what are these

pipeline/stages/api.py

@@ -148,6 +148,7 @@ class APIPersonDetector(APIStageBase):
         resp.raise_for_status()
         return resp.json()
 
+
 # haiku 4.5 is multimodal but i fear its going to ping 65 million images per second (we need cache control? who are we? why cant we upload video?)
 class VLMVerifier(APIStageBase):
     """

pipeline/stages/local.py

@@ -5,7 +5,12 @@ import time
 from typing import List, Optional
 
 from pipeline.config import DEFAULT_CONFIG, PipelineConfig
-from pipeline.ops import nms_by_class
+from pipeline.ops import (
+    merge_overlapping,
+    nms_by_class,
+    select_for_verification,
+    select_top_k,
+)
 from pipeline.protocols import Model, Verifier
 from pipeline.stages.protocol import StageContext, StageResult
 from pipeline.types import BoundingBox, Detection, Ticket
@@ -66,10 +71,39 @@ class LocalCigaretteDetector:
         cfg = self.cfg
         h_img, w_img = ctx.frame_data.shape[:2]
 
+        # === Budget: Limit how many people we process ===
+        people_to_process = ctx.people
+
+        if cfg.merge_people:
+            # Merge overlapping people into regions
+            people_to_process = merge_overlapping(
+                people_to_process, cfg.merge_people_iou
+            )
+            if len(people_to_process) < len(ctx.people):
+                logger.debug(
+                    "Merged %d people into %d regions",
+                    len(ctx.people),
+                    len(people_to_process),
+                )
+
+        if cfg.max_person_crops > 0 and len(people_to_process) > cfg.max_person_crops:
+            # Select top K diverse people by priority
+            people_to_process = select_top_k(
+                people_to_process,
+                k=cfg.max_person_crops,
+                priority=cfg.person_priority,
+            )
+            logger.debug(
+                "Budget: Processing %d/%d people (priority=%s)",
+                len(people_to_process),
+                len(ctx.people),
+                cfg.person_priority,
+            )
+
         all_cigs: List[Detection] = []
         early_hit = None
 
-        for person in ctx.people:
+        for person in people_to_process:
             # Expand person box for crop
             crop_box = self._expand_box(person.box, cfg.person_margin, w_img, h_img)
             ex1, ey1, ex2, ey2 = crop_box
@@ -195,12 +229,28 @@ class LocalVerifier:
         cfg = self.cfg
         h_img, w_img = ctx.frame_data.shape[:2]
 
+        # === Budget: Limit how many cigs we verify ===
+        cigs_to_verify = ctx.cigarettes
+
+        if (
+            cfg.max_cig_verifications > 0
+            and len(cigs_to_verify) > cfg.max_cig_verifications
+        ):
+            # Select top K by confidence (most likely real → verify first)
+            cigs_to_verify = select_for_verification(
+                cigs_to_verify,
+                k=cfg.max_cig_verifications,
+                min_confidence=cfg.cig_min_confidence,
+            )
+            logger.debug(
+                "Budget: Verifying %d/%d cigarettes",
+                len(cigs_to_verify),
+                len(ctx.cigarettes),
+            )
+
         confirmed: list[tuple[Detection, float]] = []
 
-        for cig_det in ctx.cigarettes:
-            offset = cig_det.metadata.get("crop_offset", (0, 0))
-            ex1, ey1 = offset
-
+        for cig_det in cigs_to_verify:
             # Extract padded crop for classifier
             crop = self._extract_cig_crop(ctx.frame_data, cig_det, w_img, h_img)
             if crop.size == 0:

pipeline/stages/runner.py

@@ -60,7 +60,7 @@ class StagePipeline:
                     stage.name,
                     ctx.stop_reason,
                 )
-                continue # break?
+                continue  # break?
 
             try:
                 result = stage.process(ctx)