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PaddleDetection
未验证 提交 da0177b4 编写于 作者: G Guanghua Yu 提交者： GitHub
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fix avh demo (#6836)

上级 847c4c58
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Showing with 286 addition and 49 deletion
deploy/third_engine/demo_avh/.gitignore 0 → 100644
浏览文件 @ da0177b4
include/inputs.h
include/outputs.h
__pycache__/
build/
\ No newline at end of file
deploy/third_engine/demo_avh/Makefile
浏览文件 @ da0177b4
......@@ -81,13 +81,27 @@ ${BUILD_DIR}/libcmsis_startup.a: $(CMSIS_STARTUP_SRCS)
$(QUIET)$(AR) -cr $(abspath $(BUILD_DIR)/libcmsis_startup.a) $(abspath $(BUILD_DIR))/libcmsis_startup/*.o
$(QUIET)$(RANLIB) $(abspath $(BUILD_DIR)/libcmsis_startup.a)
CMSIS_SHA_FILE=${CMSIS_PATH}/977abe9849781a2e788b02282986480ff4e25ea6.sha
ifneq ("$(wildcard $(CMSIS_SHA_FILE))","")
${BUILD_DIR}/cmsis_nn/Source/libcmsis-nn.a:
$(QUIET)mkdir -p $(@D)
$(QUIET)cd $(CMSIS_PATH)/CMSIS/NN && $(CMAKE) -B $(abspath $(BUILD_DIR)/cmsis_nn) $(CMSIS_NN_CMAKE_FLAGS)
$(QUIET)cd $(abspath $(BUILD_DIR)/cmsis_nn) && $(MAKE) all
else
# Build CMSIS-NN
${BUILD_DIR}/cmsis_nn/Source/SoftmaxFunctions/libCMSISNNSoftmax.a:
$(QUIET)mkdir -p $(@D)
$(QUIET)cd $(CMSIS_PATH)/CMSIS/NN && $(CMAKE) -B $(abspath $(BUILD_DIR)/cmsis_nn) $(CMSIS_NN_CMAKE_FLAGS)
$(QUIET)cd $(abspath $(BUILD_DIR)/cmsis_nn) && $(MAKE) all
$(QUIET)cd $(abspath $(BUILD_DIR)/cmsis_nn) && $(MAKE) all
endif
# Build demo application
ifneq ("$(wildcard $(CMSIS_SHA_FILE))","")
$(BUILD_DIR)/demo: $(DEMO_MAIN) $(UART_SRCS) $(BUILD_DIR)/stack_allocator.o $(BUILD_DIR)/crt_backend_api.o \
${BUILD_DIR}/libcodegen.a ${BUILD_DIR}/libcmsis_startup.a ${BUILD_DIR}/cmsis_nn/Source/libcmsis-nn.a
$(QUIET)mkdir -p $(@D)
$(QUIET)$(CC) $(PKG_CFLAGS) $(FREERTOS_FLAGS) -o $@ -Wl,--whole-archive $^ -Wl,--no-whole-archive $(PKG_LDFLAGS)
else
$(BUILD_DIR)/demo: $(DEMO_MAIN) $(UART_SRCS) $(BUILD_DIR)/stack_allocator.o $(BUILD_DIR)/crt_backend_api.o \
${BUILD_DIR}/libcodegen.a ${BUILD_DIR}/libcmsis_startup.a \
${BUILD_DIR}/cmsis_nn/Source/SoftmaxFunctions/libCMSISNNSoftmax.a \
......@@ -102,6 +116,7 @@ $(BUILD_DIR)/demo: $(DEMO_MAIN) $(UART_SRCS) $(BUILD_DIR)/stack_allocator.o $(BU
${BUILD_DIR}/cmsis_nn/Source/PoolingFunctions/libCMSISNNPooling.a
$(QUIET)mkdir -p $(@D)
$(QUIET)$(CC) $(PKG_CFLAGS) $(FREERTOS_FLAGS) -o $@ -Wl,--whole-archive $^ -Wl,--no-whole-archive $(PKG_LDFLAGS)
endif
clean:
$(QUIET)rm -rf $(BUILD_DIR)/codegen
......
