Python implementation of large field-of-view integral imaging pickup system.
“Computational large field-of-view RGB-D integral imaging system”, Sensors, November 2021
Download paper : Computational large field-of-view RGB-D integral imaging system
In this system, use the code Computational integral imaging pickup system
- Trained by NYU RGB-D V2 (650 MB)
- Download depth estimation model file.
- Go to the link above, and download model.
- Locate file at
monodepth
or/your/own/path/
.
- Prepare the input image.
- Locate the input color image to
inputs
directory or/your/own/path/
.
- Locate the input color image to
- Start large FOV integral imaging pickup system.
python main.py \ --color_path ./inputs/image_file_name or /your/own/path/ \ --output_path ./results or /your/own/path/ \ --model_path ./monodepth/model.h5 or /your/own/path/ \ --is_gpu
- Sub-aperture Image Array
- Update codes (Depth sub-aperture images).