{
  "benchmark": "L3-004 (CACTI) \u2014 InverseNet SCI Video Benchmark",
  "citation": "Yuan et al. CACTI; Yang et al. SCI Video Benchmark",
  "data_range": "[0, 1] for both ground_truth and solution (normalized from raw .mat)",
  "generated_by": "scripts/regenerate_demos_inversenet.py",
  "how_to_run": "python3 scripts/regenerate_demos_inversenet.py --only cacti (uses pwm_core.recon.cacti_solvers.gap_tv_cacti)",
  "psnr_convention": "InverseNet paper compute_psnr: clip both to [0,1], peak=1",
  "reference_solver_psnr_db": 25.06,
  "scene_id": "aerial",
  "sha256": {
    "ground_truth.npz": "c8384415eda2352cf56d782d5c69d1e9604d0ff63b8200c7904f307ff78ab67c",
    "snapshot.npz": "91b54e64c9885689022edbb39a6c6377cb463048ac0b7ca0dc264f69ae2f9e5a",
    "solution.npz": "cfe4713cfcf3bde785a735079bf6d3baa742239d90b06f49cfe907035cb626c9"
  },
  "shape_ground_truth": [
    8,
    256,
    256
  ],
  "shape_snapshot": [
    256,
    256
  ],
  "shape_solution": [
    8,
    256,
    256
  ],
  "solver": "pwm_core.recon.cacti_solvers.gap_tv_cacti",
  "solver_elapsed_sec": 3.4,
  "solver_iterations": 100,
  "source_dataset": "SCI Video Benchmark (Kobe/Traffic/Runner/Drop/Crash/Aerial); Liu et al. 2019 + Yuan et al. Bell Labs",
  "source_mat": "aerial32_cacti.mat",
  "tier_approx": "T1_nominal",
  "tv_weight": 0.1
}