deploy/third_engine/demo_avh/README.md
浏览文件 @ da0177b4
......@@ -5,25 +5,30 @@
<!--- to you under the Apache License, Version 2.0 (the -->
<!--- "License"); you may not use this file except in compliance -->
<!--- with the License. You may obtain a copy of the License at -->
<!--- http://www.apache.org/licenses/LICENSE-2.0 -->
<!--- Unless required by applicable law or agreed to in writing, -->
<!--- software distributed under the License is distributed on an -->
<!--- "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY -->
<!--- KIND, either express or implied. See the License for the -->
<!--- specific language governing permissions and limitations -->
<!--- under the License. -->
Running PP-PicoDet via TVM on bare metal Arm(R) Cortex(R)-M55 CPU and CMSIS-NN
===============================================================
This folder contains an example of how to use TVM to run a PP-PicoDet model
on bare metal Cortex(R)-M55 CPU and CMSIS-NN.
Running PP-PicoDet object detection model on bare metal Arm(R) Cortex(R)-M55 CPU using Arm Virtual Hardware
======================================================================
This folder contains an example of how to run a PP-PicoDet model on bare metal [Cortex(R)-M55 CPU](https://www.arm.com/products/silicon-ip-cpu/cortex-m/cortex-m55) using [Arm Virtual Hardware](https://www.arm.com/products/development-tools/simulation/virtual-hardware).
Prerequisites
Running environment and prerequisites
-------------
If the demo is run in the ci_cpu Docker container provided with TVM, then the following
software will already be installed.
Case 1: If the demo is run in Arm Virtual Hardware Amazon Machine Image(AMI) instance hosted by [AWS](https://aws.amazon.com/marketplace/pp/prodview-urbpq7yo5va7g?sr=0-1&ref_=beagle&applicationId=AWSMPContessa)/[AWS China](https://awsmarketplace.amazonaws.cn/marketplace/pp/prodview-2y7nefntbmybu), the following software will be installed through [configure_avh.sh](./configure_avh.sh) script. It will install automatically when you run the application through [run_demo.sh](./run_demo.sh) script.
You can refer to this [guide](https://arm-software.github.io/AVH/main/examples/html/MicroSpeech.html#amilaunch) to launch an Arm Virtual Hardware AMI instance.
If the demo is not run in the ci_cpu Docker container, then you will need the following:
Case 2: If the demo is run in the [ci_cpu Docker container](https://github.com/apache/tvm/blob/main/docker/Dockerfile.ci_cpu) provided with [TVM](https://github.com/apache/tvm), then the following software will already be installed.
Case 3: If the demo is not run in the ci_cpu Docker container, then you will need the following:
- Software required to build and run the demo (These can all be installed by running
tvm/docker/install/ubuntu_install_ethosu_driver_stack.sh.)
- [Fixed Virtual Platform (FVP) based on Arm(R) Corstone(TM)-300 software](https://release/2.5er.arm.com/tools-and-software/open-source-software/arm-platforms-software/arm-ecosystem-fvps)
......@@ -37,26 +42,37 @@ If the demo is not run in the ci_cpu Docker container, then you will need the fo
pip install -r ./requirements.txt
```
In case2 and case3:
You will need to update your PATH environment variable to include the path to cmake 3.19.5 and the FVP.
For example if you've installed these in ```/opt/arm``` , then you would do the following:
```bash
export PATH=/opt/arm/FVP_Corstone_SSE-300/models/Linux64_GCC-6.4:/opt/arm/cmake/bin:$PATH
```
You will also need TVM which can either be:
- Installed from TLCPack(see [TLCPack](https://tlcpack.ai/))
- Built from source (see [Install from Source](https://tvm.apache.org/docs/install/from_source.html))
- When building from source, the following need to be set in config.cmake:
- set(USE_CMSISNN ON)
- set(USE_MICRO ON)
- set(USE_LLVM ON)
- Installed from TLCPack(see [TLCPack](https://tlcpack.ai/))
You will need to update your PATH environment variable to include the path to cmake 3.19.5 and the FVP.
For example if you've installed these in ```/opt/arm``` , then you would do the following:
```bash
export PATH=/opt/arm/FVP_Corstone_SSE-300/models/Linux64_GCC-6.4:/opt/arm/cmake/bin:$PATH
```
Running the demo application
----------------------------
Type the following command to run the bare metal text recognition application ([src/demo_bare_metal.c](./src/demo_bare_metal.c)):
```bash
./run_demo.sh
```
If you are not able to use Arm Virtual Hardware Amazon Machine Image(AMI) instance hosted by AWS/AWS China, specify argument --enable_FVP to 1 to make the application run on local Fixed Virtual Platforms (FVPs) executables.
