Description
Hi there,
I followed tutorial(GitHub - AastaNV/TRT_object_detection: Python sample for referencing object detection model with TensorRT) in Jetson Nano and it worked well with ssd_mobilenet_v2_coco_2018_03_29 model.
but, it was not working with my own dataset(ssd mobilenet v2). → I trained one class(Face)
I am a beginner of Jetson Nano. Please provide a solution or tutorial to follow.
Thank you.
TRT_object_detection/config/model_ssd_mobilenet_v2_coco_2018_03_29.py
I modified path and numClasses.
#path = ‘model/ssd_mobilenet_v2_coco_2018_03_29/frozen_inference_graph.pb’
path = ‘/home/tn/ssd_mobilenet_v2_face/frozen_inference_graph.pb’
NMS = gs.create_plugin_node( name="NMS", op="NMS_TRT", shareLocation=1, varianceEncodedInTarget=0, backgroundLabelId=0, confidenceThreshold=1e-8, nmsThreshold=0.6, topK=100, keepTopK=100, numClasses=2, inputOrder=[1, 0, 2], confSigmoid=1, isNormalized=1 )
TRT_object_detection/main.py
I got an error here.
with trt.Builder(TRT_LOGGER) as builder, builder.create_network() as network, trt.UffParser() as parser: builder.max_workspace_size = 1 << 28 builder.max_batch_size = 1 builder.fp16_mode = True parser.register_input('Input', model.dims) parser.register_output('MarkOutput_0') parser.parse('tmp.uff', network) engine = builder.build_cuda_engine(network) ==> here buf = engine.serialize() with open(model.TRTbin, 'wb') as f: f.write(buf)
Error
tn@tn-desktop:~/TRT_object_detection$ python3 main.py maksssksksss0.png
2021-03-10 14:52:32.047116: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.10.2
WARNING:tensorflow:Deprecation warnings have been disabled. Set TF_ENABLE_DEPRECATION_WARNINGS=1 to re-enable them.
NOTE: UFF has been tested with TensorFlow 1.15.0.
WARNING: The version of TensorFlow installed on this system is not guaranteed to work with UFF.
UFF Version 0.6.9
=== Automatically deduced input nodes ===
[name: “Input”
op: “Placeholder”
attr {
key: “dtype”
value {
type: DT_FLOAT
}
}
attr {
key: “shape”
value {
shape {
dim {
size: 1
}
dim {
size: 3
}
dim {
size: 300
}
dim {
size: 300
}
}
}
}
]
=========================================
Using output node NMS
Converting to UFF graph
Warning: No conversion function registered for layer: NMS_TRT yet.
Converting NMS as custom op: NMS_TRT
WARNING:tensorflow:From /usr/lib/python3.6/dist-packages/uff/converters/tensorflow/converter.py:226: The name tf.AttrValue is deprecated. Please use tf.compat.v1.AttrValue instead.Warning: No conversion function registered for layer: FlattenConcat_TRT yet.
Converting concat_box_conf as custom op: FlattenConcat_TRT
Warning: No conversion function registered for layer: GridAnchor_TRT yet.
Converting GridAnchor as custom op: GridAnchor_TRT
Warning: No conversion function registered for layer: FlattenConcat_TRT yet.
Converting concat_box_loc as custom op: FlattenConcat_TRT
DEBUG [/usr/lib/python3.6/dist-packages/uff/converters/tensorflow/converter.py:143] Marking [‘NMS’] as outputs
No. nodes: 644
UFF Output written to tmp.uff
UFF Text Output written to tmp.pbtxt
[TensorRT] INFO: Some tactics do not have sufficient workspace memory to run. Increasing workspace size may increase performance, please check verbose output.
[TensorRT] INFO: Detected 1 inputs and 2 output network tensors.
> #assertionnmsPlugin.cpp,246
> Aborted (core dumped)
Environment
Jetpack Version: 4.5
TensorRT Version: 7.1.3
CUDA Version: 10.2
Python Version (if applicable): 3.6
TensorFlow Version (if applicable): 1.15
Relevant Files
model
TRT_object_detection
Jetpack Version 4.5 I modifed TRT_object_detection file.
Please include:
- Exact steps/commands to build your repro
- Exact steps/commands to run your repro
- Full traceback of errors encountered