Add confidence check on model
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ziesorx
parent
8c429cc8f6
commit
81547311d8
1 changed files with 58 additions and 24 deletions
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@ -561,6 +561,9 @@ def run_pipeline(frame, node: dict, return_bbox: bool=False, context=None):
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# ─── Detection stage - Multi-class support ──────────────────
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tk = node["triggerClassIndices"]
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logger.debug(f"Running detection for node {node['modelId']} with trigger classes: {node.get('triggerClasses', [])} (indices: {tk})")
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logger.debug(f"Node configuration: minConfidence={node['minConfidence']}, multiClass={node.get('multiClass', False)}")
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res = node["model"].track(
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frame,
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stream=False,
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@ -573,12 +576,17 @@ def run_pipeline(frame, node: dict, return_bbox: bool=False, context=None):
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all_boxes = []
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regions_dict = {}
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for box in res.boxes:
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logger.debug(f"Raw detection results from model: {len(res.boxes) if res.boxes is not None else 0} detections")
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for i, box in enumerate(res.boxes):
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conf = float(box.cpu().conf[0])
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cid = int(box.cpu().cls[0])
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name = node["model"].names[cid]
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logger.debug(f"Detection {i}: class='{name}' (id={cid}), confidence={conf:.3f}, threshold={node['minConfidence']}")
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if conf < node["minConfidence"]:
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logger.debug(f" -> REJECTED: confidence {conf:.3f} < threshold {node['minConfidence']}")
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continue
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xy = box.cpu().xyxy[0]
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@ -595,6 +603,8 @@ def run_pipeline(frame, node: dict, return_bbox: bool=False, context=None):
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all_detections.append(detection)
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all_boxes.append(bbox)
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logger.debug(f" -> ACCEPTED: {name} with confidence {conf:.3f}, bbox={bbox}")
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# Store highest confidence detection for each class
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if name not in regions_dict or conf > regions_dict[name]["confidence"]:
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regions_dict[name] = {
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@ -602,8 +612,13 @@ def run_pipeline(frame, node: dict, return_bbox: bool=False, context=None):
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"confidence": conf,
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"detection": detection
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}
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logger.debug(f" -> Updated regions_dict['{name}'] with confidence {conf:.3f}")
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logger.info(f"Detection summary: {len(all_detections)} accepted detections from {len(res.boxes) if res.boxes is not None else 0} total")
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logger.info(f"Detected classes: {list(regions_dict.keys())}")
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if not all_detections:
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logger.warning("No detections above confidence threshold - returning null")
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return (None, None) if return_bbox else None
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# ─── Multi-class validation ─────────────────────────────────
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@ -611,13 +626,25 @@ def run_pipeline(frame, node: dict, return_bbox: bool=False, context=None):
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expected_classes = node["expectedClasses"]
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detected_classes = list(regions_dict.keys())
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# Check if all expected classes are detected
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logger.info(f"Multi-class validation: expected={expected_classes}, detected={detected_classes}")
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# Check if at least one expected class is detected (flexible mode)
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matching_classes = [cls for cls in expected_classes if cls in detected_classes]
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missing_classes = [cls for cls in expected_classes if cls not in detected_classes]
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if missing_classes:
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logger.debug(f"Missing expected classes: {missing_classes}. Detected: {detected_classes}")
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logger.debug(f"Matching classes: {matching_classes}, Missing classes: {missing_classes}")
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if not matching_classes:
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# No expected classes found at all
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logger.warning(f"PIPELINE REJECTED: No expected classes detected. Expected: {expected_classes}, Detected: {detected_classes}")
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return (None, None) if return_bbox else None
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logger.info(f"Multi-class detection success: {detected_classes}")
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if missing_classes:
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logger.info(f"Partial multi-class detection: {matching_classes} found, {missing_classes} missing")
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else:
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logger.info(f"Complete multi-class detection success: {detected_classes}")
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else:
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logger.debug("No multi-class validation - proceeding with all detections")
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# ─── Execute actions with region information ────────────────
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detection_result = {
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@ -628,26 +655,33 @@ def run_pipeline(frame, node: dict, return_bbox: bool=False, context=None):
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# ─── Create initial database record when Car+Frontal detected ────
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if node.get("db_manager") and node.get("multiClass", False):
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# Generate UUID session_id since client session is None for now
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import uuid as uuid_lib
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from datetime import datetime
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generated_session_id = str(uuid_lib.uuid4())
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# Only create database record if we have both Car and Frontal
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has_car = "Car" in regions_dict
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has_frontal = "Frontal" in regions_dict
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# Insert initial detection record
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camera_id = detection_result.get("camera_id", "unknown")
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timestamp = datetime.now().strftime("%Y-%m-%dT%H-%M-%S")
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inserted_session_id = node["db_manager"].insert_initial_detection(
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camera_id=camera_id,
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captured_timestamp=timestamp,
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session_id=generated_session_id
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)
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if inserted_session_id:
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# Update detection_result with the generated session_id for actions and branches
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detection_result["session_id"] = inserted_session_id
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detection_result["timestamp"] = timestamp # Update with proper timestamp
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logger.info(f"Created initial database record with session_id: {inserted_session_id}")
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if has_car and has_frontal:
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# Generate UUID session_id since client session is None for now
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import uuid as uuid_lib
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from datetime import datetime
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generated_session_id = str(uuid_lib.uuid4())
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# Insert initial detection record
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camera_id = detection_result.get("camera_id", "unknown")
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timestamp = datetime.now().strftime("%Y-%m-%dT%H-%M-%S")
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inserted_session_id = node["db_manager"].insert_initial_detection(
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camera_id=camera_id,
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captured_timestamp=timestamp,
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session_id=generated_session_id
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)
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if inserted_session_id:
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# Update detection_result with the generated session_id for actions and branches
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detection_result["session_id"] = inserted_session_id
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detection_result["timestamp"] = timestamp # Update with proper timestamp
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logger.info(f"Created initial database record with session_id: {inserted_session_id}")
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else:
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logger.debug(f"Database record not created - missing required classes. Has Car: {has_car}, Has Frontal: {has_frontal}")
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execute_actions(node, frame, detection_result, regions_dict)
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