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fix(autoware_image_projection_based_fusion): roi cluster fusion has no existence probability update #8864

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Sep 24, 2024
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fix(autoware_image_projection_based_fusion): roi cluster fusion has no existence probability update #8864

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40 changes: 12 additions & 28 deletions perception/autoware_image_projection_based_fusion/src/roi_cluster_fusion/node.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -166,64 +166,48 @@
int index = -1;
bool associated = false;
double max_iou = 0.0;
bool is_roi_label_known =
const bool is_roi_label_known =
feature_obj.object.classification.front().label != ObjectClassification::UNKNOWN;
for (const auto & cluster_map : m_cluster_roi) {
double iou(0.0);
bool is_use_non_trust_object_iou_mode = is_far_enough(
input_cluster_msg.feature_objects.at(cluster_map.first), trust_object_distance_);
auto image_roi = feature_obj.feature.roi;
auto cluster_roi = cluster_map.second;
sanitizeROI(image_roi, camera_info.width, camera_info.height);
sanitizeROI(cluster_roi, camera_info.width, camera_info.height);
if (is_use_non_trust_object_iou_mode || is_roi_label_known) {
iou = cal_iou_by_mode(cluster_roi, image_roi, non_trust_object_iou_mode_);
} else {
iou = cal_iou_by_mode(cluster_roi, image_roi, trust_object_iou_mode_);
}

const bool passed_inside_cluster_gate =
only_allow_inside_cluster_ ? is_inside(image_roi, cluster_roi, roi_scale_factor_) : true;
if (max_iou < iou && passed_inside_cluster_gate) {
index = cluster_map.first;
max_iou = iou;
associated = true;
}
}

if (!associated) {
continue;
}

if (!output_cluster_msg.feature_objects.empty()) {
bool is_roi_existence_prob_higher =
output_cluster_msg.feature_objects.at(index).object.existence_probability <=
feature_obj.object.existence_probability;
if (iou_threshold_ < max_iou && is_roi_existence_prob_higher && is_roi_label_known) {
output_cluster_msg.feature_objects.at(index).object.classification =
feature_obj.object.classification;

// Update existence_probability for fused objects
if (
output_cluster_msg.feature_objects.at(index).object.existence_probability <
min_roi_existence_prob_) {
output_cluster_msg.feature_objects.at(index).object.existence_probability =
min_roi_existence_prob_;
}
}

// fuse with unknown roi

if (unknown_iou_threshold_ < max_iou && is_roi_existence_prob_higher && !is_roi_label_known) {
output_cluster_msg.feature_objects.at(index).object.classification =
feature_obj.object.classification;
auto & fused_object = output_cluster_msg.feature_objects.at(index).object;
const bool is_roi_existence_prob_higher =
fused_object.existence_probability <= feature_obj.object.existence_probability;

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Codecov / codecov/patch

perception/autoware_image_projection_based_fusion/src/roi_cluster_fusion/node.cpp#L200-L201 

Added lines #L200 - L201 were not covered by tests
const bool is_roi_iou_over_threshold =
(is_roi_label_known && iou_threshold_ < max_iou) ||
(!is_roi_label_known && unknown_iou_threshold_ < max_iou);

if (is_roi_iou_over_threshold && is_roi_existence_prob_higher) {

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CodeScene Delta Analysis / CodeScene Cloud Delta Analysis (main)

✅ Getting better: Complex Conditional 

RoiClusterFusionNode::fuseOnSingleImage decreases from 3 complex conditionals with 7 branches to 1 complex conditionals with 3 branches, threshold = 2. A complex conditional is an expression inside a branch (e.g. if, for, while) which consists of multiple, logical operators such as AND/OR. The more logical operators in an expression, the more severe the code smell.
fused_object.classification = feature_obj.object.classification;
// Update existence_probability for fused objects
if (
output_cluster_msg.feature_objects.at(index).object.existence_probability <
min_roi_existence_prob_) {
output_cluster_msg.feature_objects.at(index).object.existence_probability =
min_roi_existence_prob_;
}
fused_object.existence_probability =

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perception/autoware_image_projection_based_fusion/src/roi_cluster_fusion/node.cpp#L209 

Added line #L209 was not covered by tests
std::clamp(feature_obj.object.existence_probability, min_roi_existence_prob_, 1.0f);

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CodeScene Delta Analysis / CodeScene Cloud Delta Analysis (main)

✅ Getting better: Complex Method 

RoiClusterFusionNode::fuseOnSingleImage decreases in cyclomatic complexity from 43 to 40, threshold = 9. This function has many conditional statements (e.g. if, for, while), leading to lower code health. Avoid adding more conditionals and code to it without refactoring.

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CodeScene Delta Analysis / CodeScene Cloud Delta Analysis (main)

✅ Getting better: Bumpy Road Ahead 

RoiClusterFusionNode::fuseOnSingleImage decreases from 6 to 5 logical blocks with deeply nested code, threshold is one single block per function. The Bumpy Road code smell is a function that contains multiple chunks of nested conditional logic. The deeper the nesting and the more bumps, the lower the code health.
}
}
if (debugger_) debugger_->image_rois_.push_back(feature_obj.feature.roi);
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