Update long-form proposal renderer for architecture diagram

scripts/render_longform_proposal.py

@@ -97,6 +97,90 @@ def make_heavy_vs_student() -> None:
     plt.close(fig)
 
 
+def make_final_student_architecture() -> None:
+    """Draw the exact deployed tensor path, including recurrent state and inactive heads."""
+    fig, ax = plt.subplots(figsize=(15.5, 8.6))
+    fig.patch.set_facecolor("white")
+    ax.set_xlim(0, 15.5)
+    ax.set_ylim(0, 8.6)
+    ax.axis("off")
+
+    def box(x, y, w, h, title, body, color=BLUE, dashed=False):
+        patch = plt.Rectangle(
+            (x, y), w, h, facecolor="white", edgecolor=color, linewidth=1.8,
+            linestyle="--" if dashed else "-", joinstyle="round"
+        )
+        ax.add_patch(patch)
+        ax.text(x + 0.12, y + h - 0.18, title, va="top", fontsize=10,
+                fontweight="bold", color=color)
+        ax.text(x + 0.12, y + h - 0.55, body, va="top", fontsize=8.1,
+                color=NAVY, linespacing=1.28)
+
+    def arrow(x1, y1, x2, y2, color=NAVY, style="-"):
+        ax.annotate("", xy=(x2, y2), xytext=(x1, y1),
+                    arrowprops=dict(arrowstyle="->", color=color, lw=1.4,
+                                    linestyle=style, shrinkA=2, shrinkB=2))
+
+    ax.text(0.35, 8.25, "Final OrbitSight CPU student — exact deployed architecture",
+            fontsize=17, fontweight="bold", color=NAVY)
+    ax.text(0.35, 7.88, "Solid boxes execute at inference; dashed boxes are stored/training-only.",
+            fontsize=9, color=GREY)
+
+    box(0.35, 5.25, 1.65, 1.35, "40 ms input", "3×640×640\npositive count\nnegative count\nrecency", CYAN)
+    box(2.35, 5.25, 1.65, 1.35, "Stem · 120 p", "3×3 Conv 3→4\nBatchNorm + SiLU\n4×640×640")
+    arrow(2.0, 5.93, 2.35, 5.93)
+
+    stages = [
+        (4.35, "Stage 1", "down 4→4 · s2\nConvLSTM d1\n4×320×320\n1,324 p"),
+        (6.35, "Stage 2", "down 4→8 · s2\nConvLSTM d2\n8×160×160\n4,952 p"),
+        (8.35, "Stage 3", "down 8→16 · s2\nConvLSTM d4\n16×80×80\n19,696 p"),
+        (10.35, "Stage 4", "down 16→32 · s2\nConvLSTM d8\n32×40×40\n78,560 p"),
+    ]
+    for x, title, body in stages:
+        box(x, 5.05, 1.65, 1.75, title, body)
+    for start in [4.0, 6.0, 8.0, 10.0]:
+        arrow(start, 5.93, start + 0.35, 5.93)
+
+    for x, label in [(5.0, "H,C\nstate"), (7.0, "H,C\nstate"),
+                     (9.0, "H,C\nstate"), (11.0, "H,C\nstate")]:
+        ax.annotate(label, xy=(x + 0.17, 6.75), xytext=(x + 0.17, 7.52),
+                    ha="center", va="center", fontsize=7.5, color=RED,
+                    arrowprops=dict(arrowstyle="<->", color=RED, lw=1.1))
+
+    heads = [
+        (6.25, 2.55, "Stride-4 head", "8→16→16\nreg 4×160²\nobj 1×160²\n3,573 active p"),
+        (8.25, 2.55, "Stride-8 head", "16→16→16\nreg 4×80²\nobj 1×80²\n4,725 active p"),
+        (10.25, 2.55, "Stride-16 head", "32→16→16\nreg 4×40²\nobj 1×40²\n7,029 active p"),
+    ]
+    for x, y, title, body in heads:
+        box(x, y, 1.75, 1.65, title, body, CYAN)
+    arrow(7.15, 5.05, 7.15, 4.2)
+    arrow(9.15, 5.05, 9.15, 4.2)
+    arrow(11.15, 5.05, 11.15, 4.2)
+
+    box(12.45, 2.55, 2.45, 1.65, "Exact top-one decoder",
+        "33,600 scores → stable argmax\nthreshold 0.10\ndecode only winning cell\nno production NMS", RED)
+    for x in [8.0, 10.0, 12.0]:
+        arrow(x, 3.37, 12.45, 3.37)
+
+    box(12.45, 5.05, 2.45, 1.75, "Native output path",
+        "inverse area mapping\nDVX size ×0.98\nKalman/coast tracker\nsensor gate → integer row", BLUE)
+    arrow(13.68, 4.2, 13.68, 5.05)
+
+    box(0.35, 0.55, 3.45, 1.25, "Selective training objective",
+        "human focal + pixel-inclusive CIoU + aux BCE\n+ matched-teacher confidence/box + empty-window negatives", GREY, dashed=True)
+    box(4.15, 0.55, 3.45, 1.25, "Auxiliary segmentation · 9 p",
+        "1×1 Conv on stride-4 feature → 1×160×160\nexecuted only while model.training", GREY, dashed=True)
+    box(7.95, 0.55, 3.45, 1.25, "Compatibility classification · 15,123 p",
+        "three stored cls towers/predictors\ncompute_cls=False; never scored", GREY, dashed=True)
+    box(11.75, 0.55, 3.15, 1.25, "Checkpoint contract",
+        "135,111 stored parameters\nquality head: off · sensor FiLM: off", GREY, dashed=True)
+
+    fig.subplots_adjust(left=0.015, right=0.985, top=0.98, bottom=0.03)
+    fig.savefig(ASSETS / "final_student_architecture.png", dpi=180, bbox_inches="tight")
+    plt.close(fig)
+
+
 def clean_inline(value: str) -> str:
     value = re.sub(r"!\[[^]]*]\([^)]+\)", "", value)
     value = re.sub(r"\[([^]]+)]\([^)]+\)", r"\1", value)
@@ -316,6 +400,7 @@ def main() -> None:
     ASSETS.mkdir(parents=True, exist_ok=True)
     make_model_evolution()
     make_heavy_vs_student()
+    make_final_student_architecture()
     render_markdown()
     print(f"Rendered {OUTPUT}")