Monocular depth estimation with tkDNN

Currently tkDNN supports only Monodepth2 as monocular depth esitmation network.

Run the demo

To run the depth estimation demo follow these steps (example with monodepth2):

rm monodepth2_fp32.rt        # be sure to delete(or move) old tensorRT files
./test_monodepth2            # run the yolo test (is slow)
./demoDepth monodepth2_fp32.rt ../demo/yolo_test.mp4 

In general the demo program takes the following parameters:

./demoDepth <network-rt-file> <path-to-video> <show-flag> <save-flag>

where

• <network-rt-file> is the rt file generated by a test
• <<path-to-video> is the path to a video file or a camera input
• <show-flag> if set to 0 the demo will not show the visualization, it will otherwise (default=1)
• <save-flag> if set to 1 the demo will save the video into result.mp4, it won't otherwise (default=1)

NB) By default it is used FP32 inference