Segmentation Error DS 7.0

Accelerated Computing Intelligent Video Analytics DeepStream SDK
1

Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU): 4070ti
• DeepStream Version: 7.0
• TensorRT Version:8.6
• NVIDIA GPU Driver Version (valid for GPU only): 535.161.08
• Issue Type( questions, new requirements, bugs)
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing)

I’m getting the below error after compiling :

eegrab@eegrab:~/c++/deepstream/anpr_kp_spd_demo$ ./ANPR_SPD ./models/anpr_config.yml ./config.json
Now playing : file:///home/eegrab/front3.mp4
save_img
main buffer probe
Using file: ./models/anpr_config.yml
WARNING: [TRT]: Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors.
0:00:03.602322786  4574 0x610b09ab9350 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<secondary2-nvinference-engine> NvDsInferContext[UID 3]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:2095> [UID = 3]: deserialized trt engine from :/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/indian_lpr.engine
WARNING: [TRT]: The getMaxBatchSize() function should not be used with an engine built from a network created with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag. This function will always return 1.
INFO: ../nvdsinfer/nvdsinfer_model_builder.cpp:612 [Implicit Engine Info]: layers num: 3
0   INPUT  kFLOAT image_input     3x48x96         
1   OUTPUT kINT32 tf_op_layer_ArgMax 24              
2   OUTPUT kFLOAT tf_op_layer_Max 24              

0:00:03.700760901  4574 0x610b09ab9350 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<secondary2-nvinference-engine> NvDsInferContext[UID 3]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2198> [UID = 3]: Use deserialized engine model: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/indian_lpr.engine
0:00:03.703692873  4574 0x610b09ab9350 INFO                 nvinfer gstnvinfer_impl.cpp:343:notifyLoadModelStatus:<secondary2-nvinference-engine> [UID 3]: Load new model:/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/lpr_config_sgie_us.yml sucessfully
WARNING: [TRT]: Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors.
Deserialize yoloLayer plugin: yolo
0:00:06.637291829  4574 0x610b09ab9350 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<secondary1-nvinference-engine> NvDsInferContext[UID 2]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:2095> [UID = 2]: deserialized trt engine from :/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/lpd.engine
WARNING: [TRT]: The getMaxBatchSize() function should not be used with an engine built from a network created with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag. This function will always return 1.
INFO: ../nvdsinfer/nvdsinfer_model_builder.cpp:612 [Implicit Engine Info]: layers num: 4
0   INPUT  kFLOAT input           3x416x416       
1   OUTPUT kFLOAT boxes           2535x4          
2   OUTPUT kFLOAT scores          2535x1          
3   OUTPUT kFLOAT classes         2535x1          

0:00:06.743976249  4574 0x610b09ab9350 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<secondary1-nvinference-engine> NvDsInferContext[UID 2]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2198> [UID = 2]: Use deserialized engine model: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/lpd.engine
0:00:06.745996427  4574 0x610b09ab9350 INFO                 nvinfer gstnvinfer_impl.cpp:343:notifyLoadModelStatus:<secondary1-nvinference-engine> [UID 2]: Load new model:/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/sgie1_config.yml sucessfully
gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream/lib/libnvds_nvmultiobjecttracker.so
[NvMultiObjectTracker] Initialized
WARNING: [TRT]: Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors.
0:00:09.687011938  4574 0x610b09ab9350 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<primary-nvinference-engine> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:2095> [UID = 1]: deserialized trt engine from :/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/vehicle_detection_v3.0.engine
WARNING: [TRT]: The getMaxBatchSize() function should not be used with an engine built from a network created with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag. This function will always return 1.
INFO: ../nvdsinfer/nvdsinfer_model_builder.cpp:612 [Implicit Engine Info]: layers num: 2
0   INPUT  kFLOAT input           3x640x640       
1   OUTPUT kFLOAT output          25200x6         

0:00:09.795203902  4574 0x610b09ab9350 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<primary-nvinference-engine> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2198> [UID = 1]: Use deserialized engine model: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/vehicle_detection_v3.0.engine
0:00:09.798425067  4574 0x610b09ab9350 INFO                 nvinfer gstnvinfer_impl.cpp:343:notifyLoadModelStatus:<primary-nvinference-engine> [UID 1]: Load new model:/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/pgie_config.yml sucessfully
Decodebin child added: source
Decodebin child added: decodebin0
Running...

