PRISMA is a computational photography pipeline that can perform a variety of inferences from any image or video. Similar to how light is refracted into different wavelengths through a prism, this pipeline expands images into data usable for 3D reconstruction or real-time post-processing operations. It integrates various algorithms and open-source pretrained models, such as monocular depth (MiDAS v3.1, ZoeDepth, Marigold, PatchFusion), optical flow (RAFT), segmentation masks (mmdet), and camera pose estimation (colmap), among others. The results are stored in a folder with the same name as the input file, with each band saved as a separate .png or .mp4 file. For videos, in the final step, it attempts to perform sparse reconstruction, which can be used for NeRFs (such as NVidia's Instant-ngp) or Gaussian diffusion training. The inferred depth information is exported by default as heatmap GLSL/HLSL samples that can be decoded in real-time using LYGIA, and the optical flow is encoded as HUE (angle) and saturation, which can also be decoded in real-time using LYGIA's optical flow GLSL/HLSL sampler.