# raster_triangle **Repository Path**: windavatar/raster_triangle ## Basic Information - **Project Name**: raster_triangle - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2021-01-20 - **Last Updated**: 2021-01-20 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # Raster Triangle This is a simple renderer with z-buffer for synthesis data generating. With an input mesh and its pose, the rendered RGB and depth map are generated. It has been applied to [PVN3D](https://github.com/ethnhe/PVN3D). ## Installation Compile the source code by ```shell chmod +x ./rastertriangle_so.sh ./rastertriangle_so.sh ``` ## Datasets: - Download the LineMOD dataset from [here](https://drive.google.com/drive/folders/19ivHpaKm9dOrr12fzC8IDFczWRPFxho7). Unzip it and link the unzipped folder to this folder: ```shell ln -s path_to_Linemod_preprocessed ./Linemod_preprocessed ``` - Download SUN2012pascalformat dataset from [here](http://groups.csail.mit.edu/vision/SUN/releases/SUN2012pascalformat.tar.gz). Unzip it and link the unzipped folder to this folder: ```shell ln -s path_to_SUN2012pascalformat ./ ``` - Download the sample poses from [here](https://hkustconnect-my.sharepoint.com/:f:/g/personal/yhebk_connect_ust_hk/End-Ha7PuQFNktD_ZqBIuQgBwR0wNVDPi-Bneulo7Dy-JA?e=WQba57) and move the pickle files to folder ```sampled_poses/```. ## Generate synthesis data - Generate rendered data. Sampled poses for each object are provided in ``sampled_poses/``, which are generated by scripts [here](https://github.com/zju3dv/pvnet-rendering). Run the following command to generate rendered data: ```shell python3 rgbd_renderer.py --help python3 rgbd_renderer.py --cls ape --render_num 70000 ``` Example rendered images are as follows: ![render0](./example_images/rnd0.png) ![render1](./example_images/rnd1.png) - Run the following command to generate fusing data: ```shell python3 fuse.py --help python3 generate_fusing_data.py --cls ape --fuse_num 10000 ``` Example fused images are as follows: ![fuse0](./example_images/fuse0.png) ![fuse1](./example_images/fuse1.png)