I have two images (frame1 and frame2) and I am able to calculate u,v using opencv:
flow = cv2.calcOpticalFlowFarneback(prvs,next, 0.5, 1, 3, 15, 3, 5, 1, 0)
I want to translate frame1 using this u,v to quantify the quality of the difference using various optical flow methods. I intend to extrapolate using these u,v.
Is there a simple way to achieve this?
One way to compute a simple translation is to average the flow:
avg_u = np.mean(flow[:, :, 0])
avg_v = np.mean(flow[:, :, 1])
This gives the vector (avg_u, avg_v) needed to translate.
Regarding your comments, it seems you want to move every pixel (x,y) to the location specified by its flow vector (u(x,y), v(x,y)).
First, generate a Cartesian grid:
height, width = flow.shape[0, 1]
R2 = np.dstack(np.meshgrid(np.arange(width), np.arange(height)))
Then, the desired mapping is simply the addition of this grid with the flow:
pixel_map = R2 + flow
Finally, perform a cv2.remap:
new_frame = cv2.remap(prev_frame, pixel_map)