```bash
./run_demo.sh --enable_FVP 1
```
If the Ethos(TM)-U platform and/or CMSIS have not been installed in /opt/arm/ethosu then
the locations for these can be specified as arguments to run_demo.sh, for example:
......@@ -65,13 +81,14 @@ the locations for these can be specified as arguments to run_demo.sh, for exampl
--ethosu_platform_path /home/tvm-user/ethosu/core_platform
```
This will:
- Download a PP-PicoDet text recognition model
With [run_demo.sh](./run_demo.sh) to run the demo application, it will:
- Set up running environment by installing the required prerequisites automatically if running in Arm Virtual Hardware Amazon AMI instance(not specify --enable_FVP to 1)
- Download a PP-PicoDet model
- Use tvmc to compile the text recognition model for Cortex(R)-M55 CPU and CMSIS-NN
- Create a C header file inputs.c containing the image data as a C array
- Create a C header file outputs.c containing a C array where the output of inference will be stored
- Build the demo application
- Run the demo application on a Fixed Virtual Platform (FVP) based on Arm(R) Corstone(TM)-300 software
- Run the demo application on a Arm Virtual Hardware based on Arm(R) Corstone(TM)-300 software
- The application will report the text on the image and the corresponding score.
Using your own image
......@@ -82,9 +99,9 @@ image to be converted into an array of bytes for consumption by the model.
The demo can be modified to use an image of your choice by changing the following line in run_demo.sh
```bash
python3 ./convert_image.py ../../demo/000000014439_640x640.jpg
python3 ./convert_image.py path/to/image
```
Model description
-----------------
In this demo, the model we used is based on [PP-PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/configs/picodet). Because of the excellent performance, PP-PicoDet are very suitable for deployment on mobile or CPU. And it is released by [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection).
In this demo, the model we used is based on [PP-PicoDet](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.5/configs/picodet). Because of the excellent performance, PP-PicoDet are very suitable for deployment on mobile or CPU. And it is released by [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection).
deploy/third_engine/demo_avh/README.md.bak 0 → 100644
浏览文件 @ da0177b4
<!--- Licensed to the Apache Software Foundation (ASF) under one -->
<!--- or more contributor license agreements. See the NOTICE file -->
<!--- distributed with this work for additional information -->
<!--- regarding copyright ownership. The ASF licenses this file -->
<!--- to you under the Apache License, Version 2.0 (the -->
<!--- "License"); you may not use this file except in compliance -->
<!--- with the License. You may obtain a copy of the License at -->
<!--- http://www.apache.org/licenses/LICENSE-2.0 -->
<!--- Unless required by applicable law or agreed to in writing, -->
<!--- software distributed under the License is distributed on an -->
<!--- "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY -->
<!--- KIND, either express or implied. See the License for the -->
<!--- specific language governing permissions and limitations -->
<!--- under the License. -->
Running PP-PicoDet via TVM on bare metal Arm(R) Cortex(R)-M55 CPU and CMSIS-NN
===============================================================
This folder contains an example of how to use TVM to run a PP-PicoDet model
on bare metal Cortex(R)-M55 CPU and CMSIS-NN.
Prerequisites
-------------
If the demo is run in the ci_cpu Docker container provided with TVM, then the following
software will already be installed.
If the demo is not run in the ci_cpu Docker container, then you will need the following:
- Software required to build and run the demo (These can all be installed by running
tvm/docker/install/ubuntu_install_ethosu_driver_stack.sh.)
- [Fixed Virtual Platform (FVP) based on Arm(R) Corstone(TM)-300 software](https://developer.arm.com/tools-and-software/open-source-software/arm-platforms-software/arm-ecosystem-fvps)
- [cmake 3.19.5](https://github.com/Kitware/CMake/releases/)
- [GCC toolchain from Arm(R)](https://developer.arm.com/-/media/Files/downloads/gnu-rm/10-2020q4/gcc-arm-none-eabi-10-2020-q4-major-x86_64-linux.tar.bz2)
- [Arm(R) Ethos(TM)-U NPU driver stack](https://review.mlplatform.org)
- [CMSIS](https://github.com/ARM-software/CMSIS_5)
- The python libraries listed in the requirements.txt of this directory
- These can be installed by running the following from the current directory:
```bash
pip install -r ./requirements.txt
```
You will also need TVM which can either be:
- Built from source (see [Install from Source](https://tvm.apache.org/docs/install/from_source.html))
- When building from source, the following need to be set in config.cmake:
- set(USE_CMSISNN ON)
- set(USE_MICRO ON)
- set(USE_LLVM ON)
- Installed from TLCPack(see [TLCPack](https://tlcpack.ai/))
You will need to update your PATH environment variable to include the path to cmake 3.19.5 and the FVP.
