Hi i am trying to develop emotion recognition project with FaceNet and my own TAO model over deepstream_test_2 template. I am getting this error:
ali@ali:~/Desktop/face-deployable-test-2$ python3 deepstream_test_2.py womanexpression.h264
Creating Pipeline
Creating Source
Creating H264Parser
Creating Decoder
Creating EGLSink
Playing file womanexpression.h264
Warning: ‘input-dims’ parameter has been deprecated. Use ‘infer-dims’ instead.
Adding elements to Pipeline
Linking elements in the Pipeline
Starting pipeline
0:00:00.134727294 268040 0x335db90 INFO nvinfer gstnvinfer.cpp:646:gst_nvinfer_logger: NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1923> [UID = 1]: Trying to create engine from model files
WARNING: [TRT]: CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See CUDA_MODULE_LOADING in CUDA C++ Programming Guide
WARNING: [TRT]: CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See CUDA_MODULE_LOADING in CUDA C++ Programming Guide
ERROR: [TRT]: 3: [builder.cpp::~Builder::307] Error Code 3: API Usage Error (Parameter check failed at: optimizer/api/builder.cpp::~Builder::307, condition: mObjectCounter.use_count() == 1. Destroying a builder object before destroying objects it created leads to undefined behavior.
)
WARNING: [TRT]: The implicit batch dimension mode has been deprecated. Please create the network with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag whenever possible.
0:00:39.310399942 268040 0x335db90 INFO nvinfer gstnvinfer.cpp:646:gst_nvinfer_logger: NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1955> [UID = 1]: serialize cuda engine to file: /home/ali/Desktop/face-deployable-test-2/emotionmodel.etlt_b30_gpu0_fp32.engine successfully
WARNING: [TRT]: CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See CUDA_MODULE_LOADING in CUDA C++ Programming Guide
INFO: …/nvdsinfer/nvdsinfer_model_builder.cpp:610 [Implicit Engine Info]: layers num: 2
0 INPUT kFLOAT input_1 3x224x224
1 OUTPUT kFLOAT predictions/Softmax 7x1x1
0:00:39.326044798 268040 0x335db90 INFO nvinfer gstnvinfer_impl.cpp:328:notifyLoadModelStatus: [UID 1]: Load new model:dstest2_sgie1_config.txt sucessfully
gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream/lib/libnvds_nvmultiobjecttracker.so
gstnvtracker: Batch processing is ON
gstnvtracker: Past frame output is OFF
[NvMultiObjectTracker] Initialized
0:00:39.332767850 268040 0x335db90 INFO nvinfer gstnvinfer.cpp:646:gst_nvinfer_logger: NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1923> [UID = 1]: Trying to create engine from model files
WARNING: [TRT]: CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See CUDA_MODULE_LOADING in CUDA C++ Programming Guide
WARNING: …/nvdsinfer/nvdsinfer_model_builder.cpp:659 INT8 calibration file not specified/accessible. INT8 calibration can be done through setDynamicRange API in ‘NvDsInferCreateNetwork’ implementation
WARNING: [TRT]: CUDA lazy loading is not enabled. Enabling it can significantly reduce device memory usage. See CUDA_MODULE_LOADING in CUDA C++ Programming Guide
ERROR: [TRT]: 3: [builder.cpp::~Builder::307] Error Code 3: API Usage Error (Parameter check failed at: optimizer/api/builder.cpp::~Builder::307, condition: mObjectCounter.use_count() == 1. Destroying a builder object before destroying objects it created leads to undefined behavior.
)
WARNING: [TRT]: The implicit batch dimension mode has been deprecated. Please create the network with NetworkDefinitionCreationFlag::kEXPLICIT_BATCH flag whenever possible.
ERROR: [TRT]: 3: [network.cpp::addInput::1615] Error Code 3: API Usage Error (Parameter check failed at: optimizer/api/network.cpp::addInput::1615, condition: isValidDims(dims, hasImplicitBatchDimension())
)
ERROR: [TRT]: UFFParser: Failed to parseInput for node input_1
ERROR: [TRT]: UffParser: Parser error: input_1: Failed to parse node - Invalid Tensor found at node input_1
parseModel: Failed to parse UFF model
ERROR: tlt/tlt_decode.cpp:358 Failed to build network, error in model parsing.
ERROR: [TRT]: 3: [builder.cpp::~Builder::307] Error Code 3: API Usage Error (Parameter check failed at: optimizer/api/builder.cpp::~Builder::307, condition: mObjectCounter.use_count() == 1. Destroying a builder object before destroying objects it created leads to undefined behavior.
)
ERROR: …/nvdsinfer/nvdsinfer_model_builder.cpp:723 Failed to create network using custom network creation function
ERROR: …/nvdsinfer/nvdsinfer_model_builder.cpp:789 Failed to get cuda engine from custom library API
0:00:40.885030889 268040 0x335db90 ERROR nvinfer gstnvinfer.cpp:640:gst_nvinfer_logger: NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1943> [UID = 1]: build engine file failed
Segmentation fault (core dumped)
primary config file:
[property]
gpu-id=0
net-scale-factor=0.0039215697906911373
tlt-encoded-model=facemodel.etlt
labelfile-path=labels.txt
force-implicit-batch-dim=1
tlt-model-key=nvidia_tlt
input-dims=3;240;384;0
uff-input-blob-name=input_1
batch-size=1
process-mode=1
model-color-format=0
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=1
#network-type=0 #bunu yeni ekledim
num-detected-classes=1
interval=0
gie-unique-id=1
# output-blob-names=output_bbox/BiasAdd;output_cov/Sigmoid
# output-blob-names=conv2d_bbox;conv2d_cov/Sigmoid
output-blob-names=predictions/Softmax
cluster-mode=2
uff-file=sample_ssd_relu6.uff
uff-input-blob-name=Input
# parse-bbox-func-name=parse_bbox_resnet
#Use the config params below for dbscan clustering mode
#[class-attrs-all]
#detected-min-w=4
#detected-min-h=4
#minBoxes=3
#eps=0.7
#Use the config params below for NMS clustering mode
[class-attrs-all]
topk=20
nms-iou-threshold=0.5
pre-cluster-threshold=0.2
## Per class configurations
[class-attrs-0]
topk=20
nms-iou-threshold=0.5
pre-cluster-threshold=0.4
#[class-attrs-1]
#pre-cluster-threshold=0.05
#eps=0.7
#dbscan-min-score=0.5
secondary config file :
[property]
gpu-id=0
net-scale-factor=1
offsets=123.67;116.28;103.53
#offsets=124;117;104
model-color-format=1
batch-size=30
labelfile-path=emotionlabels.txt
tlt-encoded-model=emotionmodel.etlt
tlt-model-key=nvidia_tlt
infer-dims=3;224;224 # where c = number of channels, h = height of the model input, w = width of model input
#parse-bbox-func-name=parse_bbox_resnet
uff-input-blob-name=input_1
#uff-input-order=0
output-blob-names=predictions/Softmax
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=0
# process-mode: 2 - inferences on crops from primary detector, 1 - inferences on whole frame
process-mode=2
num-detected-classes=7
interval=0
network-type=1 # defines that the model is a classifier.
gie-unique-id=1
classifier-threshold=0.2
my dataset is fer13, consist of 48*48 px gray images.
GPU 1060 GTX
deepstream-app version 6.1.1
DeepStreamSDK 6.1.1
Please Help, thank you.