Decodebin child added: qtdemux0
Decodebin child added: multiqueue0
Decodebin child added: h265parse0
Decodebin child added: capsfilter0
Decodebin child added: nvv4l2decoder0
Segmentation fault (core dumped)
eegrab@eegrab:~/c++/deepstream/anpr_kp_spd_demo$ ./ANPR_SPD ./models/anpr_config.yml ./config.json --gst-debug=3
Now playing : file:///home/eegrab/front3.mp4
save_img
main buffer probe
Using file: ./models/anpr_config.yml
WARNING: [TRT]: Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors.
0:00:03.291304749  4684 0x5edc9ef89750 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<secondary2-nvinference-engine> NvDsInferContext[UID 3]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:2095> [UID = 3]: deserialized trt engine from :/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/indian_lpr.engine
WARNING: [TRT]: The getMaxBatchSize() function should not be used with an engine built from a network created with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag. This function will always return 1.
INFO: ../nvdsinfer/nvdsinfer_model_builder.cpp:612 [Implicit Engine Info]: layers num: 3
0   INPUT  kFLOAT image_input     3x48x96         
1   OUTPUT kINT32 tf_op_layer_ArgMax 24              
2   OUTPUT kFLOAT tf_op_layer_Max 24              

0:00:03.392155985  4684 0x5edc9ef89750 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<secondary2-nvinference-engine> NvDsInferContext[UID 3]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2198> [UID = 3]: Use deserialized engine model: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/indian_lpr.engine
0:00:03.394944638  4684 0x5edc9ef89750 INFO                 nvinfer gstnvinfer_impl.cpp:343:notifyLoadModelStatus:<secondary2-nvinference-engine> [UID 3]: Load new model:/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/lpr_config_sgie_us.yml sucessfully
WARNING: [TRT]: Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors.
Deserialize yoloLayer plugin: yolo
0:00:06.311757855  4684 0x5edc9ef89750 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<secondary1-nvinference-engine> NvDsInferContext[UID 2]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:2095> [UID = 2]: deserialized trt engine from :/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/lpd.engine
WARNING: [TRT]: The getMaxBatchSize() function should not be used with an engine built from a network created with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag. This function will always return 1.
INFO: ../nvdsinfer/nvdsinfer_model_builder.cpp:612 [Implicit Engine Info]: layers num: 4
0   INPUT  kFLOAT input           3x416x416       
1   OUTPUT kFLOAT boxes           2535x4          
2   OUTPUT kFLOAT scores          2535x1          
3   OUTPUT kFLOAT classes         2535x1          

0:00:06.419790642  4684 0x5edc9ef89750 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<secondary1-nvinference-engine> NvDsInferContext[UID 2]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2198> [UID = 2]: Use deserialized engine model: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/lpd.engine
0:00:06.421593129  4684 0x5edc9ef89750 INFO                 nvinfer gstnvinfer_impl.cpp:343:notifyLoadModelStatus:<secondary1-nvinference-engine> [UID 2]: Load new model:/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/sgie1_config.yml sucessfully
gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream/lib/libnvds_nvmultiobjecttracker.so
[NvMultiObjectTracker] Initialized
WARNING: [TRT]: Using an engine plan file across different models of devices is not recommended and is likely to affect performance or even cause errors.
0:00:09.342430216  4684 0x5edc9ef89750 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<primary-nvinference-engine> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:2095> [UID = 1]: deserialized trt engine from :/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/vehicle_detection_v3.0.engine
WARNING: [TRT]: The getMaxBatchSize() function should not be used with an engine built from a network created with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag. This function will always return 1.
INFO: ../nvdsinfer/nvdsinfer_model_builder.cpp:612 [Implicit Engine Info]: layers num: 2
0   INPUT  kFLOAT input           3x640x640       
1   OUTPUT kFLOAT output          25200x6         