For example if you've installed these in ```/opt/arm``` , then you would do the following:
```bash
export PATH=/opt/arm/FVP_Corstone_SSE-300/models/Linux64_GCC-6.4:/opt/arm/cmake/bin:$PATH
```
Running the demo application
----------------------------
Type the following command to run the bare metal text recognition application ([src/demo_bare_metal.c](./src/demo_bare_metal.c)):
```bash
./run_demo.sh
```
If the Ethos(TM)-U platform and/or CMSIS have not been installed in /opt/arm/ethosu then
the locations for these can be specified as arguments to run_demo.sh, for example:
```bash
./run_demo.sh --cmsis_path /home/tvm-user/cmsis \
--ethosu_platform_path /home/tvm-user/ethosu/core_platform
```
This will:
- Download a PP-PicoDet text recognition model
- Use tvmc to compile the text recognition model for Cortex(R)-M55 CPU and CMSIS-NN
- Create a C header file inputs.c containing the image data as a C array
- Create a C header file outputs.c containing a C array where the output of inference will be stored
- Build the demo application
- Run the demo application on a Fixed Virtual Platform (FVP) based on Arm(R) Corstone(TM)-300 software
- The application will report the text on the image and the corresponding score.
Using your own image
--------------------
The create_image.py script takes a single argument on the command line which is the path of the
image to be converted into an array of bytes for consumption by the model.
The demo can be modified to use an image of your choice by changing the following line in run_demo.sh
```bash
python3 ./convert_image.py ../../demo/000000014439_640x640.jpg
```
Model description
-----------------
deploy/third_engine/demo_avh/configure_avh.sh 0 → 100755
浏览文件 @ da0177b4
#!/bin/bash
# Copyright (c) 2022 Arm Limited and Contributors. All rights reserved.
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
set -e
set -u
set -o pipefail
# Show usage
function show_usage() {
cat <<EOF
Usage: Set up running environment by installing the required prerequisites.
-h, --help
Display this help message.
EOF
}
if [ "$#" -eq 1 ] && [ "$1" == "--help" -o "$1" == "-h" ]; then
show_usage
exit 0
elif [ "$#" -ge 1 ]; then
show_usage
exit 1
fi
echo -e "\e[36mStart setting up running environment\e[0m"
# Install CMSIS
echo -e "\e[36mStart installing CMSIS\e[0m"
CMSIS_PATH="/opt/arm/ethosu/cmsis"
mkdir -p "${CMSIS_PATH}"
CMSIS_SHA="977abe9849781a2e788b02282986480ff4e25ea6"
CMSIS_SHASUM="86c88d9341439fbb78664f11f3f25bc9fda3cd7de89359324019a4d87d169939eea85b7fdbfa6ad03aa428c6b515ef2f8cd52299ce1959a5444d4ac305f934cc"
CMSIS_URL="http://github.com/ARM-software/CMSIS_5/archive/${CMSIS_SHA}.tar.gz"
DOWNLOAD_PATH="/tmp/${CMSIS_SHA}.tar.gz"
wget ${CMSIS_URL} -O "${DOWNLOAD_PATH}"
echo "$CMSIS_SHASUM" ${DOWNLOAD_PATH} | sha512sum -c
tar -xf "${DOWNLOAD_PATH}" -C "${CMSIS_PATH}" --strip-components=1
touch "${CMSIS_PATH}"/"${CMSIS_SHA}".sha
echo -e "\e[36mCMSIS Installation SUCCESS\e[0m"
# Install Arm(R) Ethos(TM)-U NPU driver stack
echo -e "\e[36mStart installing Arm(R) Ethos(TM)-U NPU driver stack\e[0m"
git clone "https://review.mlplatform.org/ml/ethos-u/ethos-u-core-platform" /opt/arm/ethosu/core_platform
cd /opt/arm/ethosu/core_platform
git checkout tags/"21.11"
echo -e "\e[36mArm(R) Ethos(TM)-U Core Platform Installation SUCCESS\e[0m"
# Install Arm(R) GNU Toolchain
echo -e "\e[36mStart installing Arm(R) GNU Toolchain\e[0m"
