FaceDetect IR Training using TLT 3.0 and Custom Dataset

Facenet is based on detectNet_v2 network. So, please refer to section 10.A of tlt_cv_samples_v1.0.2/detectnet_v2/detectnet_v2.ipynb

DetectNet_v2 model supports int8 inference mode in TensorRT. In order to use int8 mode, we must calibrate the model to run 8-bit inferences -

  • Generate calibration tensorfile from the training data using detectnet_v2 calibration_tensorfile
  • Use tlt-export to generate int8 calibration table.

!tlt detectnet_v2 calibration_tensorfile -e $SPECS_DIR/detectnet_v2_retrain_resnet18_kitti.txt
-m 10
-o $USER_EXPERIMENT_DIR/experiment_dir_final/calibration.tensor

!rm -rf $LOCAL_EXPERIMENT_DIR/experiment_dir_final/resnet18_detector.etlt
!rm -rf $LOCAL_EXPERIMENT_DIR/experiment_dir_final/calibration.bin
!tlt detectnet_v2 export
-m $USER_EXPERIMENT_DIR/experiment_dir_retrain/weights/resnet18_detector_pruned.tlt
-o $USER_EXPERIMENT_DIR/experiment_dir_final/resnet18_detector.etlt
-k $KEY
–cal_data_file $USER_EXPERIMENT_DIR/experiment_dir_final/calibration.tensor
–data_type int8
–batches 10
–batch_size 4
–max_batch_size 4
–engine_file $USER_EXPERIMENT_DIR/experiment_dir_final/resnet18_detector.trt.int8
–cal_cache_file $USER_EXPERIMENT_DIR/experiment_dir_final/calibration.bin
–verbose