0:00:09.450669323  4684 0x5edc9ef89750 INFO                 nvinfer gstnvinfer.cpp:682:gst_nvinfer_logger:<primary-nvinference-engine> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2198> [UID = 1]: Use deserialized engine model: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/vehicle_detection_v3.0.engine
0:00:09.452470944  4684 0x5edc9ef89750 INFO                 nvinfer gstnvinfer_impl.cpp:343:notifyLoadModelStatus:<primary-nvinference-engine> [UID 1]: Load new model:/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/pgie_config.yml sucessfully
0:00:09.452786641  4684 0x5edc9ef89750 WARN                 basesrc gstbasesrc.c:3688:gst_base_src_start_complete:<source> pad not activated yet
Decodebin child added: source
Decodebin child added: decodebin0
0:00:09.452953818  4684 0x5edc9ef89750 WARN                 basesrc gstbasesrc.c:3688:gst_base_src_start_complete:<source> pad not activated yet
Running...

Decodebin child added: qtdemux0
0:00:09.457270682  4684 0x5edcb1883640 WARN                 qtdemux qtdemux.c:7963:qtdemux_parse_container:<qtdemux0> length too long (1638400 > 29)
0:00:09.457311858  4684 0x5edcb1883640 WARN                 qtdemux qtdemux.c:3121:qtdemux_parse_trex:<qtdemux0> failed to find fragment defaults for stream 1
0:00:09.457358278  4684 0x5edcb1883640 WARN                 qtdemux qtdemux.c:10208:qtdemux_parse_segments:<qtdemux0> Segment 0  extends to 0:01:05.630763000 past the end of the declared movie duration 0:00:58.931728000 movie segment will be extended
Decodebin child added: multiqueue0
Decodebin child added: h265parse0
Decodebin child added: capsfilter0
Decodebin child added: nvv4l2decoder0
0:00:09.459787771  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459796338  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe minimum capture size for pixelformat MJPG
0:00:09.459801759  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459806031  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe maximum capture size for pixelformat MJPG
0:00:09.459817653  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459823906  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe minimum capture size for pixelformat AV10
0:00:09.459828247  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459832196  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe maximum capture size for pixelformat AV10
0:00:09.459840263  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459844231  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe minimum capture size for pixelformat DVX5
0:00:09.459850205  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459854129  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe maximum capture size for pixelformat DVX5
0:00:09.459861502  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459865456  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe minimum capture size for pixelformat DVX4
0:00:09.459869334  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459873190  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe maximum capture size for pixelformat DVX4
0:00:09.459880296  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459886301  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe minimum capture size for pixelformat MPG4
0:00:09.459890483  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459894574  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe maximum capture size for pixelformat MPG4
0:00:09.459901558  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459905633  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe minimum capture size for pixelformat MPG2
0:00:09.459909499  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459913449  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe maximum capture size for pixelformat MPG2
0:00:09.459921001  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459925112  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe minimum capture size for pixelformat H265
0:00:09.459929097  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459932836  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe maximum capture size for pixelformat H265
0:00:09.459939761  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459943540  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe minimum capture size for pixelformat VP90
0:00:09.459947446  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459951257  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe maximum capture size for pixelformat VP90
0:00:09.459957710  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459961518  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe minimum capture size for pixelformat VP80
0:00:09.459965424  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459968951  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe maximum capture size for pixelformat VP80
0:00:09.459978221  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459982153  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe minimum capture size for pixelformat H264
0:00:09.459986089  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:sink> Unable to try format: Unknown error -1
0:00:09.459989790  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:sink> Could not probe maximum capture size for pixelformat H264
0:00:09.460215951  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:src> Unable to try format: Unknown error -1
0:00:09.460221483  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:src> Could not probe minimum capture size for pixelformat Y444
0:00:09.460225049  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:src> Unable to try format: Unknown error -1
0:00:09.460229075  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:src> Could not probe maximum capture size for pixelformat Y444
0:00:09.460238271  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:src> Unable to try format: Unknown error -1
0:00:09.460242616  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:src> Could not probe minimum capture size for pixelformat P410
0:00:09.460246659  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:src> Unable to try format: Unknown error -1
0:00:09.460250668  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:src> Could not probe maximum capture size for pixelformat P410
0:00:09.460258763  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:src> Unable to try format: Unknown error -1
0:00:09.460262648  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:src> Could not probe minimum capture size for pixelformat PM10
0:00:09.460266662  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:src> Unable to try format: Unknown error -1
0:00:09.460270299  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:src> Could not probe maximum capture size for pixelformat PM10
0:00:09.460278531  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:src> Unable to try format: Unknown error -1
0:00:09.460282551  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2985:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:src> Could not probe minimum capture size for pixelformat NM12
0:00:09.460286530  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:3100:gst_v4l2_object_get_nearest_size:<nvv4l2decoder0:src> Unable to try format: Unknown error -1
0:00:09.460290232  4684 0x728fd40a4b60 WARN                    v4l2 gstv4l2object.c:2991:gst_v4l2_object_probe_caps_for_format:<nvv4l2decoder0:src> Could not probe maximum capture size for pixelformat NM12
0:00:09.564569168  4684 0x728fd40a4b60 WARN            v4l2videodec gstv4l2videodec.c:2311:gst_v4l2_video_dec_decide_allocation:<nvv4l2decoder0> Duration invalid, not setting latency
0:00:09.564582368  4684 0x728fd40a4b60 WARN          v4l2bufferpool gstv4l2bufferpool.c:1116:gst_v4l2_buffer_pool_start:<nvv4l2decoder0:pool:src> Uncertain or not enough buffers, enabling copy threshold
0:00:09.565394688  4684 0x728fc4006ea0 WARN          v4l2bufferpool gstv4l2bufferpool.c:1567:gst_v4l2_buffer_pool_dqbuf:<nvv4l2decoder0:pool:src> Driver should never set v4l2_buffer.field to ANY
Segmentation fault (core dumped)

