Reputation: 1
I want to save the entire frame every time when my model detects the object in the video
import cv2
import time
import numpy as np
# Create our body classifier
car_classifier = cv2.CascadeClassifier('haarcascade_car.xml')
# Initiate video capture for video file
cap = cv2.VideoCapture('K:/b.mp4')
# Loop once video is successfully loaded
while cap.isOpened():
# Read first frame
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Pass frame to our car classifier
cars = car_classifier.detectMultiScale(gray, 1.4, 2)
print(cars)
# Extract bounding boxes for any bodies identified
for (x,y,w,h) in cars:
cv2.rectangle(frame, (x, y), (x+w, y+h), (25, 0, 180), 2)
cv2.imshow('Cars', frame)
if cv2.waitKey(1) == 13: #13 is the Enter Key
break
cap.release()
cv2.destroyAllWindows()
Upvotes: 0
Views: 919
Reputation: 13
I would simply edit you forloop as such:
foundCarNumber = 0
while cap.isOpened():
# Read first frame
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Pass frame to our car classifier
cars = car_classifier.detectMultiScale(gray, 1.4, 2)
print(cars)
# Extract bounding boxes for any bodies identified
foundCar = false;
for (x,y,w,h) in cars:
cv2.rectangle(frame, (x, y), (x+w, y+h), (25, 0, 180), 2)
cv2.imshow('Cars', frame)
foundCar = true
if(foundCar):
foundCarNumber += 1
filePath = "/folder/folder/filename{}.jpg".format(foundCarNumber)
cv2.imwrite(filePath, frame)
This will generate a filepath + new name everytime you find a car.
The foundCarNumber increment makes sure you do not overwrite your previous image. And the image only gets saved everytime foundCar is true from the forloop.
Upvotes: 1