opencv - 您如何将对象检测器应用于给定视频的每一帧？

Question

我之前在这个网站上发布过代码，我了解到我不能发布整个内容。所以，我只会发布重要的代码。

所以，我想做的是获取一个对象检测器(用于图像)并将其应用于给定视频的每一帧。

唯一的问题是我不知道如何完成它。也就是说，一旦我检测到第一帧，我该怎么处理这个帧？我把它存放在某个地方吗？我该如何处理其他框架？一旦我处理了这些帧，我如何将这些帧重新组合成一个视频，即输出视频？

这是代码:

import numpy as np
import cv2
from numpy import expand_dims
from keras.models import load_model
from keras.preprocessing.image import load_img
from keras.preprocessing.image import img_to_array
from matplotlib import pyplot
from matplotlib.patches import Rectangle

model = load_model('model.h5')

# define the expected input shape for the model
input_w, input_h = 416, 416

# define the anchors
anchors = [[116,90, 156,198, 373,326], [30,61, 62,45, 59,119], [10,13, 16,30, 33,23]]

# define the labels
labels = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck",
    "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench",
    "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe",
    "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard",
    "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard",
    "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana",
    "apple", "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut", "cake",
    "chair", "sofa", "pottedplant", "bed", "diningtable", "toilet", "tvmonitor", "laptop", "mouse",
    "remote", "keyboard", "cell phone", "microwave", "oven", "toaster", "sink", "refrigerator",
    "book", "clock", "vase", "scissors", "teddy bear", "hair drier", "toothbrush"]

vs = cv2.VideoCapture('video.mp4')

class_threshold = 0.6
boxes = list()

while True:
    (grabbed, frame) = vs.read()

    if not grabbed:
        break

    if W is None or H is None:
        (H, W) = frame.shape[:2]

    image, image_w, image_h = load_image_pixels(frame, (input_w, input_h))
    yhat = model.predict(image)

    for i in range(len(yhat)):
        # decode the output of the network
        boxes += decode_netout(yhat[i][0], anchors[i], class_threshhold, input_h, input_w)
    # correct the sizes of the bounding boxes for the shape of the image
    correct_yolo_boxes(boxes, image_h, image_w, input_h, input_w)
    # suppress non-maximal boxes
    do_nms(boxes, 0.5)

    # get the details of the detected objects
    v_boxes, v_labels, v_scores = get_boxes(boxes, labels, class_threshold)

    # draw what we found
    draw_boxes(frame, v_boxes, v_labels, v_scores)

Answer 1

您可以使用 VideoWriter从opencv再次将帧输出为视频。

关于如何使用它的一些示例代码:

fourcc = cv2.VideoWriter_fourcc(*'XVID')
video_writer = cv2.VideoWriter('test.avi', fourcc, 30, (image_w, image_h))
...
while True:
    ....
    video_writer.write(frame)
    ....
....
video_writer.release()

供引用 openCV video saving in python