はい。私に分かることであれば・・・

@@SIN-ef5gm import cv2 import os import csv from ultralytics import YOLO from collections import defaultdict import numpy as np from datetime import datetime from shapely.geometry import Point from shapely.geometry.polygon import Polygon import threading import gc # 定期的にガベージコレクションを実行 gc.collect() # エリア設定 multiplier = 1 # カメラ1エリア設定[(右上), (右下), (左下), (左上)] area1_list = [(490, 180), (580, 280), (370, 500), (230, 420)] area2_list = [(350, 50), (470, 140), (220, 380), (100, 260)] area1 = [(x * multiplier, y * multiplier) for x, y in area1_list] area2 = [(x * multiplier, y * multiplier) for x, y in area2_list] polygon1 = Polygon(area1) polygon2 = Polygon(area2) # カメラ2エリア設定[(右上), (右下), (左下), (左上)] area3_list = [(450, 220), (580, 350), (390, 570), (170, 460)] area4_list = [(330, 50), (400, 200), (140, 430), (20, 300)] area3 = [(x * multiplier, y * multiplier) for x, y in area3_list] area4 = [(x * multiplier, y * multiplier) for x, y in area4_list] polygon3 = Polygon(area3) polygon4 = Polygon(area4) # カメラ3エリア設定[(右上), (右下), (左下), (左上)] area5_list = [(450, 220), (530, 350), (300, 570), (130, 460)] area6_list = [(280, 100), (370, 230), (80, 450), (10, 300)] area5 = [(x * multiplier, y * multiplier) for x, y in area5_list] area6 = [(x * multiplier, y * multiplier) for x, y in area6_list] polygon5 = Polygon(area5) polygon6 = Polygon(area6) # フォルダを作成してCSVファイルの保存パスを指定 output_folder = "./count" os.makedirs(output_folder, exist_ok=True) # CSVファイルの保存パス csv_file_path = "./count/overall_count.csv" # CSVファイルのヘッダー csv_header = ["Camera", "count", "area1_count", "area2_count", "Time"] # CSVファイルを開いてヘッダーを書き込み with open(csv_file_path, mode='w', newline='') as csv_file: csv_writer = csv.writer(csv_file) csv_writer.writerow(csv_header) # モデル読み込み model = YOLO('./best.pt') # カメラ情報 camera_sources = [ ("Camera1", "rtsp://root:[email protected]/axis-media/media.amp"), ("Camera2", "rtsp://root:[email protected]/axis-media/media.amp"), ("Camera3", "rtsp://root:[email protected]/axis-media/media.amp") ] # Cameraのエリア設定 camera_areas = { "Camera1": [polygon1, polygon2], "Camera2": [polygon3, polygon4], "Camera3": [polygon5, polygon6] } # ウィンドウサイズ window_sizes = { "Camera1": (640, 640), "Camera2": (640, 640), "Camera3": (640, 640) } # フォント設定 font = cv2.FONT_HERSHEY_SIMPLEX font_scale = 1.0 font_color = (255, 255, 255) font_thickness = 2 def process_camera(camera_name, camera_source): cap = cv2.VideoCapture(camera_source) track_id_to_csv = {} # idを保管する辞書 frame_count = 0 # ウィンドウの作成とサイズ設定 cv2.namedWindow(f"{camera_name} YOLOv8 Tracking", cv2.WINDOW_NORMAL) cv2.resizeWindow(f"{camera_name} YOLOv8 Tracking", *window_sizes[camera_name]) # カメラごとにエリアを設定 if camera_name == "Camera1": polygon1_camera = polygon1 polygon2_camera = polygon2 elif camera_name == "Camera2": polygon1_camera = polygon3 polygon2_camera = polygon4 elif camera_name == "Camera3": polygon1_camera = polygon5 polygon2_camera = polygon6 else: polygon1_camera = None polygon2_camera = None while cap.isOpened(): success, frame = cap.read() if success: frame_count += 1 #fram:カメラのフレーム画像 #persist=True:追跡維持 #conf=0.2:検出の信頼性のしきい値 results = model.track(frame, persist=True, conf=0.2, device='0', tracker="bytetrack.yaml") if results[0].boxes.id is None: continue boxes = results[0].boxes.xywh.cpu().numpy() # IDを取得する track_ids = results[0].boxes.id.cpu().numpy().astype(int) count = len(boxes) annotated_frame = results[0].plot() if camera_name == "Camera1": cv2.polylines(annotated_frame, [np.array(area1)], isClosed=True, color=(0, 