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# To put logo on top-left corner, create a Region of Interest (ROI)įrm_bg = cv2.bitwise_and(roi,roi,mask = mask_inv) # Perform operations on the video frames here
![how to crop a video frame how to crop a video frame](https://www.videoproc.com/images/vp-seo/vlc-crop-preview.jpg)
Print('Error: Camera could not be opened') # Initialize Default Video Web Camera for capture. Click target format, and select YouTube Video > MP4. Lets take the cropping as an example: Launch VideoProc, and click the Video icon to start editing. If you want the cropped orange box at the bottom of the frame, add a Size and Position filter set to vertical fit - Bottom. Ret, mask = cv2.threshold(dog_gray, 10, 255, cv2.THRESH_BINARY)ĭog_fg = cv2.bitwise_and(dog,dog,mask = mask) To crop, cut, trim, rotate a video, or add effects, you just click the corresponding icon to call out each functioning window. When you use the Crop filter, it will auto-center the result, and the background (if you only have one track), which defaults as black, will show around the clip. # Create a mask of the logo and its inverse mask # Create a named window to display video outputĬv2.namedWindow('Watermark', cv2.WINDOW_NORMAL)ĭog_gray = cv2.cvtColor(dog,cv2.COLOR_BGR2GRAY) # Allows use of print like a function in Python 2.x See this python example code: # Python 2/3 compatibility If we have (x1,y1) as the top-left and (x2,y2) as the bottom-right vertex of a ROI, we can use Numpy slicing to crop the image with: ROI = image Here you save all the videoĬonsider (0,0) as the top-left corner of the image with left-to-right as the x-direction and top-to-bottom as the y-direction. Out = cv2.VideoWriter('result.avi', fourcc, fps, (w, h)) Choose an aspect ratio to crop your video or select freeform for a custom size. # Here you can define your croping values W_frame, h_frame = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))įps, frames = cap.get(cv2.CAP_PROP_FPS), cap.get(cv2.CAP_PROP_FRAME_COUNT) # Some characteristics from the original video Ok I think you want this, import numpy as np