analytic 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台:
Senior Analyst at Capgemini Channel link :- https://t.me/python_world_in (You can share with friends) 👉 Get materials for MNC's. 👉 Off campus recruitment updates. 👉 Interview Experiences. 👉 And all the placement related information at

凭借高频更新(最新数据采集于 19 六月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。

14 403
订阅者
-824 小时
-577
-18330
帖子存档
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import cv2 import mediapipe as mp from math import hypot from ctypes import cast, POINTER from comtypes import CLSCTX_ALL from pycaw.pycaw import AudioUtilities, IAudioEndpointVolume import numpy as np cap = cv2.VideoCapture(1) mpHands = mp.solutions.hands hands = mpHands.Hands() mpDraw = mp.solutions.drawing_utils devices = AudioUtilities.GetSpeakers() interface = devices.Activate(IAudioEndpointVolume._iid_, CLSCTX_ALL, None) volume = cast(interface, POINTER(IAudioEndpointVolume)) volMin, volMax = volume.GetVolumeRange()[:2] current_vol = volume.GetMasterVolumeLevel() # Smoothing parameters alpha = 0.2 # Adjust this value for smoother changes while True: success, img = cap.read() imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) results = hands.process(imgRGB) lmList = [] if results.multi_hand_landmarks: for handlandmark in results.multi_hand_landmarks: for id, lm in enumerate(handlandmark.landmark): h, w, _ = img.shape cx, cy = int(lm.x * w), int(lm.y * h) lmList.append([id, cx, cy]) mpDraw.draw_landmarks(img, handlandmark, mpHands.HAND_CONNECTIONS) if lmList: x1, y1 = lmList[4][1], lmList[4][2] x2, y2 = lmList[8][1], lmList[8][2] cv2.circle(img, (x1, y1), 4, (255, 0, 0), cv2.FILLED) cv2.circle(img, (x2, y2), 4, (255, 0, 0), cv2.FILLED) cv2.line(img, (x1, y1), (x2, y2), (255, 0, 0), 3) length = hypot(x2 - x1, y2 - y1) target_vol = np.interp(length, [15, 220], [volMin, volMax]) current_vol = alpha * target_vol + (1 - alpha) * current_vol # Smoothing volume.SetMasterVolumeLevel(current_vol, None) # Display rounded volume level on the screen cv2.putText(img, f"Vol: {int(round(current_vol))}%", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2) cv2.imshow('Image', img) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()

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