128 lines
4.1 KiB
Python
128 lines
4.1 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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可视化视频中的棋盘格检测
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实时显示每一帧的检测结果
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"""
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import cv2
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import numpy as np
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class ChessboardVisualizer:
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def __init__(self, pattern_size=(11, 8)):
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"""
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初始化可视化器
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Args:
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pattern_size: 棋盘格内角点数量 (列, 行)
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"""
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self.pattern_size = pattern_size
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self.criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
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def visualize_video(self, video_path, output_path='visualized_video.avi', show_window=False):
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"""
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可视化整个视频的棋盘格检测
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Args:
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video_path: 输入视频路径
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output_path: 输出视频路径
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show_window: 是否显示实时窗口
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"""
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cap = cv2.VideoCapture(video_path)
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if not cap.isOpened():
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print(f"无法打开视频: {video_path}")
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return
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# 获取视频参数
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fps = cap.get(cv2.CAP_PROP_FPS)
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width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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print(f"视频信息: {width}x{height}, {fps:.2f} FPS, {total_frames} 帧")
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# 创建视频写入器
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fourcc = cv2.VideoWriter_fourcc(*'XVID')
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out = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
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frame_count = 0
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detected_count = 0
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print(f"\n开始处理视频...")
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print("绿色角点 = 检测成功, 红色文字 = 未检测到")
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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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break
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frame_count += 1
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# 转换为灰度图
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gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
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# 检测棋盘格
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ret_detect, corners = cv2.findChessboardCorners(gray, self.pattern_size, None)
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# 创建可视化图像
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vis_frame = frame.copy()
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if ret_detect:
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detected_count += 1
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# 亚像素精度优化
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corners = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), self.criteria)
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# 绘制角点
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cv2.drawChessboardCorners(vis_frame, self.pattern_size, corners, ret_detect)
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# 添加成功标记
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cv2.putText(vis_frame, f'DETECTED #{detected_count}', (20, 40),
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cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
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else:
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# 添加未检测标记
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cv2.putText(vis_frame, 'NOT DETECTED', (20, 40),
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cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
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# 添加帧信息
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cv2.putText(vis_frame, f'Frame: {frame_count}/{total_frames}', (20, height - 20),
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cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 2)
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# 写入输出视频
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out.write(vis_frame)
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# 显示窗口（可选）
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if show_window:
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cv2.imshow('Chessboard Detection', vis_frame)
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if cv2.waitKey(1) & 0xFF == ord('q'):
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print("\n用户中断")
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break
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# 进度显示
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if frame_count % 50 == 0:
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progress = 100 * frame_count / total_frames
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print(f" 进度: {frame_count}/{total_frames} ({progress:.1f}%) - 已检测: {detected_count}")
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cap.release()
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out.release()
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if show_window:
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cv2.destroyAllWindows()
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print(f"\n✓ 处理完成!")
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print(f" 总帧数: {frame_count}")
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print(f" 检测成功: {detected_count} 帧 ({100*detected_count/frame_count:.1f}%)")
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print(f" 输出文件: {output_path}")
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def main():
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VIDEO_PATH = 'Video_20260303114232727.avi'
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OUTPUT_PATH = 'visualized_chessboard_detection.avi'
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PATTERN_SIZE = (11, 8)
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visualizer = ChessboardVisualizer(pattern_size=PATTERN_SIZE)
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visualizer.visualize_video(VIDEO_PATH, OUTPUT_PATH, show_window=False)
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if __name__ == '__main__':
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main()
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