The pipeline is as such:

gst_bin_add_many(GST_BIN(pipeline), queue1, pgie, queue2, tracker, queue3, sgie1, queue4,
                         sgie2, queue5, nvdslogger, queue6, nvvidconv, queue7, nvosd, queue8, sink, NULL);
        /* we link the elements together
         * nvstreammux -> nvinfer -> nvdslogger -> nvtiler -> nvvidconv -> nvosd
         * -> video-renderer */
        if (!gst_element_link_many(streammux, queue1, pgie, queue2, tracker, queue3, sgie1, queue4,
                                   sgie2, queue5, nvdslogger, nvvidconv, queue7, nvosd, sink, NULL))
        {
            g_printerr("Elements could not be linked. Exiting.\n");
            return -1;
        }

Can you please help @junshengy ? I shall be highly obliged. The same code runs fine for DS 6.3

3

This seems to be your custom program, do you use gdb debugging? What does the stack look like? Can you reproduce it using the SDK sample code?

It is also recommended that you use the new version, we generally do not fix issues with legacy versions

4

Thanks for your time @junshengy. I switched to DS 7.1. Still the error exists. I did debug using gdb. Here is the report:

eegrab@eegrab:~/c++/deepstream/anpr_kp_spd_demo$ gdb ./ANPR_SPD ./models/anpr_config.yml ./config.json
Excess command line arguments ignored. (./config.json)
GNU gdb (Ubuntu 12.1-0ubuntu1~22.04.2) 12.1
Copyright (C) 2022 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.
Type "show copying" and "show warranty" for details.
This GDB was configured as "x86_64-linux-gnu".
Type "show configuration" for configuration details.
For bug reporting instructions, please see:
<https://www.gnu.org/software/gdb/bugs/>.
Find the GDB manual and other documentation resources online at:
    <http://www.gnu.org/software/gdb/documentation/>.

