I read a Video with Opencv Video Capture class, then i convert to Frames.
Now, i Need to increase The Fps or The Frames in my Video(like to create slow motion Video) , I read about Frame Blending To increase Frames in Slow motoin Videos ,So i think i need this way for my problem .
so how actually Frame Blending works or any algorithms to impelement It on Opencv and are there other taqnics to increase frames ?
Related
I know this is the way to increase the brightness of an image. However, adding this piece of code to a video creates an unstable and flickering video. Is there any alternative to increase the brightness of a video where the brightness would be stable throughout the video after getting increased?
I am using OpenCV to capture videos with a number of different cameras (OpenCV 4.5.1.48 on Ubuntu 18.04). For all the cameras I set the capturing frame rate to 30fps, but I noticed when reading the fps of the recorded video through
import cv2
cap = cv2.VideoCapture(input_video_path)
fps = cap.get(cv2.CAP_PROP_FPS)
print(fps)
that the values are never exactly 30 fps, but rather
30.00030000300003
30.000299988570422
29.997772583098968
...
and so on. Is this behaviour expected? When I right click on the videos and look at the video properties, it always says 30 fps.
The videos I am recording are around 10 minutes, but if I cut a smaller section of the video (e.g. 30 seconds) than the departure from 30 fps is even greater and OpenCV would read even 29 fps instead of 30.
Would there be any real downsize from rounding the detected frame rate to an integer when processing the video? In the specific I am looking to record an output video at 10 fps taking one every three frames of the original video, so I'm wondering if setting the frame rate of the video writer to 10 fps is correct or if I should be using one third of the fps read by OpenCV.
I'm working on a code, which reads incoming videos from Raspberry Pi, performs face detection on the frames, places frames around the faces, and then write backs the frames into an MP4 file with the same FPS. I use OpenCV to open and read from the PiCam.
When I looked into the saved video, it looks like it's moving too fast. I let my code to run for around 2 minutes, but my video has a length of 30 second. When I disable all post-processings (face detection), I can observe stable speed on the output video.
I can understand that Raspberry Pi has a small processor for heavy computations, but cannot understand why the video length is shorter? Is it possible that my face detection pipeline running much slower than the camera FPS, so the camera buffer should drop frames that are not going to be grabbed by the pipeline in a timely-fashion?
Any help here is highly appreciated!
I am trying to use OpenCV to load a video file or access video stream from webcam but I'm unable to access all frames.
The video file is captured with the FPS of 60 but in my code I am only able to access a few frames per second. I tried using the threaded version of OpenCV, imutils. It works better but I still cannot access full frames.
In my code below, I use the threaded version video reader to load video file and resize it to smaller size to reduce the processing power required.
After the frame is grabbed successfully, I will so some image processing work (in the future). But now even with this boilerplate, I can at most read only a few (10+) frames and the results are stuttering. Is there a way to resolve this?
import cv2
from imutils import resize
from imutils.video import VideoStream
vs = VideoStream(src="./video.MOV").start()
while True:
frame = vs.read()
if frame is not None:
frame = resize(frame, 800)
# some heavy analytics work
cv2.imshow("Frame", frame)
if cv2.waitKey(1) & 0xFF == ord("q"):
break
cv2.destroyAllWindows()
vs.stop()
Experiment
I ran an experiment to calculate number of frames loaded and average time taken for each imshow function on both my iMac and an Ubuntu machine rocking Intel Core i5-7400 # 3.00Ghz with a 1080p monitor.
The video (h264) has a duration of 1:03 min and of size 185.7MB.
iMac can only load a total of 414 frames while the Ubuntu machine can load a total of 2826 frames.
Average time take for imshow function for both machine is 0.0003s
Basically, you just load the video and display, so there isn't any reason that you get low fps like that except that you are using a Macbook with Retina screen. Maybe it's the reason causes slow video display because the Retina screen has a lot more pixels, and it might take time for the compositing engine to render your image on the screen. I suggest to use an external screen.
I have raw-rgb video coming from PAL 50i camera. How can I detect the start of frame, just like I would detect the keyframe of h264 video, in gstreamer? I would like to do that for indexing/cutting purposes.
If this really is raw rgb video, there is no (realistic) way to detect the start of the frame. I would assume your video would come as whole frames, so one buffer == one frame, and hence no need for such detection.