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OpenCV real time streaming video capture is slow. How to drop frames or get synced with real time?

Goal and problem
I'd like to set up an opencv system to process either HLS streams or RMTP streams, however, I am running into a strange issue regarding a reduced frame-rate and an accumulating lag. It's as if the video gets further and further behind from where it is supposed to be in the stream.
I'm looking for a way to keep up to date with a live source even if it means dropping frames.
Current approach
import cv2
cap = cv2.VideoCapture()
cap.open('https://videos3.earthcam.com/fecnetwork/9974.flv/chunklist_w1421640637.m3u8')
while (True):
_, frame = cap.read()
cv2.imshow("camCapture", frame)
cv2.waitKey(1)
I've validated the quality of the stream on VLC and it seems to work fine there.
cv2 speed
.
realistic/expected speed
Questions:
What am I doing wrong here?
Why is it so slow?
How do I sync it to real-time speeds?

My hypothesis is that the jitter is most likely due to network limitations and occurs when a frame packet is dropped. When a frame is dropped, this causes the program to display the last "good" frame which results in the display freezing. This is probably a hardware or bandwidth issue but we can alleviate some of this with software. Here are some possible changes:
1. Set maximum buffer size
We set the cv2.videoCapture() object to have a limited buffer size with the cv2.CAP_PROP_BUFFERSIZE parameter. The idea is that by limiting the buffer, we will always have the latest frame. This can also help to alleviate the problem of frames randomly jumping ahead.
2. Set frame retrieval delay
Currently, I believe the read() is reading too fast even though it is in its own dedicated thread. This may be one reason why all the frames appear to pool up and suddenly burst in the next frame. For instance, say in a one second time interval, it may produce 15 new frames but in the next one second interval, only 3 frames are returned. This may be due to the network packet frame loss so to ensure that we obtain constant frame rates, we simply add a delay in the frame retrieval thread. A delay to obtain roughly ~30 FPS does a good job to "normalize" the frame rate and smooth the transition between frames incase there is packet loss.
Note: We should try to match the frame rate of the stream but I'm not sure what the FPS of the webcam is so I just guessed 30 FPS. Also, there is usually a "direct" stream link instead of going through a intermediate webserver which can greatly improve performance.
If you try using a saved .mp4 video file, you will notice that there is no jitter. This confirms my suspicion that the problem is most likely due to network latency.
from threading import Thread
import cv2, time
class ThreadedCamera(object):
def __init__(self, src=0):
self.capture = cv2.VideoCapture(src)
self.capture.set(cv2.CAP_PROP_BUFFERSIZE, 2)
# FPS = 1/X
# X = desired FPS
self.FPS = 1/30
self.FPS_MS = int(self.FPS * 1000)
# Start frame retrieval thread
self.thread = Thread(target=self.update, args=())
self.thread.daemon = True
self.thread.start()
def update(self):
while True:
if self.capture.isOpened():
(self.status, self.frame) = self.capture.read()
time.sleep(self.FPS)
def show_frame(self):
cv2.imshow('frame', self.frame)
cv2.waitKey(self.FPS_MS)
if __name__ == '__main__':
src = 'https://videos3.earthcam.com/fecnetwork/9974.flv/chunklist_w1421640637.m3u8'
threaded_camera = ThreadedCamera(src)
while True:
try:
threaded_camera.show_frame()
except AttributeError:
pass
Related camera/IP/RTSP/streaming, FPS, video, threading, and multiprocessing posts
Python OpenCV streaming from camera - multithreading, timestamps
Video Streaming from IP Camera in Python Using OpenCV cv2.VideoCapture
How to capture multiple camera streams with OpenCV?
OpenCV real time streaming video capture is slow. How to drop frames or get synced with real time?
Storing RTSP stream as video file with OpenCV VideoWriter
OpenCV video saving
Python OpenCV multiprocessing cv2.VideoCapture mp4