For help, type "help".
Type "apropos word" to search for commands related to "word"...
Reading symbols from ./ANPR_SPD...
"/home/eegrab/c++/deepstream/anpr_kp_spd_demo/./models/anpr_config.yml" is not a core dump: file format not recognized
(gdb) r
Starting program: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/ANPR_SPD 
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
[New Thread 0x7fffeb000000 (LWP 20085)]
[New Thread 0x7fffea600000 (LWP 20086)]
Usage: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/ANPR_SPD <yml file>
OR: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/ANPR_SPD <uri1> [uri2] ... [uriN] 
[Thread 0x7fffeb000000 (LWP 20085) exited]
[Thread 0x7fffea600000 (LWP 20086) exited]
[Inferior 1 (process 20082) exited with code 0377]
(gdb)

Any help is highly appreciated. I’m also attaching the anpr_config.yaml:

source-list:
  # list: file:///home/mainak/ms/python/speedViolation_anpr/lane2.mp4;
  # list : rtsp://192.168.144.25:8554/main.264;
  # list : http://3.109.22.98:8080/record/live_400.flv;
  # list: file:///home/eegrab/data/kp/front5.mp4;
  list: file:///home/eegrab/front3.mp4
  # list: rtmp://192.168.1.50/live/stream1;

streammux:
  batch-size: 1
  batched-push-timeout: 40000
  width: 1920
  height: 1056
  attach-sys-ts : 1
  live-source : 0

osd:
  process-mode: 0
  display-text: 1

#If there is ROI
analytics-config:
        #filename: config_nvdsanalytics.txt

triton:
  ## 0:disable 1:enable
  enable: 0
  ##0:trtion-native 1:triton-grpc
  type: 0
  ##car mode, 1:US car plate model|2: Chinese car plate model
  car-mode: 1

output:
  ## 1:file ouput  2:fake output 3:eglsink output
  type: 1
  ## 0: H264 encoder  1:H265 encoder
  enc: 0
  bitrate: 4000000
  ##The file name without suffix
  filename: anpr

primary-gie:
  ##For car detection
  config-file-path: ./pgie_config.yml
  unique-id: 1

secondary-gie-0:
  ##For US car plate
  config-file-path: ./sgie1_config.yml
  ##For China mainland car plate
  #config-file-path: lpd_ccpd_yolov4-tiny_config.yml
  unique-id: 2
  process-mode: 2

secondary-gie-1:
  ##For US car plate recognization
  config-file-path: ./lpr_config_sgie_us.yml
  ##For China mainland car plate recognization
  #config-file-path: lpr_config_sgie_ch.yml
  unique-id: 3
  process-mode: 2
5

This information is useless, there is no stack trace

gdb --args “your-application" "paramaters"

Then enterr, After application crash, enter bt command. We will not debug user applications.

6

I completely understand. Thank’s again for your time @junshengy. However for sgie2 I’m using LPRNet. Debugging gives the following error:

eegrab@eegrab:~/c++/deepstream/anpr_kp_spd_demo$ gdb --args ./ANPR_SPD ./models/anpr_config.yml ./config.json
GNU gdb (Ubuntu 12.1-0ubuntu1~22.04.2) 12.1
Copyright (C) 2022 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.
Type "show copying" and "show warranty" for details.
This GDB was configured as "x86_64-linux-gnu".
Type "show configuration" for configuration details.
For bug reporting instructions, please see:
<https://www.gnu.org/software/gdb/bugs/>.
Find the GDB manual and other documentation resources online at:
    <http://www.gnu.org/software/gdb/documentation/>.

