TLT YOLOv4 (CSPDakrnet53) - TensorRT INT8 model gives wrong predictions (0 mAP)

Yes, you can ignore “force_ptq”.

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I cannot reproduce 0 mAP against trt int8 engine. You can try with my step.
My step:

  • Run a training with cspdarknet19 backbone(I forget to set to 53, I will try later) with KITTI dataset.
    Only run for 10 epochs. Then get the tlt model.
  • Generate etlt model and trt int8 engine

yolo_v4 export -k nvidia_tlt -m epoch_010.tlt -e spec.txt --engine_file 384_1248.engine --data_type int8 --batch_size 8 --batches 10 --cal_cache_file export/cal.bin --cal_data_file export/cal.tensorfile --cal_image_dir /kitti_path/training/image_2 -o 384_1248.etlt

  • Run evaluation

yolo_v4 evaluate -e spec.txt -m 384_1248.engine

Try with cspdarknet53 backbone, there is also no issue.

thanks alot.

Sure. will try and let you know.

can you please let me know what is the mAP you got with the test set?

About 60%, I just test only 10 epochs for public KITTI dataset.