Attempt at threading
I've attempted this solution from nathancy with minor success.
It involves:
creating a separate thread for image capture from the source
using the main thread exclusively for display.
Code:
import cv2
from threading import Thread
class ThreadedCamera(object):
def __init__(self, source = 0):
self.capture = cv2.VideoCapture(source)
self.thread = Thread(target = self.update, args = ())
self.thread.daemon = True
self.thread.start()
self.status = False
self.frame = None
def update(self):
while True:
if self.capture.isOpened():
(self.status, self.frame) = self.capture.read()
def grab_frame(self):
if self.status:
return self.frame
return None
if __name__ == '__main__':
stream_link = "https://videos3.earthcam.com/fecnetwork/9974.flv/chunklist_w1421640637.m3u8"
streamer = ThreadedCamera(stream_link)
while True:
frame = streamer.grab_frame()
if frame is not None:
cv2.imshow("Context", frame)
cv2.waitKey(1)
Jittery, but real-time results
.
The streaming works. It maintains real-time. However, it is as if all the frames pool up and suddenly burst into the video. I would like somebody to explain that.
Room for improvement
The real-time stream can be found here.
https://www.earthcam.com/usa/newyork/timessquare/?cam=tsstreet
This site is scraped for the m3u8 using python's streamlink stream scraper.
import streamlink
streams = streamlink.streams("https://www.earthcam.com/usa/newyork/timessquare/?cam=tsstreet")
print(streams)
which yeilds:
OrderedDict([
('720p',<HLSStream('https://videos3.earthcam.com/fecnetwork/9974.flv/chunklist_w202109066.m3u8')>),
('live', <RTMPStream({'rtmp': 'rtmp://videos3.earthcam.com/fecnetwork/', 'playpath': '9974.flv', 'pageUrl': 'https://www.earthcam.com/usa/newyork/timessquare/?cam=tsstreet','swfUrl': 'http://static.earthcam.com/swf/streaming/stream_viewer_v3.swf', 'live': 'true'}, redirect=False>),
('worst', <HLSStream('https://videos3.earthcam.com/fecnetwork/9974.flv/chunklist_w202109066.m3u8')>),
('best', <RTMPStream({'rtmp': 'rtmp://videos3.earthcam.com/fecnetwork/', 'playpath': '9974.flv', 'pageUrl': 'https://www.earthcam.com/usa/newyork/timessquare/?cam=tsstreet', 'swfUrl': 'http://static.earthcam.com/swf/streaming/stream_viewer_v3.swf', 'live': 'true'}, redirect=False>)
])
The possibility that the streams are being read wrong.

I would suggest double checking the compatible video stream codecs with the hardware. I ran into the same issue, frame rate dropped to 5 fps only during streaming, because it was defaulting to a format that is not being streamed so it would convert it then display very lagged (~1s) with lower fps as well.
use Self.capture.set(cv2.CAP_PROP_FOURCC ,cv2.VideoWriter_fourcc('M', 'J', 'P', 'G') ) with the proper codec in place of MJPG and with your cv2.VideoCapture and see if that helps.

How to take the latest frame from an ip camera with Opencv? [duplicate]

This question already has answers here:
How to get the latest frame from capture device (camera) in opencv
(5 answers)
Closed 2 years ago.
I need to take snapshots of an ip camera connected to my raspberry pi 3 b+. I´m using python3 and opencv. There is a timer in the camera so I can check if the snapshot is taken in the right moment.
This script works well in my PC with Windows but does not in the raspberry. The script takes a snapshot every second, but the frame taken is not the correct, its old.
In the raspberry pi, I ran the video with VLC and omxplayer and its ran fluidly, so I think that the problem is in Opencv and my code. I have the impression that the frames are stored in a buffer, the raspberry is too slow to take all the frames from the buffer in real time, so as the time pass there is more delay between the last real frame and the frame taken.
import threading
import time
import cv2
cap = cv2.VideoCapture(‘rtsp://192.168.0.88’)
cap.set(cv2.CAP_PROP_BUFFERSIZE, 3)
counter = 0
while True:
ret, frame = cap.read()
if ret:
cv2.imwrite(str(counter) + '.jpg', frame)
counter = counter + 1
time.sleep(1)
Anyone have an idea of how can I take only the latest frame from the camera?
I want to remark that the resolution is 1920x1080 and the video format is h264. Furthermore, in the real application I need that the time between frames to be 0.1 seconds.