For help, type "help".
Type "apropos word" to search for commands related to "word"...
Reading symbols from ./ANPR_SPD...
(gdb) r
Starting program: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/ANPR_SPD ./models/anpr_config.yml ./config.json
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
[New Thread 0x7fffeb000000 (LWP 21246)]
[New Thread 0x7fffea600000 (LWP 21247)]
Now playing : file:///home/eegrab/front3.mp4
[New Thread 0x7fffc5c00000 (LWP 21248)]
[New Thread 0x7fffc5200000 (LWP 21249)]
[Detaching after vfork from child process 21253]
[Detaching after vfork from child process 21254]
save_img
main buffer probe
Using file: ./models/anpr_config.yml
[New Thread 0x7fffbb200000 (LWP 21255)]
[New Thread 0x7fffb7e00000 (LWP 21256)]
[New Thread 0x7fffb7400000 (LWP 21257)]
0:00:00.286322473 21243 0x55555685dd50 INFO                 nvinfer gstnvinfer.cpp:684:gst_nvinfer_logger:<secondary2-nvinference-engine> NvDsInferContext[UID 3]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:2092> [UID = 3]: deserialized trt engine from :/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/indian_lpr.engine
Implicit layer support has been deprecated
INFO: ../nvdsinfer/nvdsinfer_model_builder.cpp:327 [Implicit Engine Info]: layers num: 0

0:00:00.286356742 21243 0x55555685dd50 INFO                 nvinfer gstnvinfer.cpp:684:gst_nvinfer_logger:<secondary2-nvinference-engine> NvDsInferContext[UID 3]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2195> [UID = 3]: Use deserialized engine model: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/indian_lpr.engine
[New Thread 0x7fffb6a00000 (LWP 21258)]
[New Thread 0x7fffa7400000 (LWP 21259)]
[New Thread 0x7fffa6a00000 (LWP 21260)]
0:00:00.291135478 21243 0x55555685dd50 INFO                 nvinfer gstnvinfer_impl.cpp:343:notifyLoadModelStatus:<secondary2-nvinference-engine> [UID 3]: Load new model:/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/lpr_config_sgie_us.yml sucessfully
[New Thread 0x7fffa6000000 (LWP 21261)]
Deserialize yoloLayer plugin: /home/eegrab/c++/deepstream/testing_app/models/lpd.weights
0:00:00.307833610 21243 0x55555685dd50 INFO                 nvinfer gstnvinfer.cpp:684:gst_nvinfer_logger:<secondary1-nvinference-engine> NvDsInferContext[UID 2]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:2092> [UID = 2]: deserialized trt engine from :/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/lpd.engine
Implicit layer support has been deprecated
INFO: ../nvdsinfer/nvdsinfer_model_builder.cpp:327 [Implicit Engine Info]: layers num: 0

0:00:00.307851021 21243 0x55555685dd50 INFO                 nvinfer gstnvinfer.cpp:684:gst_nvinfer_logger:<secondary1-nvinference-engine> NvDsInferContext[UID 2]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2195> [UID = 2]: Use deserialized engine model: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/lpd.engine
[New Thread 0x7fffa5600000 (LWP 21262)]
[New Thread 0x7fffa4c00000 (LWP 21263)]
[New Thread 0x7fff9fe00000 (LWP 21264)]
0:00:00.308483760 21243 0x55555685dd50 INFO                 nvinfer gstnvinfer_impl.cpp:343:notifyLoadModelStatus:<secondary1-nvinference-engine> [UID 2]: Load new model:/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/sgie1_config.yml sucessfully
[New Thread 0x7fff9f400000 (LWP 21265)]
gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream/lib/libnvds_nvmultiobjecttracker.so
[NvMultiObjectTracker] Initialized
[New Thread 0x7fff9ea00000 (LWP 21266)]
[New Thread 0x7fff9e000000 (LWP 21267)]
[New Thread 0x7fff9d600000 (LWP 21268)]
0:00:00.406160644 21243 0x55555685dd50 INFO                 nvinfer gstnvinfer.cpp:684:gst_nvinfer_logger:<primary-nvinference-engine> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:2092> [UID = 1]: deserialized trt engine from :/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/yolov8_pgie.engine
Implicit layer support has been deprecated
INFO: ../nvdsinfer/nvdsinfer_model_builder.cpp:327 [Implicit Engine Info]: layers num: 0

