{
  "figure": "fig9_gallery",
  "version": "v11",
  "size_inches": [
    5.5,
    3.2
  ],
  "source_script": "scripts/89_fig9_gallery_v7.py",
  "metric_name": {
    "macro": "\\name",
    "file": "paper/v5_macros.tex",
    "resolved": "JLD"
  },
  "sources": {
    "results/baselines_fr_tid2013_crop.csv": "02e2976594d82df3e6937b3ceb68fb29875bc3dea77f278f2240268187046e51",
    "results/explore/e06_tid2013_chroma_s2.csv": "6944c3b3dc2327658e1c3f72a03fb857c678b4ab74a3db48c0099649466ee0ec",
    "results/baselines_fr_kadid10k_test_crop.csv": "288e337b278486489ed3d011e5781d61e010d44c3f0f03a35e609dc68aa5b359",
    "results/explore/e06_kadid10k_test_chroma_s2.csv": "5d77ae4e3137c11c9f2d6c477a1c66fb944af1d338a3461a59d98933a4efa65e"
  },
  "caption": "JLD and learned baselines have complementary wins and failures. Each comparison shows its pristine reference thumbnail above two distorted photographs. Bold MOS identifies the higher-rated left image; blue metric marks agree with this ordering and orange slashed marks reverse it. JLD, DISTS and LPIPS-VGG each agree on two of four deliberately selected comparisons. JLD agrees on the upper noise-versus-pattern and quantisation-versus-block comparisons, and disagrees on the lower contrast-versus-impulse and patches-versus-block comparisons. Both baselines show the opposite pattern. These selected examples do not estimate accuracy. Fields use a shared warm colour scale and exclude the global output term, which remains included in the scalar decisions. MOS scales differ between datasets.",
  "selection_rule": "Columns are TID2013 and held-out KADID. First exclude each dataset reference used in fig4_qual. Top row: the next maximum human-score-gap comparison satisfying the fig4 rule (different distortion types, PSNR difference below 0.02 dB, the macro-named metric correct and both baselines wrong). Bottom row: exclude every already used reference and maximise the human-score gap among different distortion types with PSNR difference below 0.5 dB, the macro-named metric wrong and both baselines correct. A always has higher MOS. Resolve ties by lower PSNR gap then reference/A/B paths lexicographically.",
  "examples": [
    {
      "dataset": "tid2013",
      "reference": "data/tid2013/tid2013/reference_images/I04.BMP",
      "reference_sha256": "c8500941a30397bc9e613a297e1286bdb955f49926148f58e7963d6e82b03c9f",
      "variants": {
        "A": {
          "image": "data/tid2013/tid2013/distorted_images/i04_05_2.bmp",
          "image_sha256": "4d607748fc04f6f6a1a8dc1ee532b2ef804eb2310eddebfeef1c4b146414144c",
          "crop_xywh": [
            4,
            3,
            504,
            378
          ],
          "distortion_label": "Noise",
          "distortion_full_name": "high-frequency noise",
          "distortion_name_source": "jld/interpret.py:TID_TYPE_NAMES",
          "distortion_type": 5,
          "level": 2,
          "type_and_level_source": {
            "file": "results/baselines_fr_tid2013_crop.csv",
            "selector": {
              "dist": "data/tid2013/tid2013/distorted_images/i04_05_2.bmp"
            },
            "columns": [
              "dtype",
              "level"
            ]
          },
          "scores": {
            "human": 5.90244,
            "perjaclens": 0.0812484249472617,
            "dists": 0.1388886570930481,
            "lpips_vgg": 0.2267469316720962,
            "psnr": 30.00241470336914
          },
          "score_sources": {
            "human": {
              "file": "results/baselines_fr_tid2013_crop.csv",
              "selector": {
                "dist": "data/tid2013/tid2013/distorted_images/i04_05_2.bmp"
              },
              "column": "mos"
            },
            "dists": {
              "file": "results/baselines_fr_tid2013_crop.csv",
              "selector": {
                "dist": "data/tid2013/tid2013/distorted_images/i04_05_2.bmp"
              },
              "column": "dists"
            },
            "lpips_vgg": {
              "file": "results/baselines_fr_tid2013_crop.csv",
              "selector": {
                "dist": "data/tid2013/tid2013/distorted_images/i04_05_2.bmp"
              },
              "column": "lpips_vgg"
            },
            "psnr": {
              "file": "results/baselines_fr_tid2013_crop.csv",
              "selector": {
                "dist": "data/tid2013/tid2013/distorted_images/i04_05_2.bmp"
              },
              "column": "psnr"
            },
            "perjaclens": {
              "file": "results/explore/e06_tid2013_chroma_s2.csv",
