137 lines
4.8 KiB
Python
137 lines
4.8 KiB
Python
import cv2
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import time
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import os
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import numpy as np
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from PIL import Image
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from skimage.metrics import structural_similarity as ssim
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import shutil
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# ================== 配置参数 ==================
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rtsp_url = "rtsp://192.168.144.25:8554/main.264" # RTSP 流地址
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capture_interval = 1.0 # 每隔多少秒采集一次（单位：秒）
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SSIM_THRESHOLD = 0.9 # SSIM 相似度阈值，>0.9 认为太像
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output_dir = os.path.join("userdata", "image") # 图片保存路径
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# 灰色判断参数
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GRAY_LOWER = 70
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GRAY_UPPER = 230
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GRAY_RATIO_THRESHOLD = 0.7
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# 创建输出目录
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if not os.path.exists(output_dir):
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os.makedirs(output_dir)
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print(f"已创建目录: {output_dir}")
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def is_large_gray(image, gray_lower=GRAY_LOWER, gray_upper=GRAY_UPPER, ratio_thresh=GRAY_RATIO_THRESHOLD):
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"""
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判断图片是否大面积为灰色（R/G/B 都在 [gray_lower, gray_upper] 区间）
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"""
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img_array = np.array(image)
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if len(img_array.shape) != 3 or img_array.shape[2] != 3:
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return True # 非三通道图视为无效/灰色
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h, w, _ = img_array.shape
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total = h * w
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gray_mask = (
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(img_array[:, :, 0] >= gray_lower) & (img_array[:, :, 0] <= gray_upper) &
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(img_array[:, :, 1] >= gray_lower) & (img_array[:, :, 1] <= gray_upper) &
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(img_array[:, :, 2] >= gray_lower) & (img_array[:, :, 2] <= gray_upper)
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)
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gray_pixels = np.sum(gray_mask)
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gray_ratio = gray_pixels / total
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return gray_ratio > ratio_thresh
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max_retry_seconds = 10 # 最大重试时间为10秒
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retry_interval_seconds = 1 # 每隔1秒尝试重新连接一次
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last_gray = None # 用于 SSIM 去重
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while True: # 外层循环用于处理重新连接逻辑
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cap = cv2.VideoCapture(rtsp_url)
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start_time = time.time() # 记录开始尝试连接的时间
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while not cap.isOpened():
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if time.time() - start_time >= max_retry_seconds:
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print(f"已尝试重新连接 {max_retry_seconds} 秒，但仍无法获取视频流。")
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exit()
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print("无法打开摄像头，正在尝试重新连接...")
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time.sleep(retry_interval_seconds)
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cap = cv2.VideoCapture(rtsp_url)
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print("✅ 开始读取视频流...")
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last_capture_time = time.time()
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frame_count = 0
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try:
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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("读取帧失败，可能是流中断或摄像头断开")
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cap.release()
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break
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current_time = time.time()
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if current_time - last_capture_time < capture_interval:
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continue
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frame_count += 1
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last_capture_time = current_time
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print(f"处理帧 {frame_count}")
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rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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pil_image = Image.fromarray(rgb_frame)
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if is_large_gray(pil_image):
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print(f"跳过：大面积灰色图像 (frame_{frame_count})")
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continue
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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if last_gray is not None:
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similarity = ssim(gray, last_gray)
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if similarity > SSIM_THRESHOLD:
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print(f"跳过：与上一帧太相似 (SSIM={similarity:.3f})")
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continue
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last_gray = gray.copy()
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timestamp = time.strftime("%Y%m%d_%H%M%S")
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ms = int((time.time() % 1) * 1000)
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filename = f"frame_{timestamp}_{ms:03d}.png"
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filepath = os.path.join(output_dir, filename)
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total, used, free = shutil.disk_usage(output_dir)
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if free < 1024 * 1024 * 20: # 小于 20MB 就停止
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print(f"❌ 磁盘空间严重不足（仅剩 {free / (1024**3):.2f} GB），停止运行。")
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raise SystemExit(1)
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try:
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pil_image.save(filepath, format='PNG')
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print(f"已保存: {filepath}")
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except (OSError, IOError) as e:
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error_msg = str(e)
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if "No space left on device" in error_msg or "disk full" in error_msg.lower() or "quota" in error_msg.lower():
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print(f"磁盘空间不足，无法保存 {filepath}！错误: {e}")
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print("停止程序以防止无限错误。")
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raise SystemExit(1)
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else:
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print(f"保存失败 {filename}: {e}（非磁盘空间问题，继续运行）")
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cv2.imshow('Camera Stream (Live)', frame)
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if cv2.waitKey(1) & 0xFF == ord('q'):
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raise KeyboardInterrupt
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except KeyboardInterrupt:
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print("\n用户中断")
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break
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finally:
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cap.release()
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cv2.destroyAllWindows()
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print(f"视频流已关闭，共处理 {frame_count} 帧。")
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print("程序结束") |