0:00:00.406182072 21243 0x55555685dd50 INFO                 nvinfer gstnvinfer.cpp:684:gst_nvinfer_logger:<primary-nvinference-engine> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2195> [UID = 1]: Use deserialized engine model: /home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/yolov8_pgie.engine
[New Thread 0x7fff9cc00000 (LWP 21269)]
[New Thread 0x7fff93e00000 (LWP 21270)]
[New Thread 0x7fff93400000 (LWP 21271)]
0:00:00.406899886 21243 0x55555685dd50 INFO                 nvinfer gstnvinfer_impl.cpp:343:notifyLoadModelStatus:<primary-nvinference-engine> [UID 1]: Load new model:/home/eegrab/c++/deepstream/anpr_kp_spd_demo/models/pgie_config.yml sucessfully
[New Thread 0x7fff92a00000 (LWP 21272)]
Decodebin child added: source
Decodebin child added: decodebin0
[New Thread 0x7fff8de00000 (LWP 21273)]
[New Thread 0x7fff8d400000 (LWP 21274)]
[New Thread 0x7fff8ca00000 (LWP 21275)]
Running...
Decodebin child added: qtdemux0
[New Thread 0x7fff87e00000 (LWP 21276)]
Decodebin child added: multiqueue0
[New Thread 0x7fff87400000 (LWP 21277)]
Decodebin child added: h265parse0
Decodebin child added: capsfilter0
Decodebin child added: nvv4l2decoder0
Failed to query video capabilities: Invalid argument
[New Thread 0x7fff85400000 (LWP 21278)]
[New Thread 0x7fff84a00000 (LWP 21279)]
[New Thread 0x7fff7a200000 (LWP 21280)]
[New Thread 0x7fff79800000 (LWP 21281)]
[New Thread 0x7fff78e00000 (LWP 21282)]
[New Thread 0x7fff71200000 (LWP 21283)]
[New Thread 0x7fff21600000 (LWP 21284)]
[Detaching after vfork from child process 21285]
[Detaching after vfork from child process 21287]
[New Thread 0x7fff20c00000 (LWP 21289)]
[New Thread 0x7fff1de00000 (LWP 21290)]
[New Thread 0x7fff1d400000 (LWP 21291)]
[New Thread 0x7fff1ca00000 (LWP 21292)]
[New Thread 0x7fff15800000 (LWP 21293)]
[New Thread 0x7fff14e00000 (LWP 21294)]
[New Thread 0x7fff0be00000 (LWP 21295)]
[New Thread 0x7fff0b400000 (LWP 21296)]
[New Thread 0x7fff0aa00000 (LWP 21297)]
[New Thread 0x7ffefde00000 (LWP 21298)]
[New Thread 0x7ffefd400000 (LWP 21299)]
[New Thread 0x7ffefca00000 (LWP 21300)]
[New Thread 0x7ffef7e00000 (LWP 21301)]
[New Thread 0x7ffef7400000 (LWP 21302)]
[New Thread 0x7ffef6a00000 (LWP 21303)]
[New Thread 0x7ffef6000000 (LWP 21304)]
[New Thread 0x7ffef5600000 (LWP 21305)]
[New Thread 0x7ffef4c00000 (LWP 21306)]
[New Thread 0x7ffeebe00000 (LWP 21307)]
[New Thread 0x7ffeeb400000 (LWP 21308)]
[New Thread 0x7ffeeaa00000 (LWP 21309)]
[New Thread 0x7ffeea000000 (LWP 21310)]
[New Thread 0x7ffee9600000 (LWP 21311)]
[New Thread 0x7ffee8c00000 (LWP 21312)]
[New Thread 0x7ffedfe00000 (LWP 21313)]
[New Thread 0x7ffedf400000 (LWP 21314)]
[New Thread 0x7ffedea00000 (LWP 21315)]
[New Thread 0x7ffedce00000 (LWP 21316)]
[New Thread 0x7ffed3e00000 (LWP 21317)]
[New Thread 0x7ffed3400000 (LWP 21318)]
[New Thread 0x7ffed2a00000 (LWP 21319)]
[Detaching after vfork from child process 21320]
[Detaching after vfork from child process 21321]