Here's a widget which saves a screenshot of the latest frame every x seconds. This idea is to create another thread just for obtaining the frames as cv2.VideoCapture.read() is a blocking operation. By putting this operation into a separate dedicated thread that focuses only on grabbing frames, we can ensure that we have the latest frame without any buffer. This will improve performance by I/O latency reduction as the main thread does not have to wait until there is a new frame. I used my own RTSP stream link and saved a screenshot every 1 second. Change it to your RTSP link and however long you want to save a screenshot
from threading import Thread
import cv2
import time
class VideoScreenshot(object):
def __init__(self, src=0):
# Create a VideoCapture object
self.capture = cv2.VideoCapture(src)
# Take screenshot every x seconds
self.screenshot_interval = 1
# Default resolutions of the frame are obtained (system dependent)
self.frame_width = int(self.capture.get(3))
self.frame_height = int(self.capture.get(4))
# Start the thread to read frames from the video stream
self.thread = Thread(target=self.update, args=())
self.thread.daemon = True
self.thread.start()
def update(self):
# Read the next frame from the stream in a different thread
while True:
if self.capture.isOpened():
(self.status, self.frame) = self.capture.read()
def show_frame(self):
# Display frames in main program
if self.status:
cv2.imshow('frame', self.frame)
# Press Q on keyboard to stop recording
key = cv2.waitKey(1)
if key == ord('q'):
self.capture.release()
cv2.destroyAllWindows()
exit(1)
def save_frame(self):
# Save obtained frame periodically
self.frame_count = 0
def save_frame_thread():
while True:
try:
cv2.imwrite('frame_{}.png'.format(self.frame_count), self.frame)
self.frame_count += 1
time.sleep(self.screenshot_interval)
except AttributeError:
pass
Thread(target=save_frame_thread, args=()).start()
if __name__ == '__main__':
rtsp_stream_link = 'your stream link!'
video_stream_widget = VideoScreenshot(rtsp_stream_link)
video_stream_widget.save_frame()
while True:
try:
video_stream_widget.show_frame()
except AttributeError:
pass

Combining OpenCV, Python, Tkinter and PiCamera

I'm having problems with using OpenCV, Python, Tkinter and PiCamera in a program.
A Tkinter window is used to display and set the values to be used in OpenCV:
I am trying to continuously read and process the video feed from PiCamera currently I am using:
while True:
for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
root.update_idletasks()
But after some reading on internet I found that using update() is not advisable, so I tried my luck to understand threading but I failed. There are a lot of examples with VideoCapture() which is used with USB cameras but not a lot with PiCamera. Is there any other way than threading?

You can use root.after(...). Below is a sample code:
# define a variable used to stop the image capture
do_image_capture = True
def capture_image():
if do_image_capture:
camera.capture(rawCapture, format='bgr', use_video_port=True)
# do whatever you want on the captured data
...
root.after(100, capture_image) # adjust the first argument to suit your case
capture_image()
Below sample code is using thread:
import threading
stop_image_capture = False
def capture_image():
for frame in camera.capture_continuous(rawCapture, format='bgr', use_video_port=True)
# do whatever you want on the capture image
....
if stop_image_capture:
break
t = threading.Thread(target=capture_image)
t.setDaemon(True)
t.start()

Capture Raspicam image via PiCamera module - How to avoid old images?

I am working on a project where we are using the Raspicam attached to a Raspberry Pi to capture (and process) images with python using the PiCamera module.
With our current implementation I am experiencing an unexpected behaviour.
The camera is configured to capture images with 15 frames per second. To simulate processing time the program waits 5 seconds.
Minimal example:
#!/usr/bin/env python
import cv2
from picamera import PiCamera
from picamera.array import PiRGBArray
class RaspiCamera:
def __init__(self, width, height, framerate):
self.camera = PiCamera()
self.camera.resolution = (width, height)
self.camera.framerate = framerate
self.rawCapture = PiRGBArray(self.camera, size=self.camera.resolution)
self.capture_continuous = self.camera.capture_continuous(self.rawCapture, format="bgr", use_video_port=True)
def capture(self):
frame = self.capture_continuous.next()
image = self.rawCapture.array
self.rawCapture.truncate(0)
return image
if __name__ == "__main__":
camera = RaspiCamera(640, 480, 15)
while True:
frame = camera.capture()
cv2.imshow("Image", frame)
if cv2.waitKey(5000) & 0xFF == ord('q'):
break
When capture() is called for the first time, self.capture_continuous.next() returns an up to date image. When calling capture() consecutively, it often happens that self.capture_continuous.next() does not return the latest image but one that is already a few seconds old (verified by pointing the camera at a clock). From time to time, it's even older than 10 seconds. On the other hand, sometimes self.capture_continuous.next() actually returns the latest image.
Since capture_continuous is an object of the type generator, my assumption is that it keeps generating camera images in the background that accumulate in a queue while the program waits and on the next call of self.capture_continuous.next() the next element in the queue is returned.
Anyway, I am only interested in the latest, most up to date image the camera has captured.
Some first attempts to get hold of the latest images failed. I tried to call self.capture_continuous.next() repeatedly in a while loop to get to the latest image.
Since a generator is apparently also an iterator I tried some methods mentioned in this post: Cleanest way to get last item from Python iterator.
Simply using the capture() function of the PiCamera class itself is not an option since it takes approx. 0.3 seconds till the image is captured what is too much for our use case.
Does anyone have a clue what might cause the delay described above and how it could be avoided?

