Fixed multipleInferences
Updated and fixed multipleInferences files
This commit is contained in:
Marcos Luciano
@@ -63,7 +63,7 @@ config-file=pgie/config_infer_primary.txt
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enable=1
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gpu-id=0
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gie-unique-id=2
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#operate-on-gie-id=1
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operate-on-gie-id=1
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#operate-on-class-ids=0
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nvbuf-memory-type=0
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config-file=sgie1/config_infer_secondary1.txt
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@@ -2,7 +2,7 @@
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gpu-id=0
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net-scale-factor=0.0039215697906911373
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model-color-format=0
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custom-network-config=yolo.cfg
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custom-network-config=pgie/yolo.cfg
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model-file=yolo.weights
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model-engine-file=model_b1_gpu0_fp16.engine
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labelfile-path=labels.txt
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@@ -0,0 +1,155 @@
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/*
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* Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a
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* copy of this software and associated documentation files (the "Software"),
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* to deal in the Software without restriction, including without limitation
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* the rights to use, copy, modify, merge, publish, distribute, sublicense,
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* and/or sell copies of the Software, and to permit persons to whom the
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* Software is furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
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* THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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* DEALINGS IN THE SOFTWARE.
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* Edited by Marcos Luciano
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* https://www.github.com/marcoslucianops
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*/
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#ifndef __YOLO_PLUGINS__
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#define __YOLO_PLUGINS__
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#include <cassert>
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#include <cstring>
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#include <cuda_runtime_api.h>
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#include <iostream>
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#include <memory>
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#include <vector>
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#include "NvInferPlugin.h"
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#define CHECK(status) \
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{ \
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if (status != 0) \
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{ \
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std::cout << "CUDA failure: " << cudaGetErrorString(status) << " in file " << __FILE__ \
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<< " at line " << __LINE__ << std::endl; \
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abort(); \
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} \
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}
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namespace
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{
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const char* YOLOLAYER_PLUGIN_VERSION {"1"};
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const char* YOLOLAYER_PLUGIN_NAME {"YoloLayer_TRT"};
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} // namespace
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class YoloLayer : public nvinfer1::IPluginV2
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{
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public:
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YoloLayer (const void* data, size_t length);
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YoloLayer (const uint& numBoxes, const uint& numClasses, const uint& gridSize,
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const uint model_type, const uint new_coords, const float scale_x_y, const float beta_nms,
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const std::vector<float> anchors, const std::vector<std::vector<int>> mask);
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const char* getPluginType () const override { return YOLOLAYER_PLUGIN_NAME; }
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const char* getPluginVersion () const override { return YOLOLAYER_PLUGIN_VERSION; }
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int getNbOutputs () const override { return 1; }
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nvinfer1::Dims getOutputDimensions (
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int index, const nvinfer1::Dims* inputs,
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int nbInputDims) override;
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bool supportsFormat (
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nvinfer1::DataType type, nvinfer1::PluginFormat format) const override;
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void configureWithFormat (
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const nvinfer1::Dims* inputDims, int nbInputs,
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const nvinfer1::Dims* outputDims, int nbOutputs,
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nvinfer1::DataType type, nvinfer1::PluginFormat format, int maxBatchSize) override;
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int initialize () override { return 0; }
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void terminate () override {}
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size_t getWorkspaceSize (int maxBatchSize) const override { return 0; }
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int enqueue (
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int batchSize, const void* const* inputs, void** outputs,
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void* workspace, cudaStream_t stream) override;
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size_t getSerializationSize() const override;
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void serialize (void* buffer) const override;
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void destroy () override { delete this; }
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nvinfer1::IPluginV2* clone() const override;
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void setPluginNamespace (const char* pluginNamespace)override {
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m_Namespace = pluginNamespace;
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}
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virtual const char* getPluginNamespace () const override {
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return m_Namespace.c_str();
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}
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private:
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uint m_NumBoxes {0};
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uint m_NumClasses {0};
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uint m_GridSize {0};
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uint64_t m_OutputSize {0};
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std::string m_Namespace {""};
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uint m_type {0};
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uint m_new_coords {0};
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float m_scale_x_y {0};
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float m_beta_nms {0};
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std::vector<float> m_Anchors;
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std::vector<std::vector<int>> m_Mask;
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};
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class YoloLayerPluginCreator : public nvinfer1::IPluginCreator
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{
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public:
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YoloLayerPluginCreator () {}
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~YoloLayerPluginCreator () {}
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const char* getPluginName () const override { return YOLOLAYER_PLUGIN_NAME; }
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const char* getPluginVersion () const override { return YOLOLAYER_PLUGIN_VERSION; }
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const nvinfer1::PluginFieldCollection* getFieldNames() override {
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std::cerr<< "YoloLayerPluginCreator::getFieldNames is not implemented" << std::endl;
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return nullptr;
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}
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nvinfer1::IPluginV2* createPlugin (
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const char* name, const nvinfer1::PluginFieldCollection* fc) override
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{
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std::cerr<< "YoloLayerPluginCreator::getFieldNames is not implemented";
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return nullptr;
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}
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nvinfer1::IPluginV2* deserializePlugin (
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const char* name, const void* serialData, size_t serialLength) override
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{
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std::cout << "Deserialize yoloLayer plugin: " << name << std::endl;
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return new YoloLayer(serialData, serialLength);
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}
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void setPluginNamespace(const char* libNamespace) override {
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m_Namespace = libNamespace;
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}
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const char* getPluginNamespace() const override {
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return m_Namespace.c_str();
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}
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private:
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std::string m_Namespace {""};
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};
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extern int kNUM_CLASSES;
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extern float kBETA_NMS;
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extern std::vector<float> kANCHORS;
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extern std::vector<std::vector<int>> kMASK;
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#endif // __YOLO_PLUGINS__
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@@ -2,9 +2,9 @@
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gpu-id=0
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net-scale-factor=0.0039215697906911373
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model-color-format=0
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custom-network-config=yolo.cfg
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custom-network-config=sgie1/yolo.cfg
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model-file=yolo.weights
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model-engine-file=model_b1_gpu0_fp16.engine
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model-engine-file=model_b16_gpu0_fp16.engine
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labelfile-path=labels.txt
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batch-size=16
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network-mode=2
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@@ -12,8 +12,6 @@ num-detected-classes=10
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interval=0
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gie-unique-id=2
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process-mode=2
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#operate-on-gie-id=1
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#operate-on-class-ids=0
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network-type=0
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cluster-mode=4
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maintain-aspect-ratio=0
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@@ -0,0 +1,155 @@
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/*
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* Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
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*
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* Permission is hereby granted, free of charge, to any person obtaining a
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* copy of this software and associated documentation files (the "Software"),
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* to deal in the Software without restriction, including without limitation
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* the rights to use, copy, modify, merge, publish, distribute, sublicense,
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* and/or sell copies of the Software, and to permit persons to whom the
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* Software is furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in
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* all copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
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* THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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* DEALINGS IN THE SOFTWARE.
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* Edited by Marcos Luciano
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* https://www.github.com/marcoslucianops
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*/
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#ifndef __YOLO_PLUGINS__
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#define __YOLO_PLUGINS__
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#include <cassert>
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#include <cstring>
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#include <cuda_runtime_api.h>
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#include <iostream>
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#include <memory>
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#include <vector>
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#include "NvInferPlugin.h"
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#define CHECK(status) \
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{ \
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if (status != 0) \
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{ \
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std::cout << "CUDA failure: " << cudaGetErrorString(status) << " in file " << __FILE__ \
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<< " at line " << __LINE__ << std::endl; \
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abort(); \
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} \
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}
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namespace
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{
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const char* YOLOLAYER_PLUGIN_VERSION {"2"};
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const char* YOLOLAYER_PLUGIN_NAME {"YoloLayer_TRT"};
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} // namespace
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class YoloLayer : public nvinfer1::IPluginV2
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{
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public:
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YoloLayer (const void* data, size_t length);
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YoloLayer (const uint& numBoxes, const uint& numClasses, const uint& gridSize,
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const uint model_type, const uint new_coords, const float scale_x_y, const float beta_nms,
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const std::vector<float> anchors, const std::vector<std::vector<int>> mask);
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const char* getPluginType () const override { return YOLOLAYER_PLUGIN_NAME; }
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const char* getPluginVersion () const override { return YOLOLAYER_PLUGIN_VERSION; }
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int getNbOutputs () const override { return 1; }
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nvinfer1::Dims getOutputDimensions (
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int index, const nvinfer1::Dims* inputs,
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int nbInputDims) override;
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bool supportsFormat (
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nvinfer1::DataType type, nvinfer1::PluginFormat format) const override;
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void configureWithFormat (
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const nvinfer1::Dims* inputDims, int nbInputs,
