<jupyter_start><jupyter_text>VPI remap<jupyter_code>!ls 1080p_stereo_calib/left/001.png
arr_in = np.asarray(Image.open('1080p_stereo_calib/left/001.png'))
vpi_img = vpi.asimage(arr_in)
t1 = time.perf_counter()

with vpi.Backend.CUDA:
    for _ in range(200):
        vpi_img_out = vpi_img.remap(warp_l)
        arr_out = vpi_img_out.cpu()
        
t2 = time.perf_counter()

print(f"{200/(t2 - t1)} FPS")
fig, axs = plt.subplots(1, 2, figsize=(20,10))

# before
axs[0].title.set_text('Original L')
axs[0].imshow(arr_in)

axs[1].title.set_text('Rectified L')
axs[1].imshow(arr_out)<jupyter_output><empty_output>
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