mkdir -p /opt/arm/gcc-arm-none-eabi
export gcc_arm_url='https://developer.arm.com/-/media/Files/downloads/gnu-rm/10-2020q4/gcc-arm-none-eabi-10-2020-q4-major-x86_64-linux.tar.bz2?revision=ca0cbf9c-9de2-491c-ac48-898b5bbc0443&la=en&hash=68760A8AE66026BCF99F05AC017A6A50C6FD832A'
curl --retry 64 -sSL ${gcc_arm_url} | tar -C /opt/arm/gcc-arm-none-eabi --strip-components=1 -jx
export PATH=/opt/arm/gcc-arm-none-eabi/bin:$PATH
arm-none-eabi-gcc --version
arm-none-eabi-g++ --version
echo -e "\e[36mArm(R) Arm(R) GNU Toolchain Installation SUCCESS\e[0m"
# Install TVM from TLCPack
echo -e "\e[36mStart installing TVM\e[0m"
pip install tlcpack-nightly -f https://tlcpack.ai/wheels
echo -e "\e[36mTVM Installation SUCCESS\e[0m"
\ No newline at end of file
deploy/third_engine/demo_avh/convert_image.py
浏览文件 @ da0177b4
......@@ -24,10 +24,10 @@ import math
from PIL import Image
import numpy as np
def resize_norm_img(img, image_shape, padding=True):
imgC, imgH, imgW = image_shape
img = cv2.resize(
img, (imgW, imgH), interpolation=cv2.INTER_LINEAR)
img = cv2.resize(img, (imgW, imgH), interpolation=cv2.INTER_LINEAR)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img = np.transpose(img, [2, 0, 1]) / 255
img = np.expand_dims(img, 0)
......@@ -47,9 +47,8 @@ def create_header_file(name, tensor_name, tensor_data, output_path):
raw_path = file_path.with_suffix(".h").resolve()
with open(raw_path, "a") as header_file:
header_file.write(
"\n"
+ f"const size_t {tensor_name}_len = {tensor_data.size};\n"
+ f'__attribute__((section(".data.tvm"), aligned(16))) float {tensor_name}[] = '
"\n" + f"const size_t {tensor_name}_len = {tensor_data.size};\n" +
f'__attribute__((section(".data.tvm"), aligned(16))) float {tensor_name}[] = '
)
header_file.write("{")
......@@ -66,14 +65,16 @@ def create_headers(image_name):
# Resize image to 32x320
img = cv2.imread(img_path)
img = resize_norm_img(img, [3,32,320])
img = resize_norm_img(img, [3, 32, 320])
img_data = img.astype("float32")
# # Add the batch dimension, as we are expecting 4-dimensional input: NCHW.
img_data = np.expand_dims(img_data, axis=0)
os.remove("./include/inputs.h")
os.remove("./include/outputs.h")
if os.path.exists("./include/inputs.h"):
os.remove("./include/inputs.h")
if os.path.exists("./include/outputs.h"):
os.remove("./include/outputs.h")
# Create input header file
create_header_file("inputs", "input", img_data, "./include")
# Create output header file
......@@ -82,15 +83,13 @@ def create_headers(image_name):
"outputs",
"output0",
output_data,
"./include",
)
"./include", )
output_data = np.zeros([170000], np.float)
create_header_file(
"outputs",
"output1",
output_data,
"./include",
)
"./include", )
if __name__ == "__main__":
......
deploy/third_engine/demo_avh/corstone300.ld
浏览文件 @ da0177b4
......@@ -247,10 +247,10 @@ SECTIONS
} > DTCM
.bss.NoInit :
.bss.noinit (NOLOAD):
{
. = ALIGN(16);
*(.bss.NoInit)
*(.bss.noinit.*)
. = ALIGN(16);
} > DDR AT > DDR
......
deploy/third_engine/demo_avh/run_demo.sh 100755 → 100644
浏览文件 @ da0177b4
......@@ -15,7 +15,6 @@
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
export PATH=/opt/arm/FVP_Corstone_SSE-300/models/Linux64_GCC-6.4:/opt/arm/cmake/bin:$PATH
set -e
set -u
set -o pipefail
......@@ -25,18 +24,28 @@ function show_usage() {
cat <<EOF
Usage: run_demo.sh
-h, --help
Display this help message.
