从 Opencv 保存视频

Question

我使用灰色高斯模糊创建空间检测代码，但现在我不知道将这些代码放在哪里来保存我的 opencv 视频。
我已经尝试将代码放在随机行中，但它只在输出文件中出现，我无法播放，视频也只有 5.6KB。我什至尝试录制视频很长时间。
我的代码在没有保存功能的情况下运行良好，但我想添加保存视频功能：

fourcc = open_cv.VideoWriter_fourcc(*'DIVX')
out = open_cv.VideoWriter('output.avi',fourcc, 20.0, (640,480))

这些是我想从上面添加保存视频编码的代码：

import cv2 as open_cv
import numpy as np
import logging
from drawing_utils import draw_contours
from colors import COLOR_GREEN, COLOR_WHITE, COLOR_BLUE


class MotionDetector:
    LAPLACIAN = 1.4
    DETECT_DELAY = 1
    

    def __init__(self, video, coordinates, start_frame):
        self.video = 0
        self.coordinates_data = coordinates
        self.start_frame = start_frame
        self.contours = []
        self.bounds = []
        self.mask = []

    def detect_motion(self):
        capture = open_cv.VideoCapture(self.video)
        capture.set(open_cv.CAP_PROP_POS_FRAMES, self.start_frame)

        coordinates_data = self.coordinates_data
        logging.debug("coordinates data: %s", coordinates_data)
        
        for p in coordinates_data:
            coordinates = self._coordinates(p)
            logging.debug("coordinates: %s", coordinates)

            rect = open_cv.boundingRect(coordinates)
            logging.debug("rect: %s", rect)

            new_coordinates = coordinates.copy()
            new_coordinates[:, 0] = coordinates[:, 0] - rect[0]
            new_coordinates[:, 1] = coordinates[:, 1] - rect[1]
            logging.debug("new_coordinates: %s", new_coordinates)

            self.contours.append(coordinates)
            self.bounds.append(rect)

            mask = open_cv.drawContours(
                np.zeros((rect[3], rect[2]), dtype=np.uint8),
                [new_coordinates],
                contourIdx=-1,
                color=255,
                thickness=-1,
                lineType=open_cv.LINE_8)

            mask = mask == 255
            self.mask.append(mask)
            logging.debug("mask: %s", self.mask)

        statuses = [False] * len(coordinates_data)
        times = [None] * len(coordinates_data)
        

        while capture.isOpened():
            result, frame = capture.read()
            if frame is None:
                break

            if not result:
                raise CaptureReadError("Error reading video capture on frame %s" % str(frame))

            blurred = open_cv.GaussianBlur(frame.copy(), (5, 5), 3)
            grayed = open_cv.cvtColor(blurred, open_cv.COLOR_BGR2GRAY)
            new_frame = frame.copy()
            logging.debug("new_frame: %s", new_frame)

            position_in_seconds = capture.get(open_cv.CAP_PROP_POS_MSEC) / 1000.0

            for index, c in enumerate(coordinates_data):
                status = self.__apply(grayed, index, c)

                if times[index] is not None and self.same_status(statuses, index, status):
                    times[index] = None
                    continue

                if times[index] is not None and self.status_changed(statuses, index, status):
                    if position_in_seconds - times[index] >= MotionDetector.DETECT_DELAY:
                        statuses[index] = status
                        times[index] = None
                    continue

                if times[index] is None and self.status_changed(statuses, index, status):
                    times[index] = position_in_seconds

            for index, p in enumerate(coordinates_data):
                coordinates = self._coordinates(p)

                color = COLOR_GREEN if statuses[index] else COLOR_BLUE
                draw_contours(new_frame, coordinates, str(p["id"] + 1), COLOR_WHITE, color)

            open_cv.imshow(str(self.video), new_frame)
            k = open_cv.waitKey(1)
            if k == ord("q"):
                break
                
    
        capture.release()
        open_cv.destroyAllWindows()

    def __apply(self, grayed, index, p):
        coordinates = self._coordinates(p)
        logging.debug("points: %s", coordinates)

        rect = self.bounds[index]
        logging.debug("rect: %s", rect)

        roi_gray = grayed[rect[1]:(rect[1] + rect[3]), rect[0]:(rect[0] + rect[2])]
        laplacian = open_cv.Laplacian(roi_gray, open_cv.CV_64F)
        logging.debug("laplacian: %s", laplacian)

        coordinates[:, 0] = coordinates[:, 0] - rect[0]
        coordinates[:, 1] = coordinates[:, 1] - rect[1]

        status = np.mean(np.abs(laplacian * self.mask[index])) < MotionDetector.LAPLACIAN
        logging.debug("status: %s", status)

        return status
    
    @staticmethod
    def _coordinates(p):
        return np.array(p["coordinates"])

    @staticmethod
    def same_status(coordinates_status, index, status):
        return status == coordinates_status[index]

    @staticmethod
    def status_changed(coordinates_status, index, status):
        return status != coordinates_status[index]


class CaptureReadError(Exception):
    pass

Answer 1

为要进入的视频创建文件。您可以将此文件视为一本书，但实际上是一本没有页面的书。此代码用于创建文件：

fourcc = open_cv.VideoWriter_fourcc(*'DIVX')
out = open_cv.VideoWriter('output.avi',fourcc, 20.0, (640,480))

并非所有编解码器都适用于所有系统。我使用 Ubuntu，这是我用来创建视频文件的代码：

out = cv2.VideoWriter('output.avi',cv2.VideoWriter_fourcc('M','J','P','G'), 30,(w,h))

如果您尝试播放此视频，则不会发生任何事情。视频中没有帧，所以没有可播放的内容（就像一本没有页面的书）。处理完每一帧后，需要将帧写入视频（就像在书中放一页一样）：

out.write(new_frame)

你应该在.imshow()附近这样做：

out.write(new_frame)
open_cv.imshow(str(self.video), new_frame)
k = open_cv.waitKey(1)
if k == ord("q"):
    break