Thread 9 "ANPR_SPD" received signal SIGSEGV, Segmentation fault.
[Switching to Thread 0x7fffb6a00000 (LWP 21258)]
0x00007fffe81e9047 in NvDsInferParseCustomNVPlate () from /home/eegrab/c++/deepstream/anpr_kp_spd_demo/nvinfer_custom_lpr_parser/libnvdsinfer_custom_impl_lpr.so
(gdb) bt
#0  0x00007fffe81e9047 in NvDsInferParseCustomNVPlate ()
    at /home/eegrab/c++/deepstream/anpr_kp_spd_demo/nvinfer_custom_lpr_parser/libnvdsinfer_custom_impl_lpr.so
#1  0x00007fffe9d55162 in nvdsinfer::ClassifyPostprocessor::fillClassificationOutput(std::vector<NvDsInferLayerInfo, std::allocator<NvDsInferLayerInfo> > const&, NvDsInferClassificationOutput&) () at ///opt/nvidia/deepstream/deepstream-7.1/lib/libnvds_infer.so
#2  0x00007fffe9d33247 in nvdsinfer::ClassifyPostprocessor::parseEachBatch(std::vector<NvDsInferLayerInfo, std::allocator<NvDsInferLayerInfo> > const&, NvDsInferFrameOutput&) () at ///opt/nvidia/deepstream/deepstream-7.1/lib/libnvds_infer.so
#3  0x00007fffe9d3a72a in nvdsinfer::InferPostprocessor::postProcessHost(nvdsinfer::NvDsInferBatch&, NvDsInferContextBatchOutput&) ()
    at ///opt/nvidia/deepstream/deepstream-7.1/lib/libnvds_infer.so
#4  0x00007fffe9d353a8 in nvdsinfer::NvDsInferContextImpl::dequeueOutputBatch(NvDsInferContextBatchOutput&) ()
    at ///opt/nvidia/deepstream/deepstream-7.1/lib/libnvds_infer.so
#5  0x00007fffe9dcfd0d in  () at /usr/lib/x86_64-linux-gnu/gstreamer-1.0/deepstream/libnvdsgst_infer.so
#6  0x00007ffff7ccdab1 in  () at /lib/x86_64-linux-gnu/libglib-2.0.so.0
#7  0x00007ffff5294ac3 in start_thread (arg=<optimized out>) at ./nptl/pthread_create.c:442
#8  0x00007ffff5326850 in clone3 () at ../sysdeps/unix/sysv/linux/x86_64/clone3.S:81

I followed this step to generate the .so file for LPRNet /usr/bin/ld: cannot find -lnvparsers: No such file or directory - #3 by junshengy
When I’m removing sgie2 it’s working perfectly. Any suggestions why LPRNet is throwing a problem??

7

For DS-7.1, The lpr sample has been moved to deepstream_tao_apps/apps/tao_others/deepstream_lpr_app at release/tao_ds7.1ga · NVIDIA-AI-IOT/deepstream_tao_apps · GitHub Please refer to the new link. Make sure the sample work normally first.

8

Thanks. I’ll move to TAO forum for further queries. Thank You

9

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