Display this help message.
--cmsis_path CMSIS_PATH
Set path to CMSIS.
Set path to CMSIS.
--ethosu_platform_path ETHOSU_PLATFORM_PATH
Set path to Arm(R) Ethos(TM)-U core platform.
Set path to Arm(R) Ethos(TM)-U core platform.
--fvp_path FVP_PATH
Set path to FVP.
Set path to FVP.
--cmake_path
Set path to cmake.
Set path to cmake.
--enable_FVP
Set 1 to run application on local Fixed Virtual Platforms (FVPs) executables.
EOF
}
# Configure environment variables
FVP_enable=0
export PATH=/opt/arm/gcc-arm-none-eabi/bin:$PATH
# Install python libraries
echo -e "\e[36mInstall python libraries\e[0m"
sudo pip install -r ./requirements.txt
# Parse arguments
while (( $# )); do
case "$1" in
......@@ -92,6 +101,18 @@ while (( $# )); do
exit 1
fi
;;
--enable_FVP)
if [ $# -gt 1 ] && [ "$2" == "1" -o "$2" == "0" ];
then
FVP_enable="$2"
shift 2
else
echo 'ERROR: --enable_FVP requires a right argument 1 or 0' >&2
show_usage >&2
exit 1
fi
;;
-*|--*)
echo "Error: Unknown flag: $1" >&2
......@@ -101,6 +122,16 @@ while (( $# )); do
esac
done
# Choose running environment: cloud(default) or local environment
Platform="VHT_Corstone_SSE-300_Ethos-U55"
if [ $FVP_enable == "1" ]; then
Platform="FVP_Corstone_SSE-300_Ethos-U55"
echo -e "\e[36mRun application on local Fixed Virtual Platforms (FVPs)\e[0m"
else
if [ ! -d "/opt/arm/" ]; then
sudo ./configure_avh.sh
fi
fi
# Directories
script_dir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
......@@ -110,6 +141,11 @@ make cleanall
mkdir -p build
cd build
# Get PaddlePaddle inference model
echo -e "\e[36mDownload PaddlePaddle inference model\e[0m"
wget https://bj.bcebos.com/v1/paddledet/deploy/Inference/picodet_s_320_coco_lcnet_no_nms.tar
tar -xf picodet_s_320_coco_lcnet_no_nms.tar
# Compile model for Arm(R) Cortex(R)-M55 CPU and CMSIS-NN
# An alternative to using "python3 -m tvm.driver.tvmc" is to call
# "tvmc" directly once TVM has been pip installed.
......@@ -123,7 +159,7 @@ python3 -m tvm.driver.tvmc compile --target=cmsis-nn,c \
--pass-config tir.usmp.enable=1 \
--pass-config tir.usmp.algorithm=hill_climb \
--pass-config tir.disable_storage_rewrite=1 \
--pass-config tir.disable_vectorize=1 ../models/picodet_s_320_coco_lcnet_no_nms/model \
--pass-config tir.disable_vectorize=1 picodet_s_320_coco_lcnet_no_nms/model.pdmodel \
--output-format=mlf \
--model-format=paddle \
--module-name=picodet \
......@@ -131,21 +167,18 @@ python3 -m tvm.driver.tvmc compile --target=cmsis-nn,c \
--output=picodet.tar
tar -xf picodet.tar
# Create C header files
cd ..
python3 ./convert_image.py ../../demo/000000014439_640x640.jpg
python3 ./convert_image.py ./image/000000014439_640x640.jpg
# Build demo executable
echo "Build demo executable..."
cd ${script_dir}
echo ${script_dir}
make
echo "End build demo executable..."
# Run demo executable on the FVP
FVP_Corstone_SSE-300_Ethos-U55 -C cpu0.CFGDTCMSZ=15 \
# Run demo executable on the AVH
$Platform -C cpu0.CFGDTCMSZ=15 \
-C cpu0.CFGITCMSZ=15 -C mps3_board.uart0.out_file=\"-\" -C mps3_board.uart0.shutdown_tag=\"EXITTHESIM\" \
-C mps3_board.visualisation.disable-visualisation=1 -C mps3_board.telnetterminal0.start_telnet=0 \
-C mps3_board.telnetterminal1.start_telnet=0 -C mps3_board.telnetterminal2.start_telnet=0 -C mps3_board.telnetterminal5.start_telnet=0 \
./build/demo
./build/demo --stat
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