TensorRT Version 7.0:
CUDA Version 10.2:
TensorFlow Version 1.14:
Hello everyone, I’m converting the model as the author of this article did and it works on the ssd_mobilenet_v1_coco_2018_01_28:
https://forums.developer.nvidia.com/t/sampleuffssd-with-custom-ssd-mobilenet-v1-model/70508
I retrained this model for one class and a resolution of 320 * 544 according to this article:
https://github.com/EdjeElectronics/TensorFlow-Object-Detection-API-Tutorial-Train-Multiple-Objects-Windows-10
changed config.py:
import graphsurgeon as gs
import tensorflow as tf
Input = gs.create_node("Input",
op="Placeholder",
dtype=tf.float32,
shape=[1, 3, 320, 544])
PriorBox = gs.create_plugin_node(name="GridAnchor", op="GridAnchor_TRT",
numLayers=6,
minSize=0.2,
maxSize=0.95,
aspectRatios=[1.0, 2.0, 0.5, 3.0, 0.33],
variance=[0.1,0.1,0.2,0.2],
featureMapShapes=[19, 10, 5, 3, 2, 1])
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=1,
inputOrder=[0, 2, 1],
confSigmoid=1,
isNormalized=1)
concat_priorbox = gs.create_node(name="concat_priorbox", op="ConcatV2", dtype=tf.float32, axis=2)
concat_box_loc = gs.create_plugin_node("concat_box_loc", op="FlattenConcat_TRT", dtype=tf.float32, axis=1, ignoreBatch=0)
concat_box_conf = gs.create_plugin_node("concat_box_conf", op="FlattenConcat_TRT", dtype=tf.float32, axis=1, ignoreBatch=0)
namespace_plugin_map = {
"MultipleGridAnchorGenerator": PriorBox,
"Postprocessor": NMS,
"Preprocessor": Input,
"ToFloat": Input,
"image_tensor:0": Input,
"MultipleGridAnchorGenerator/Concatenate": concat_priorbox,
"MultipleGridAnchorGenerator/Identity": concat_priorbox,
"concat": concat_box_loc,
"concat_1": concat_box_conf
}
namespace_remove = {
"ToFloat",
"image_tensor:0",
"Preprocessor/map/TensorArrayStack_1/TensorArrayGatherV3"
}
def preprocess(dynamic_graph):
# remove the unrelated or error layers
dynamic_graph.remove(dynamic_graph.find_nodes_by_path(namespace_remove), remove_exclusive_dependencies=False)
# Now create a new graph by collapsing namespaces
dynamic_graph.collapse_namespaces(namespace_plugin_map)
# Remove the outputs, so we just have a single output node (NMS).
dynamic_graph.remove(dynamic_graph.graph_outputs, remove_exclusive_dependencies=False)
and sampleUffSSD.cpp:
> …
std::vector<samplesCommon::PPM<3, 320, 544>> mPPMs; .. parser->registerInput(mParams.inputTensorNames[0].c_str(), DimsCHW(3,320,544), nvuffparser::UffInputOrder::kNCHW); .. const int imageC = 3; const int imageH = 320; const int imageW = 544; .. params.outputClsSize = 1; ..
Conversion to uff is successful, but when I run ./sample_uff_ssd I get this error:
./sample_uff_ssd &&&& RUNNING TensorRT.sample_uff_ssd # ./sample_uff_ssd [09/10/2020-19:23:57] [I] Building and running a GPU inference engine for SSD [09/10/2020-19:23:58] [E] [TRT] Parameter check failed at: ../builder/Layers.h::setAxis::367, condition: axis >= 0 [09/10/2020-19:23:58] [E] [TRT] Concatenate/concat: all concat input tensors must have the same dimensions except on the concatenation axis (0), but dimensions mismatched at input 1 at index 1. Input 0 shape: [2,7668,1], Input 1 shape: [2,4332,1] [09/10/2020-19:23:58] [E] [TRT] Concatenate/concat: all concat input tensors must have the same dimensions except on the concatenation axis (0), but dimensions mismatched at input 1 at index 1. Input 0 shape: [2,7668,1], Input 1 shape: [2,4332,1] [09/10/2020-19:23:58] [E] [TRT] Concatenate/concat: all concat input tensors must have the same dimensions except on the concatenation axis (0), but dimensions mismatched at input 1 at index 1. Input 0 shape: [2,7668,1], Input 1 shape: [2,4332,1] [09/10/2020-19:23:58] [E] [TRT] Concatenate/concat: all concat input tensors must have the same dimensions except on the concatenation axis (0), but dimensions mismatched at input 1 at index 1. Input 0 shape: [2,7668,1], Input 1 shape: [2,4332,1] [09/10/2020-19:23:58] [E] [TRT] Concatenate/concat: all concat input tensors must have the same dimensions except on the concatenation axis (0), but dimensions mismatched at input 1 at index 1. Input 0 shape: [2,7668,1], Input 1 shape: [2,4332,1] [09/10/2020-19:23:58] [E] [TRT] UffParser: Parser error: BoxPredictor_0/ClassPredictor/BiasAdd: The input to the Scale Layer is required to have a minimum of 3 dimensions. &&&& FAILED TensorRT.sample_uff_ssd # ./sample_uff_ssd
origin mobilnet model:
http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_coco_2018_01_28.tar.gz
my trained graph:
I didn’t work with neural networks at the layer level, so it is all very hard for me, can someone tell me what is wrong?