ixrt

FCOS (ixRT)

Model Description

FCOS is an anchor-free model based on the Fully Convolutional Network (FCN) architecture for pixel-wise object detection. It implements a proposal-free solution and introduces the concept of centerness. For more details, please refer to our report on Arxiv.

Supported Environments

GPU	IXUCA SDK	Release	Branch
MR-V100	4.4.0	26.03	release/26.03
MR-V100	4.3.0	25.12	release/25.12

Note: 请切换到与您的 SDK 版本对应的 Release 分支进行测试。请勿直接在 master 分支上运行测试，因为 master 分支可能包含与您的本地 SDK 版本不兼容的最新更改。

切换分支命令示例：git checkout release/26.03

Model Preparation

Prepare Resources

Pretrained model: https://download.openmmlab.com/mmdetection/v2.0/fcos/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_1x_coco/fcos_center-normbbox-centeronreg-giou_r50_caffe_fpn_gn-head_1x_coco-0a0d75a8.pth

Dataset:

• https://github.com/ultralytics/assets/releases/download/v0.0.0/coco2017labels.zip to download the labels dataset.
• http://images.cocodataset.org/zips/val2017.zip to download the validation dataset.
• http://images.cocodataset.org/zips/train2017.zip to download the train dataset.

unzip -q -d ./ coco2017labels.zip
unzip -q -d ./coco/images/ train2017.zip
unzip -q -d ./coco/images/ val2017.zip

coco
├── annotations
│   └── instances_val2017.json
├── images
│   ├── train2017
│   └── val2017
├── labels
│   ├── train2017
│   └── val2017
├── LICENSE
├── README.txt
├── test-dev2017.txt
├── train2017.cache
├── train2017.txt
├── val2017.cache
└── val2017.txt

Install Dependencies

# Install libGL
## CentOS
yum install -y mesa-libGL
## Ubuntu
apt install -y libgl1-mesa-glx

pip3 install -r requirements.txt

Model Conversion

MMDetection is an open source object detection toolbox based on PyTorch. It is a part of the OpenMMLab project.It is utilized for model conversion. In MMDetection, Execute model conversion command, and the checkpoints folder needs to be created, (mkdir checkpoints) in project

mkdir -p checkpoints
cd checkpoints
wget http://files.deepspark.org.cn:880/deepspark/fcos_opt.onnx

Model Inference

export PROJ_DIR=./
export DATASETS_DIR=./coco/
export CHECKPOINTS_DIR=./checkpoints
export RUN_DIR=../../ixrt_common

FP16

# Accuracy
bash scripts/infer_fcos_fp16_accuracy.sh
# Performance
bash scripts/infer_fcos_fp16_performance.sh

Model Results

Model	BatchSize	Precision	FPS	MAP@0.5	MAP@0.5:0.95
FCOS	1	FP16	51.62	0.546	0.360