inferencer_config{ # defining target class names for the experiment. # Note: This must be mentioned in order of the networks classes. target_classes: "car" # Inference dimensions. image_width: 960 image_height: 544 # Must match what the model was trained for. image_channels: 3 batch_size: 8 gpu_index: 0 # model handler config tlt_config{ model: "/workspace/tao-experiments/experiment/experiment_dir_retrain/weights/resnet18_detector_pruned.tlt" } } bbox_handler_config{ kitti_dump: true disable_overlay: false overlay_linewidth: 2 classwise_bbox_handler_config{ key:"car" value: { confidence_model: "aggregate_cov" output_map: "car" bbox_color{ R: 0 G: 255 B: 0 } clustering_config{ coverage_threshold: 0.005 dbscan_eps: 0.3 dbscan_min_samples: 0.05 dbscan_confidence_threshold: 0.9 minimum_bounding_box_height: 4 } } } }