              "selector": {
                "dist": "data/tid2013/tid2013/distorted_images/i04_05_2.bmp"
              },
              "formula": "D_ws_fe + 0.5 * R_cls_fe",
              "D_ws_fe": 0.0720876678824424,
              "R_cls_fe": 0.0183215141296386
            }
          },
          "displayed_human_score": "5.90",
          "map": {
            "file": "cache/v5_qual/i04_05_2_squared.npy",
            "sha256": "e54def7dd3b3cb146771caefc5d99feb9a6d1acb0bbc93e4c9849a21b65047fc",
            "operation": "Elementwise square root of local squared lens displacement",
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            "fit_sha256": "60241430133a2d89669bdc711cc9b5139b42c11011a6bca774d2b3b4160aa3a4",
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            "reconciliation_tolerance": {
              "absolute": 2e-05,
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            "reconciliation_note": "Original E06 is batched CUDA float32 (scripts/explore/e06_eval.py); maps use CPU float32, without numerical rescaling"
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        }
      },
      "reference_crop_xywh": [
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      "metric_verdicts": {
        "perjaclens": {
          "preferred": "B",
          "agrees_with_humans": false,
          "source": "Compare variants.A.scores.perjaclens with variants.B.scores.perjaclens; lower distance is better"
        },
        "dists": {
          "preferred": "A",
          "agrees_with_humans": true,
          "source": "Compare variants.A.scores.dists with variants.B.scores.dists; lower distance is better"
        },
        "lpips_vgg": {
          "preferred": "A",
          "agrees_with_humans": true,
          "source": "Compare variants.A.scores.lpips_vgg with variants.B.scores.lpips_vgg; lower distance is better"
        }
      },
      "human_preferred": "A",
      "human_preferred_source": "Compare recorded MOS values; higher is better in both datasets",
      "selection": {
        "outcome": "failure",
        "eligible_candidate_count": 1378,
        "candidate_count_source": "enumeration by select_case('kadid10k_test', 'failure') in scripts/75_fig4_qual_v5.py",
        "maximum_psnr_difference_db_exclusive": 0.5,
        "psnr_tolerance_source": "Illustration selection criterion, not a measured result",
        "excluded_references": [
          "data/kadid10k/kadid10k/images/I09.png",
          "data/kadid10k/kadid10k/images/I05.png"
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        "ordering": "Maximum positive MOS(A)-MOS(B); then minimum absolute PSNR difference; then reference, A and B paths lexicographically",
        "human_score_gap": 2.2299999999999995,
        "human_score_gap_source": "variants.A.scores.human minus variants.B.scores.human",
        "psnr_difference_db": 0.17415237426757812,
        "psnr_difference_source": "Absolute difference of variants.A.scores.psnr and variants.B.scores.psnr"
      },
      "exact_ordering_margins": {
        "human": {
          "operand_A": 4.1,
          "operand_B": 1.87,
          "delta_A_minus_B": 2.2299999999999995
        },
        "perjaclens": {
          "operand_A": 0.1650355160236358,
          "operand_B": 0.1548681110143661,
          "delta_B_minus_A": -0.010167405009269714,
          "meaning": "Positive agrees with higher-MOS A; negative favours lower-MOS B"
        },
        "dists": {
          "operand_A": 0.0341412425041198,
          "operand_B": 0.043710172176361,
          "delta_B_minus_A": 0.009568929672241204,
          "meaning": "Positive agrees with higher-MOS A; negative favours lower-MOS B"
        },
        "lpips_vgg": {
          "operand_A": 0.0497990697622299,
          "operand_B": 0.0526889376342296,
          "delta_B_minus_A": 0.002889867871999699,
          "meaning": "Positive agrees with higher-MOS A; negative favours lower-MOS B"
        }
      },
      "panel": 4
    }
  ],
  "map_colour_range": [
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  "map_colour_labels": [
    "0",
    "1.16"
  ],
  "map_colour_source": "Zero and maximum over all saved displacement arrays displayed in this figure; no per-image rescaling",
  "display": {
    "field": "Shared warm colour map with opacity proportional to displacement and dark warm contours over the distorted photographs",
    "colour_map": [
      "#fff9ed",
      "#f5d6ad",
      "#e8a25c",
      "#bf5b32",
      "#713326"
    ],
    "maximum_opacity": 0.58,
    "contour_fractions": [
