Question

我想创建一个csv文件，当我进入python shell窗口时，该文件应具有每个对象的坐标。

import cv2
import pandas as pd


# capture frames from a video
cap = cv2.VideoCapture('video.avi')

# Trained XML classifiers describes some features of some object we want 
to detect
car_cascade = cv2.CascadeClassifier('cars.xml')

no_obj_det=0
frames_got_processed = 0
frame_processed = []
number_of_object_detected= []

# loop runs if capturing has been initialized.
while True:
# reads frames from a video
  try:
    ret, frames = cap.read()
    frames_got_processed += 1
    # convert to gray scale of each frames
    gray = cv2.cvtColor(frames, cv2.COLOR_BGR2GRAY)
    # Detects cars of different sizes in the input image
    cars = car_cascade.detectMultiScale(gray, 1.1, 1)
    # To draw a rectangle in each cars
    for (x,y,w,h) in cars:
        cv2.rectangle(frames,(x,y),(x+w,y+h),(0,0,255),2)

    cv2.imshow('video2', frames)
    if cv2.waitKey(33) == 27:
        break

    # loop to count the number of objects detected at every 5th frame
    if frames_got_processed % 5 == 0:

        print "appended in frame 
        number",frames_got_processed,len(cars),cars
        frame_processed.append(frames_got_processed)
        number_of_object_detected.append(len(cars))

df.to_csv('example.csv')


# De-allocate any associated memory usage
cv2.destroyAllWindows()

在python shell上输出我想要在csv文件中的相同输出 [1]：https://i.stack.imgur.com/vfPEP.png

Answer 1

由于您可能需要连续向CSV写入数据，因此最好在执行时进行此操作，而不是尝试附加所有数据然后将其写入末尾。这样可以避免最终耗尽内存。

Python csv库可用于执行以下操作：

import cv2
import csv

# capture frames from a video
cap = cv2.VideoCapture('video.avi')

# Trained XML classifiers describes some features of some object we want to detect
car_cascade = cv2.CascadeClassifier('cars.xml')

frames_got_processed = 0

with open('example.csv', 'w', newline='') as f_output:
    csv_output = csv.writer(f_output)

    # loop runs if capturing has been initialized.
    while True:
    # reads frames from a video
        try:
            ret, frames = cap.read()
            frames_got_processed += 1
            # convert to gray scale of each frames
            gray = cv2.cvtColor(frames, cv2.COLOR_BGR2GRAY)
            # Detects cars of different sizes in the input image
            cars = car_cascade.detectMultiScale(gray, 1.1, 1)
            # To draw a rectangle in each cars
            for (x,y,w,h) in cars:
                cv2.rectangle(frames,(x,y),(x+w,y+h),(0,0,255),2)

            cv2.imshow('video2', frames)
            if cv2.waitKey(33) == 27:
                break

            # loop to count the number of objects detected at every 5th frame
            if frames_got_processed % 5 == 0:
                print "appended in frame number", frames_got_processed, len(cars), cars
                csv_output.writerow([frames_got_processed, len(cars)] + list(cars))
        except:
            pass

# De-allocate any associated memory usage
cv2.destroyAllWindows()

这应该给您一行，其中包含车架号，汽车数量，以及每辆汽车的坐标。

如何在csv文件中获取此打印数据

1 个答案: