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Revert "Fixed multipleInferences"

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This reverts commit c99e970199.
This commit is contained in:
Marcos Luciano
2020-12-31 01:20:02 -03:00
parent 665d2f55e7
commit dbf855490a
6 changed files with 149 additions and 36 deletions
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2
examples/multiple_inferences/deepstream_app_config.txt
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@@ -63,7 +63,7 @@ config-file=pgie/config_infer_primary.txt
enable=1
gpu-id=0
gie-unique-id=2
operate-on-gie-id=1
#operate-on-gie-id=1
#operate-on-class-ids=0
nvbuf-memory-type=0
config-file=sgie1/config_infer_secondary1.txt

8
examples/multiple_inferences/config_infer_primary.txt → examples/multiple_inferences/pgie/config_infer_primary.txt
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@@ -2,10 +2,10 @@
gpu-id=0
net-scale-factor=0.0039215697906911373
model-color-format=0
custom-network-config=yolo_pgie.cfg
model-file=yolo_pgie.weights
model-engine-file=pgie_b1_gpu0_fp16.engine
labelfile-path=labels_pgie.txt
custom-network-config=yolo.cfg
model-file=yolo.weights
model-engine-file=model_b1_gpu0_fp16.engine
labelfile-path=labels.txt
batch-size=1
network-mode=2
num-detected-classes=2

2
examples/multiple_inferences/nvdsinfer_custom_impl_Yolo/Makefile → examples/multiple_inferences/pgie/nvdsinfer_custom_impl_Yolo/Makefile
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@@ -31,7 +31,7 @@ CC:= g++
NVCC:=/usr/local/cuda-$(CUDA_VER)/bin/nvcc
CFLAGS:= -Wall -std=c++11 -shared -fPIC -Wno-error=deprecated-declarations
CFLAGS+= -I../../includes -I/usr/local/cuda-$(CUDA_VER)/include
CFLAGS+= -I../../../includes -I/usr/local/cuda-$(CUDA_VER)/include
LIBS:= -lnvinfer_plugin -lnvinfer -lnvparsers -L/usr/local/cuda-$(CUDA_VER)/lib64 -lcudart -lcublas -lstdc++fs
LFLAGS:= -shared -Wl,--start-group $(LIBS) -Wl,--end-group

10
examples/multiple_inferences/config_infer_secondary1.txt → examples/multiple_inferences/sgie1/config_infer_secondary1.txt
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@@ -2,16 +2,18 @@
gpu-id=0
net-scale-factor=0.0039215697906911373
model-color-format=0
custom-network-config=yolo_sgie1.cfg
model-file=yolo_sgie1.weights
model-engine-file=sgie1_b16_gpu0_fp16.engine
labelfile-path=labels_sgie1.txt
custom-network-config=yolo.cfg
model-file=yolo.weights
model-engine-file=model_b1_gpu0_fp16.engine
labelfile-path=labels.txt
batch-size=16
network-mode=2
num-detected-classes=10
interval=0
gie-unique-id=2
process-mode=2
#operate-on-gie-id=1
#operate-on-class-ids=0
network-type=0
cluster-mode=4
maintain-aspect-ratio=0

71
examples/multiple_inferences/sgie1/nvdsinfer_custom_impl_Yolo/Makefile Normal file
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@@ -0,0 +1,71 @@
################################################################################
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or sell copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
# DEALINGS IN THE SOFTWARE.
#
# Edited by Marcos Luciano
# https://www.github.com/marcoslucianops
################################################################################
CUDA_VER?=
ifeq ($(CUDA_VER),)
$(error "CUDA_VER is not set")
endif
CC:= g++
NVCC:=/usr/local/cuda-$(CUDA_VER)/bin/nvcc
CFLAGS:= -Wall -std=c++11 -shared -fPIC -Wno-error=deprecated-declarations
CFLAGS+= -I../../../includes -I/usr/local/cuda-$(CUDA_VER)/include
LIBS:= -lnvinfer_plugin -lnvinfer -lnvparsers -L/usr/local/cuda-$(CUDA_VER)/lib64 -lcudart -lcublas -lstdc++fs
LFLAGS:= -shared -Wl,--start-group $(LIBS) -Wl,--end-group
INCS:= $(wildcard *.h)
SRCFILES:= nvdsinfer_yolo_engine.cpp \
nvdsparsebbox_Yolo.cpp \
yoloPlugins.cpp \
layers/convolutional_layer.cpp \
layers/dropout_layer.cpp \
layers/shortcut_layer.cpp \
layers/route_layer.cpp \
layers/upsample_layer.cpp \
layers/maxpool_layer.cpp \
layers/activation_layer.cpp \
utils.cpp \
yolo.cpp \
yoloForward.cu
TARGET_LIB:= libnvdsinfer_custom_impl_Yolo.so
TARGET_OBJS:= $(SRCFILES:.cpp=.o)
TARGET_OBJS:= $(TARGET_OBJS:.cu=.o)
all: $(TARGET_LIB)
%.o: %.cpp $(INCS) Makefile
$(CC) -c -o $@ $(CFLAGS) $<
%.o: %.cu $(INCS) Makefile
$(NVCC) -c -o $@ --compiler-options '-fPIC' $<
$(TARGET_LIB) : $(TARGET_OBJS)
$(CC) -o $@ $(TARGET_OBJS) $(LFLAGS)
clean:
rm -rf $(TARGET_LIB)
rm -rf $(TARGET_OBJS)

92
multipleInferences.md
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@@ -4,44 +4,57 @@ How to use multiples GIE's on DeepStream
##
1. Download [my native folder](https://github.com/marcoslucianops/DeepStream-Yolo/tree/master/native), rename to yolo and move to your deepstream/sources folder.
2. Copy each obj.names to deepstream/sources/yolo directory, renaming file to labels_*.txt (* = pgie/sgie1/sgie2/etc), according to each inference type.
3. Copy each yolo.cfg and yolo.weights files to deepstream/sources/yolo directory, renaming files to yolo_*.cfg and yolo_*.weights (* = pgie/sgie1/sgie2/etc), according to each inference type.
4. Make a copy of config_infer_primary.txt file and rename it to config_infer_secondary*.txt (* = 1/2/3/etc), according to inference order.
5. Edit DeepStream for your custom model, according to each yolo_*.cfg (* = pgie/sgie1/sgie2/etc) file: https://github.com/marcoslucianops/DeepStream-Yolo/blob/master/customModels.md
2. Make a folder, in deepstream/sources/yolo directory, named pgie (where you will put files of primary inference).
3. Make a folder, for each secondary inference, in deepstream/sources/yolo directory, named sgie* (* = 1, 2, 3, etc.; depending on the number of secondary inferences; where you will put files of others inferences).
4. Copy and remane each obj.names file to labels.txt in each inference directory (pgie, sgie*), according each inference type.
5. Copy your yolo.cfg and yolo.weights files to each inference directory (pgie, sgie*), according each inference type.
6. Move nvdsinfer_custom_impl_Yolo folder and config_infer_primary.txt file to each inference directory (pgie, sgie*; for sgie's, rename config_infer_primary to config_infer_secondary*; * = 1, 2, 3, etc.)
7. Edit DeepStream for your custom model, according each yolo.cfg file: https://github.com/marcoslucianops/DeepStream-Yolo/blob/master/customModels.md
**In example folder, on this repository, have all example files to multiple YOLO inferences.**
##
### Editing Makefile
To compile nvdsinfer_custom_impl_Yolo without errors is necessary to edit Makefile (line 34), in nvdsinfer_custom_impl_Yolo folder in each inference directory.
```
CFLAGS+= -I../../includes -I/usr/local/cuda-$(CUDA_VER)/include
```
To:
```
CFLAGS+= -I../../../includes -I/usr/local/cuda-$(CUDA_VER)/include
```
##
### Compiling edited models
1. Check your CUDA version (nvcc --version)
2. Go to deepstream/sources/yolo directory.
2. Go to inference directory.
3. Type command (example for CUDA 10.2 version):
```
CUDA_VER=10.2 make -C nvdsinfer_custom_impl_Yolo
```
**Do this for each GIE!**
##
### Add secondary-gie to deepstream_app_config after primary-gie
Example for 1 secondary-gie (2 inferences):
```
[secondary-gie0]
enable=1
gpu-id=0
gie-unique-id=2
# 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)
operate-on-gie-id=1
# 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)
operate-on-class-ids=0
nvbuf-memory-type=0
config-file=config_infer_secondary1.txt
config-file=sgie1/config_infer_secondary1.txt
```
Example for 2 secondary-gie (3 inferences):
```
[secondary-gie0]
enable=1
@@ -50,7 +63,7 @@ gie-unique-id=2
operate-on-gie-id=1
operate-on-class-ids=0
nvbuf-memory-type=0
config-file=config_infer_secondary1.txt
config-file=sgie1/config_infer_secondary1.txt
[secondary-gie1]
enable=1
@@ -59,40 +72,51 @@ gie-unique-id=3
operate-on-gie-id=1
operate-on-class-ids=0
nvbuf-memory-type=0
config-file=config_infer_secondary2.txt
config-file=sgie2/config_infer_secondary2.txt
```
Note: remember to edit primary-gie
```
[primary-gie]
enable=1
gpu-id=0
gie-unique-id=1
nvbuf-memory-type=0
config-file=config_infer_primary.txt
```
to
```
[primary-gie]
enable=1
gpu-id=0
gie-unique-id=1
nvbuf-memory-type=0
config-file=pgie/config_infer_primary.txt
```
##
### Editing config_infer
* Edit config_infer (config_infer_primary, config_infer_secondary1, etc.) files
* Edit path of config (config_infer_primary, config_infer_secondary1, etc.) files
Example for primary
```
custom-network-config=yolo_pgie.cfg
model-file=yolo_pgie.weights
model-engine-file=pgie_b16_gpu0_fp16.engine
labelfile-path=labels_pgie.txt
custom-network-config=pgie/yolo.cfg
```
Example for secondary1
```
custom-network-config=yolo_sgie1.cfg
model-file=yolo_sgie1.weights
model-engine-file=sgie1_b16_gpu0_fp16.engine
labelfile-path=labels_sgie1.txt
custom-network-config=sgie1/yolo.cfg
```
Example for secondary2
```
custom-network-config=yolo_sgie2.cfg
model-file=yolo_sgie2.weights
model-engine-file=sgie2_b16_gpu0_fp16.engine
labelfile-path=labels_sgie2.txt
custom-network-config=sgie2/yolo.cfg
```
##
@@ -137,6 +161,22 @@ Example for all secondary:
batch-size=16
```
##
* If you want secodary inference operate on specified GIE id (gie-unique-id you want to operate: 1, 2, etc.)
```
operate-on-gie-id=1
```
##
* 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.)
```
operate-on-class-ids=0
```
### Testing model
To run your custom YOLO model, use this command
@@ -144,4 +184,4 @@ To run your custom YOLO model, use this command
deepstream-app -c deepstream_app_config.txt
```
** During test process, engine file will be generated. When engine build process is done, rename engine file according to each configured engine name pgie/sgie1/sgie2/etc) in config_infer file.
**During test process, engine file will be generated. When engine build process is done, move engine file to respective GIE folder (pgie, sgie1, etc.)**