jerryjiagit / facenet_trt Goto Github PK

hi! i'm trying to build own facial recognition system with facenet as feature extractor.when I try to run the output on the jetson tx2, I get very large time delays. i tried to use your project to build tensorrt models, but i failed.
could you provide tensorrt fp16 saved_model please?

hi, thanks in advance

how to run the program? can you provide steps to run the program.

MTCNN TRT convert for RNET and ONET execution issue: Input data has inconsistent batch size.

When running calibration for TensorRT INT8, encounter one failure "nvinfer1::DimsCHW nvinfer1::getCHW(const nvinfer1::Dims): Assertion `d.nbDims >= 3' failed" with TRT4.
Will check more on it.

thanks for the work, when i use model.pb, i get this error KeyError: "The name 'batch_join:0' refers to a Tensor which does not exist. The operation, 'batch_join', does not exist in the graph."
can u help me please
thanks in advance

I'm trying to load classifier.py and getting the following errorL

/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/importer.py", line 497, in _import_graph_def_internal
graph._c_graph, serialized, options) # pylint: disable=protected-access
tensorflow.python.framework.errors_impl.InvalidArgumentError: Node 'gradients/InceptionResnetV1/Bottleneck/BatchNorm/cond/FusedBatchNorm_1_grad/FusedBatchNormGrad' has an _output_shapes attribute inconsistent with the GraphDef for output #3: Dimension 0 in both shapes must be equal, but are 0 and 512. Shapes are [0] and [512]

ValueError: Node 'gradients/InceptionResnetV1/Bottleneck/BatchNorm/cond/FusedBatchNorm_1_grad/FusedBatchNormGrad' has an _output_shapes attribute inconsistent with the GraphDef for output #3: Dimension 0 in both shapes must be equal, but are 0 and 512. Shapes are [0] and [512].

Please help.

Today, during some testing, I found there is no runtime reducing with TensorRT for face identify checkpoint graph. But pb graph with TensorRT works as expected. Will work on the investigation and update later.

@JerryJiaGit
Hello, I tried replacing face.py, facenet.py, detect_face.py as you advised, but when I run the predict.py of facenet with 2 frozen models at https://github.com/davidsandberg/facenet/wiki#pre-trained-models, it runs extremely slowly (it shows a bunch of output and hangs) so I have to stop it from running, I ran on Jetson Nano. Sorry for not providing the output, my bad.

I have searched and doubt that the Inception Resnet v1 network architecture has some layers and ops that are not supported by TensorRT. Currently I'm not sure how to handle this, please give me some advice. Thank you a lot!!

@JerryJiaGit Hi, I have successed install tensorrt, but when I run the model, this mistake is raise:

 Can't find a device placement for the op!

my gpu is p100
tensorflow 1.12.0
tensorrt 5.0.2.6
python 3.5

Replacing your files directly with those of the facenet project can be using tensorrt to speed up facenet inference, right? I just started learning and I don't know if it's right.
And there is an error in line 401 of the facenet.py. Unresolved reference 'frozen_graph'
Another same error in line 410.
How to solve this problem?
Thanks in advance.

No runtime reducing with TensorRT5/CUDA10/cuDNN7.3 on Jetson Xavier.

L4T 4.1.1
TensorFlow 1.12.0
TensorRT 5.0.3

Can enabled TensorRT convert with same code, but there is no runtime reducing with TensorRT5/CUDA10/cuDNN7.3 on Jetson Xavier.

For inception-resnet v1 network saved model convert:
Original: 0.0428 s
TensorRT FP16: 0.04263 s

Will try x86 TRT5 and check with NVIDIA TRT team later.