OpenCV VideoCapture only updates after 5 read()s

I have a very strange error that has been plaguing my research for a few years now. I'm using OpenCV2 with Python to read image data from a webcam. However, the image is lagged by 5 frames. In other words, each call to read() is 5 frame behind real-time.
One bandage fix I have been using is to grab() 4 frames and then read the 5th every time I need an updated image, but that absolutely murders my performance.
Here's the code that I am using to display the images from the webcam
frame = self.getGoodFrame()
if self.DEBUG:
window = cv2.namedWindow("Angles")
imgHSV = cv2.cvtColor(frame, cv2.cv.CV_BGR2HSV)
... Reseach specific code I shouldn't be giving out here ...
... It finds the center of a few bright colors in an image
if self.DEBUG:
debugImage = numpy.zeros((self.CAMERA_HEIGHT, self.CAMERA_WIDTH), numpy.uint8) #blank image
... Then we draw some stuff to the image to be displayed ...
cv2.imshow("Angles", debugImage)
cv2.waitKey(1)
raw_input()
and getGoodFrame()
def getGoodFrame(self):
MIN_READS_FOR_GOOD_FRAME = 4
for i in xrange(MIN_READS_FOR_GOOD_FRAME):
successful_read = self.capture.grab()
successful_read, frame = self.capture.read()
if not successful_read:
print "Unable to read from webcam, exiting."
return frame
You'll notice that I have a raw_input() call. That makes it so I can see how many reads need to happen by pressing enter a few times in console. This shows that there is exactly 5 frames of lag.
I don't think it's a hardware issue, I've had this happen with multiple webcams and multiple USB cords. I haven't tried reproducing the error on another machine though.

So the problem was something to do with the way that my hardware was buffering the frames. I never quite got to the bottom of it but the solution I found was very simple paralellization. I modified my code to open up a thread and constantly update a variable holding the current frame. Then, when I need the current frame I just ask for whatever that variable is at the moment.
Note that this is still 5 read() calls behind because of the ever-present buffering, however because I am doing read() calls continuously and it's all on its own thread, it is very up to date. This is because I can call many read() calls per second. The image I get is not noticeably behind real-time at all.
The Python class I made to do this is below. It is not very nice code but it works. To do this properly, I would (and will) add graceful ways to exit the infinite loop. It will work for me though and it has improved the speed of my image detection code by well over 100 fold, which is extremely awesome and exciting for me :)
class webcamImageGetter:
def __init__(self):
self.currentFrame = None
self.CAMERA_WIDTH = #webcam width
self.CAMERA_HEIGHT = #webcam height
self.CAMERA_NUM = 0
self.capture = cv2.VideoCapture(0) #Put in correct capture number here
#OpenCV by default gets a half resolution image so we manually set the correct resolution
self.capture.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH,self.CAMERA_WIDTH)
self.capture.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT,self.CAMERA_HEIGHT)
#Starts updating the images in a thread
def start(self):
Thread(target=self.updateFrame, args=()).start()
#Continually updates the frame
def updateFrame(self):
while(True):
ret, self.currentFrame = self.capture.read()
while (self.currentFrame == None): #Continually grab frames until we get a good one
ret, frame = self.capture.read()
def getFrame(self):
return self.currentFrame
To use this, you initialize it then called start on the instance. This will make it so when you later called getFrame(), it will have the most up to date frame from the webcam. Woohoo!

Default buffer is set to 4.0 instead of 1.0.
To Fix it:
cap.set(38,1)
reference: https://docs.opencv.org/4.x/d4/d15/group__videoio__flags__base.html#ga41c5cfa7859ae542b71b1d33bbd4d2b4