121 lines
3.5 KiB
Python
121 lines
3.5 KiB
Python
import os
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import cv2
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from rknnlite.api import RKNNLite
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# classify_single_image, StableClassJudge, CLASS_NAMES 已在 muju_cls_rknn 中定义
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from muju_cls_rknn import classify_single_image, StableClassJudge, CLASS_NAMES
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def run_stable_classification_loop(
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model_path,
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roi_file,
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image_source,
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stable_frames=3,
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display_scale=0.5, # 显示缩放比例（0.5 = 显示为原来 50%）
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show_window=False # 是否显示窗口
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):
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"""
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image_source: cv2.VideoCapture 对象
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"""
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judge = StableClassJudge(
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stable_frames=stable_frames,
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ignore_class=2 # 忽略“有遮挡”类别参与稳定判断
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)
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cap = image_source
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if not hasattr(cap, "read"):
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raise TypeError("image_source 必须是 cv2.VideoCapture 实例")
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# 可选：创建可缩放窗口
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if show_window:
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cv2.namedWindow("RTSP Stream - Press 'q' to quit", cv2.WINDOW_NORMAL)
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while True:
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ret, frame = cap.read()
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if not ret:
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print("无法读取视频帧（可能是流断开或结束）")
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break
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# 上下左右翻转
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frame = cv2.flip(frame, -1)
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# ---------------------------
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# 单帧推理
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# ---------------------------
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result = classify_single_image(frame, model_path, roi_file)
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class_id = result["class_id"]
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class_name = result["class"]
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score = result["score"]
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print(f"[FRAME] {class_name} | conf={score:.3f}")
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# ---------------------------
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# 稳定判断
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# ---------------------------
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stable_class_id = judge.update(class_id)
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if stable_class_id is not None:
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print(f"\n稳定输出: {CLASS_NAMES[stable_class_id]}\n")
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# ---------------------------
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# 显示画面（缩小窗口）
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# ---------------------------
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if show_window:
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h, w = frame.shape[:2]
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display_frame = cv2.resize(
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frame,
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(int(w * display_scale), int(h * display_scale)),
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interpolation=cv2.INTER_AREA
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)
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cv2.imshow("RTSP Stream - Press 'q' to quit", display_frame)
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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cap.release()
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cv2.destroyAllWindows()
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if __name__ == "__main__":
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# ---------------------------
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# 配置参数
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# ---------------------------
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MODEL_PATH = "muju_cls.rknn"
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ROI_FILE = "./roi_coordinates/muju_roi.txt"
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RTSP_URL = "rtsp://admin:XJ123456@192.168.250.61:554/streaming/channels/101"
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STABLE_FRAMES = 3
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DISPLAY_SCALE = 0.5 # 显示窗口缩放比例
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SHOW_WINDOW = False # 部署时改成 False，测试的时候打开
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# ---------------------------
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# 打开 RTSP 视频流
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# ---------------------------
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print(f"正在连接 RTSP 流: {RTSP_URL}")
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cap = cv2.VideoCapture(RTSP_URL)
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# 降低 RTSP 延迟（部分摄像头支持）
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cap.set(cv2.CAP_PROP_BUFFERSIZE, 1)
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if not cap.isOpened():
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print("无法打开 RTSP 流，请检查网络、账号密码或 URL")
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exit(1)
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print("RTSP 流连接成功，开始推理...")
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# ---------------------------
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# 启动稳定分类循环三帧稳定判断
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# ---------------------------
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run_stable_classification_loop(
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model_path=MODEL_PATH,
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roi_file=ROI_FILE,
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image_source=cap,
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stable_frames=STABLE_FRAMES,
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display_scale=DISPLAY_SCALE,
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show_window=SHOW_WINDOW
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)
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