0, 255), thickness=2) cv2.polylines(annotated_frame, [np.array(area2)], isClosed=True, color=(255, 0, 0), thickness=2) elif camera_name == "Camera2": cv2.polylines(annotated_frame, [np.array(area3)], isClosed=True, color=(0, 0, 255), thickness=2) cv2.polylines(annotated_frame, [np.array(area4)], isClosed=True, color=(255, 0, 0), thickness=2) elif camera_name == "Camera3": cv2.polylines(annotated_frame, [np.array(area5)], isClosed=True, color=(0, 0, 255), thickness=2) cv2.polylines(annotated_frame, [np.array(area6)], isClosed=True, color=(255, 0, 0), thickness=2) # 初期化 area_count1 = 0 area_count2 = 0 for box, track_id in zip(boxes, track_ids): x, y, w, h = box point = Point(float(x), float(y)) # トラックIDごとのCSVファイルを管理 if track_id not in track_id_to_csv: csv_file = os.path.join(output_folder, f"{camera_name}_track_{track_id}.csv") with open(csv_file, 'w', newline='') as csvfile: csv_writer = csv.writer(csvfile) csv_writer.writerow(["X", "Y", "area", "Time"]) # ヘッダを書き込む track_id_to_csv[track_id] = csv_file if polygon1_camera.contains(point): # cameraごとにエリアが異なるため、area1に人がいた場合 area_count1 += 1 if int(frame_count % cap.get(cv2.CAP_PROP_FPS)) == 0: # 1秒ごとに各idの位置座標を記録 with open(track_id_to_csv[track_id], 'a', newline='') as csvfile: csv_writer = csv.writer(csvfile) current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") csv_writer.writerow([x, y, "1", current_time]) if polygon2_camera.contains(point): # cameraごとにエリアが異なるため、area2に人がいた場合 area_count2 += 1 if int(frame_count % cap.get(cv2.CAP_PROP_FPS)) == 0: # 1秒ごとに各idの位置座標を記録 with open(track_id_to_csv[track_id], 'a', newline='') as csvfile: csv_writer = csv.writer(csvfile) current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") csv_writer.writerow([x, y, "2", current_time]) # 現在の時刻を取得 current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") if int(frame_count % cap.get(cv2.CAP_PROP_FPS)) == 0: # 1秒ごとに各エリアの人数を記録 # CSVファイルにデータを書き込み with open(csv_file_path, mode='a', newline='') as csv_file: csv_writer = csv.writer(csv_file) csv_writer.writerow([camera_name, count, area_count1, area_count2, current_time]) # 統一されたフォント設定で表示 cv2.putText(annotated_frame, f"count: {count}", (10, 30), font, font_scale, font_color, font_thickness) cv2.putText(annotated_frame, f"area1: {area_count1}", (10, 90), font, font_scale, (0, 0, 255), font_thickness) cv2.putText(annotated_frame, f"area2: {area_count2}", (10, 150), font, font_scale, (255, 0, 0), font_thickness) cv2.putText(annotated_frame, current_time, (450, 620), font, 0.5, (0, 0, 255), 2) cv2.imshow(f"{camera_name} YOLOv8 Tracking", annotated_frame) if cv2.waitKey(1) & 0xFF == ord("q"): break else: break cap.release() cv2.destroyAllWindows() threads = [] # 各カメラを別スレッドで処理 for camera_name, camera_source in camera_sources: thread = threading.Thread(target=process_camera, args=(camera_name, camera_source)) thread.start() threads.append(thread) # 全てのスレッドが終了するのを待機 for thread in threads: thread.join() 上記のコードでも2020/9/15の動画の様に別カメラで映った同一人物に同じIDを振り分けられる様にしたいです。 どうすれば良いでしょうか

@@SIN-ef5gm yolov8を用いて複数台のカメラから同一人物を判定する方法について教えていただきたいです。

The code will be released. I'm preparing a blog now. * I'm sorry, but it will be Japanese thank you

dev.classmethod.jp/articles/yolov5-nvidia-jetson-agx-orin/

Here it is dev.classmethod.jp/articles/m5stack-core2-for-aws-dozing/

@@SIN-ef5gm Thanks, i can install in the version core2, or only for core2 Amazon?

sorry I don't have the time

@@SIN-ef5gm No worries. I'm stuck and need some help. Could you be able to help me though?