Right, runned on host pc ubuntu18.04 with deepstream5.1
/home/satchel/deepstream_models/person1/yolov4_resnet10_epoch_080.etlt_b1_gpu0_fp32.engine was generated by running the gst pipeline with “#model-engine-file=/home/satchel/deepstream_models/person1/yolov4_resnet10_epoch_080.etlt_b1_gpu0_fp32”.engine noted off
After step 2, I noted off # to run gst pipeline again.
I tried deepstream_tlt_apps, but it seemed there were new errors happend.
(base) satchel@satchel-ubuntu:~/deeplearning/Deploy/deepstream_tlt_apps/apps$ ./ds-tlt -c /home/satchel/deepstream_models/person/pgie_yolov4_tlt_config.txt -i /home/satchel/softwares/deepstream_sdk_v5.1.0_x86_64/opt/nvidia/deepstream/deepstream/samples/streams/sample_720p.h264
Unknown or legacy key specified ‘is-classifier’ for group [property]
Now playing: /home/satchel/deepstream_models/person/pgie_yolov4_tlt_config.txt
WARNING: …/nvdsinfer/nvdsinfer_func_utils.cpp:36 [TRT]: TensorRT was linked against cuDNN 8.1.0 but loaded cuDNN 8.0.5
WARNING: …/nvdsinfer/nvdsinfer_func_utils.cpp:36 [TRT]: TensorRT was linked against cuBLAS/cuBLAS LT 11.3.0 but loaded cuBLAS/cuBLAS LT 11.2.1
WARNING: …/nvdsinfer/nvdsinfer_func_utils.cpp:36 [TRT]: TensorRT was linked against cuDNN 8.1.0 but loaded cuDNN 8.0.5
WARNING: …/nvdsinfer/nvdsinfer_func_utils.cpp:36 [TRT]: TensorRT was linked against cuBLAS/cuBLAS LT 11.3.0 but loaded cuBLAS/cuBLAS LT 11.2.1
0:00:00.990112100 13808 0x56227d5ee070 INFO nvinfer gstnvinfer.cpp:619:gst_nvinfer_logger: NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:1702> [UID = 1]: deserialized trt engine from :/home/satchel/deepstream_models/person/yolov4_resnet10_epoch_080.etlt_b1_gpu0_fp32.engine
INFO: …/nvdsinfer/nvdsinfer_model_builder.cpp:685 [Implicit Engine Info]: layers num: 5
0 INPUT kFLOAT Input 3x384x640
1 OUTPUT kINT32 BatchedNMS 0
2 OUTPUT kFLOAT BatchedNMS_1 200x4
3 OUTPUT kFLOAT BatchedNMS_2 200
4 OUTPUT kFLOAT BatchedNMS_3 200
0:00:00.990235266 13808 0x56227d5ee070 INFO nvinfer gstnvinfer.cpp:619:gst_nvinfer_logger: NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:1806> [UID = 1]: Use deserialized engine model: /home/satchel/deepstream_models/person/yolov4_resnet10_epoch_080.etlt_b1_gpu0_fp32.engine
0:00:00.996335490 13808 0x56227d5ee070 INFO nvinfer gstnvinfer_impl.cpp:313:notifyLoadModelStatus: [UID 1]: Load new model:/home/satchel/deepstream_models/person/pgie_yolov4_tlt_config.txt sucessfully
Running…
ERROR: nvdsinfer_context_impl.cpp:1573 Failed to synchronize on cuda copy-coplete-event, cuda err_no:700, err_str:cudaErrorIllegalAddress
0:00:01.248884517 13808 0x56227d5e6f20 WARN nvinfer gstnvinfer.cpp:2021:gst_nvinfer_output_loop: error: Failed to dequeue output from inferencing. NvDsInferContext error: NVDSINFER_CUDA_ERROR
ERROR: …/nvdsinfer/nvdsinfer_func_utils.cpp:33 [TRT]: safeContext.cpp (184) - Cudnn Error in configure: 7 (CUDNN_STATUS_MAPPING_ERROR)
0:00:01.248930787 13808 0x56227d5e6f20 WARN nvinfer gstnvinfer.cpp:616:gst_nvinfer_logger: NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::releaseBatchOutput() <nvdsinfer_context_impl.cpp:1599> [UID = 1]: Tried to release an unknown outputBatchID
ERROR from element primary-nvinference-engine: Failed to dequeue output from inferencing. NvDsInferContext error: NVDSINFER_CUDA_ERROR
Error details: gstnvinfer.cpp(2021): gst_nvinfer_output_loop (): /GstPipeline:ds-custom-pipeline/GstNvInfer:primary-nvinference-engine
Returned, stopping playback
ERROR: …/nvdsinfer/nvdsinfer_func_utils.cpp:33 [TRT]: FAILED_EXECUTION: std::exception
ERROR: nvdsinfer_backend.cpp:287 Failed to enqueue inference batch
Cuda failure: status=700 in CreateTextureObj at line 2902
ERROR: nvdsinfer_context_impl.cpp:1533 Infer context enqueue buffer failed, nvinfer error:NVDSINFER_TENSORRT_ERROR
nvbufsurftransform.cpp:2703: => Transformation Failed -2
0:00:01.249032995 13808 0x56227d5e6d40 WARN nvinfer gstnvinfer.cpp:1225:gst_nvinfer_input_queue_loop: error: Failed to queue input batch for inferencing
段错误 (核心已转储)
tlt-model-key=Y29iMHNhOTkwcmo4c3ViNmNmcXZob3BxM2I6N2EzM2I0NjYtOTFlYy00NzUzLWE3NWYtZGViMjdhMDgxNGZi yolov4_resnet10_epoch_080.etlt (11.1 MB) pgie_yolov4_tlt_config.txt (2.3 KB)
The tlt-model-key and tlt model have been uploaded.
Please help. Thanks