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const nvinfer1::Dims* outputDims, int nbOutputs,
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nvinfer1::DataType type, nvinfer1::PluginFormat format, int maxBatchSize) override;
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int initialize () override { return 0; }
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void terminate () override {}
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size_t getWorkspaceSize (int maxBatchSize) const override { return 0; }
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int enqueue (
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int batchSize, const void* const* inputs, void** outputs,
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void* workspace, cudaStream_t stream) override;
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size_t getSerializationSize() const override;
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void serialize (void* buffer) const override;
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void destroy () override { delete this; }
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nvinfer1::IPluginV2* clone() const override;
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void setPluginNamespace (const char* pluginNamespace)override {
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m_Namespace = pluginNamespace;
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}
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virtual const char* getPluginNamespace () const override {
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return m_Namespace.c_str();
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}
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private:
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uint m_NumBoxes {0};
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uint m_NumClasses {0};
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uint m_GridSize {0};
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uint64_t m_OutputSize {0};
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std::string m_Namespace {""};
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uint m_type {0};
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uint m_new_coords {0};
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float m_scale_x_y {0};
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float m_beta_nms {0};
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std::vector<float> m_Anchors;
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std::vector<std::vector<int>> m_Mask;
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};
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class YoloLayerPluginCreator : public nvinfer1::IPluginCreator
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{
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public:
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YoloLayerPluginCreator () {}
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~YoloLayerPluginCreator () {}
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const char* getPluginName () const override { return YOLOLAYER_PLUGIN_NAME; }
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const char* getPluginVersion () const override { return YOLOLAYER_PLUGIN_VERSION; }
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const nvinfer1::PluginFieldCollection* getFieldNames() override {
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std::cerr<< "YoloLayerPluginCreator::getFieldNames is not implemented" << std::endl;
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return nullptr;
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}
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nvinfer1::IPluginV2* createPlugin (
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const char* name, const nvinfer1::PluginFieldCollection* fc) override
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{
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std::cerr<< "YoloLayerPluginCreator::getFieldNames is not implemented";
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return nullptr;
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}
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nvinfer1::IPluginV2* deserializePlugin (
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const char* name, const void* serialData, size_t serialLength) override
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{
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std::cout << "Deserialize yoloLayer plugin: " << name << std::endl;
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return new YoloLayer(serialData, serialLength);
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}
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void setPluginNamespace(const char* libNamespace) override {
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m_Namespace = libNamespace;
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}
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const char* getPluginNamespace() const override {
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return m_Namespace.c_str();
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}
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private:
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std::string m_Namespace {""};
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};
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extern int kNUM_CLASSES;
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extern float kBETA_NMS;
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extern std::vector<float> kANCHORS;
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extern std::vector<std::vector<int>> kMASK;
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#endif // __YOLO_PLUGINS__
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@@ -27,6 +27,20 @@ CFLAGS+= -I../../../includes -I/usr/local/cuda-$(CUDA_VER)/include
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##
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### Editing yoloPlugins.h
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To run deepstream-app without errors is necessary to edit yoloPlugins.h (line 51), in nvdsinfer_custom_impl_Yolo folder in each secondary inference directory.
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```
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const char* YOLOLAYER_PLUGIN_VERSION {"1"};
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```
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To:
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```
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const char* YOLOLAYER_PLUGIN_VERSION {"2"};
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```
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Note: 2 = sgie1, 3 = sgie2, 4 = sgie3, etc
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##
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### Compiling edited models
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1. Check your CUDA version (nvcc --version)
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2. Go to inference directory.
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@@ -47,7 +61,6 @@ Example for 1 secondary-gie (2 inferences):
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enable=1
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gpu-id=0
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gie-unique-id=2
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# If you want secodary inference operate on specified GIE id (gie-unique-id you want to operate: 1, 2, etc; comment it if you don't want to use)
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operate-on-gie-id=1
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# If you want secodary inference operate on specified class ids of GIE (class ids you want to operate: 1, 1;2, 2;3;4, 3 etc; comment it if you don't want to use)
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operate-on-class-ids=0
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@@ -161,22 +174,6 @@ Example for all secondary:
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batch-size=16
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```
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##
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* If you want secodary inference operate on specified GIE id (gie-unique-id you want to operate: 1, 2, etc.)
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```
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operate-on-gie-id=1
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```
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##
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* If you want secodary inference operate on specified class ids of GIE (class ids you want to operate: 1, 1;2, 2;3;4, 3 etc.)
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```
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operate-on-class-ids=0
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```
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### Testing model
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To run your custom YOLO model, use this command
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Reference in New Issue
Block a user