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      0.5,
      0.75
    ],
    "drawing_parameter_source": "Presentation choices, not additional experimental measurements",
    "crop": "Identical native centre crop to multiples of 14 used by the metric; no further crop or image adjustment",
    "score_precision": "Human scores shown to two decimal places; full recorded values and all metric scores retained in examples",
    "marks": "Circle: macro-named metric; square: DISTS; triangle: LPIPS-VGG. Blue agrees with human ordering; orange with white slash reverses it.",
    "repeated_marks": "One ordered set of metric marks per A/B comparison: circle JLD, square DISTS, triangle LPIPS-VGG.",
    "map_scope": "Block-1 lens-64 displacement after chroma sigma 2 filtering; global output term excluded",
    "metric_scope": "Decisions use D_ws_fe + 0.5 R_cls_fe, including the global output term",
    "font": "Nimbus Sans, existing installed outlines converted to TrueType for valid PDF embedding",
    "winner": "Higher MOS bold within each pair; all three tied agreement counts bold"
  },
  "old_figure_review": "Retain the v8 four-pair gallery; align the photograph and MOS baselines, use one warm field scale, consolidate pairwise marks, and add honest tied counts.",
  "reference_review": {
    "files": [
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    "applied": "Viewed every supplied image before drawing; DINO image evidence motivates aligned photographs, Anthropic vocabulary motivates warm spatial fields, compact explicit verdicts replace duplicated marks."
  },
  "layout_audit": {
    "word_count": 22,
    "words": [
      "A",
      "TID",
      "B",
      "KADID",
      "Wins",
      "and",
      "failures",
      "Noise",
      "Pattern",
      "Quantisation",
      "Blocks",
      "Contrast",
      "Impulse",
      "Patches",
      "Blocks",
      "Choices",
      "JLD",
      "DISTS",
      "LPIPS-VGG",
      "agree",
      "disagree",
      "MOS"
    ],
    "minimum_font_pt": 6.0,
    "text_overlap": "none",
    "text_photo_overlap": "none",
    "text_outside_canvas": "none",
    "counting_rule": "Alphabetic words including model names; pure numerical values and mathematical symbols excluded"
  },
  "agreement_counts": {
    "perjaclens": {
      "agreements": 2,
      "comparisons": 4,
      "source": "Exact per-pair metric_verdicts, derived from original CSV distances and MOS; selected examples only"
    },
    "dists": {
      "agreements": 2,
      "comparisons": 4,
      "source": "Exact per-pair metric_verdicts, derived from original CSV distances and MOS; selected examples only"
    },
    "lpips_vgg": {
      "agreements": 2,
      "comparisons": 4,
      "source": "Exact per-pair metric_verdicts, derived from original CSV distances and MOS; selected examples only"
    },
    "jld_minus_best_baseline": {
      "ours": 2,
      "best_baseline": 2,
      "delta_count": 0,
      "source": "perjaclens.agreements minus max(dists.agreements, lpips_vgg.agreements)"
    }
  },
  "presentation_revision": "Removed agreement-rate and delta badges from a deliberately balanced example gallery; retained pair-level wins and failures.",
  "verdict": "Wins and failures",
  "iteration_review": {
    "iteration_1": "Retained the four original pairs; moved each comparison verdict to a single aligned strip and made all tied counts explicit. Review: agreement colours need a key and the generic plot audit misreads photograph frames.",
    "iteration_2": "Added matching blue-equals and orange-not-equal key, retained 6 pt minimum type, and adopted grey Rectangle frames without chart axes. Review: replace the duplicated legend marks with explicit agree/disagree words.",
    "iteration_3": "Made agree/disagree key explicit, moved the global MOS direction to the footer and tightened the zero-delta label. Final visual review: even margins, matching baselines, no crossings or label collisions.",
    "iteration_4": "Use valid embedded Nimbus Sans TrueType outlines and the same-family delta glyph; final compare reviewed after the font fix."
  },
  "table_crosscheck": {
    "directory": "paper/tables_v5",
    "result": "Aggregate tables contain no selected-gallery pair rows. Pair MOS, PSNR and distances are checked directly against the original CSV rows, with selectors in score_sources."
  },
  "visual_review": {
    "iteration": 1,
    "reference": "cache/refsheet/paper_2104.14294-01.png",
    "compare_sheet": "/tmp/jlens-v11-review/fig9_gallery_compare.png",
    "archived_compare_sheet": "/tmp/jlens-v11-review/fig9_gallery_compare_iter1.png"
  }
}