init

CMakeLists.txt

+cmake_minimum_required(VERSION 3.16)
+project(resnet)
+
+set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_CXX_COMPILER g++)
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++17 -pthread -g")
+add_definitions(-DUNICODE -D_UNICODE)
+add_definitions("-Wall")
+
+# find_package(OpenCV REQUIRED)
+# 头文件
+set(INCLUDE_PATH    
+    ${CMAKE_CURRENT_SOURCE_DIR}/include
+    /usr/local/include/opencv4
+    ${ROCM_PATH}/onnxruntime/include)
+include_directories(${INCLUDE_PATH})
+
+# 库文件
+set(LIB_PATH
+    ${ROCM_PATH}/onnxruntime/lib
+    /usr/local/lib    
+    $ENV{DTKROOT}/lib/
+)
+link_directories(${LIB_PATH})
+
+# 库文件链接
+set(LIB onnxruntime opencv_core opencv_imgproc opencv_highgui opencv_imgcodecs)
+link_libraries(${LIB})
+
+set(source_cpp  ${CMAKE_CURRENT_SOURCE_DIR}/src/resnet50.cpp
+                ${CMAKE_CURRENT_SOURCE_DIR}/src/Helpers.cpp)
+
+add_executable(resnet  ${source_cpp})
\ No newline at end of file

README.md

 # Resnet50_onnxruntime
 
+## 论文
+`Deep Residual Learning for Image Recognition`
+
+- https://arxiv.org/abs/1512.03385
+
+## 模型结构
+ResNet50模型包含了49个卷积层、一个全连接层。
+
+![ResNet50模型结构](./resource/1.png)
+
+## 算法原理
+ResNet50使用了多个具有残差连接的残差块来解决梯度消失或梯度爆炸问题，并使得网络可以向更深层发展。
+
+![算法原理](./resource/2.png)
+
+## 环境配置
+### Docker
+拉取镜像：
+```
+docker pull image.sourcefind.cn:5000/dcu/admin/base/custom:opencv49_ffmpeg4.2.1_ubuntu20.04-dtk24.04.2
+```
+
+## 数据集
+无
+
+## 推理
+### C++推理
+该cpp项目支持多batch，下面介绍cpp项目编译流程
+#### 构建工程
+```
+cd resnet50_ort
+mkdir build && cd build 
+cmake ../
+make
+```
+#### 执行程序
+```
+export ORT_ROCM_MULTITHRAED_ENABLE=1
+cd build 
+./resnet
+```
+
+## result
+输出结果为每个图像得分前五的类别标签
+![算法原理](./resource/3.jpg)
+
+
+## 应用场景
+### 算法类别
+`图像分类`
+
+### 热点应用行业
+`制造,政府,医疗,科研`
+
+## 源码仓库及问题反馈
+https://developer.sourcefind.cn/codes/change/resnet50_ort
+
+## 参考资料
+https://github.com/onnx/models/tree/main/vision/classification/resnet

include/Helpers.h

+#pragma once
+#include "opencv2/imgproc.hpp"
+
+class Helpers
+{
+public:
+	static std::vector<float> loadImage;
+	static std::vector<std::string> loadLabels;
+};
+

model.properties

+# 模型唯一标识
+modelCode = 1195
+# 模型名称
+modelName=resnet50_ort
+# 模型描述
+modelDescription=使用onnxruntime_cpp接口推理,支持多batch推理
+# 应用场景
+appScenario=制造,政府,医疗,科研
+# 框架类型
+frameType=onnxruntime

models/imagenet_classes.txt

+tench
+goldfish
+great_white_shark
+tiger_shark
+hammerhead
+electric_ray
+stingray
+cock
+hen
+ostrich
+brambling
+goldfinch
+house_finch
+junco
+indigo_bunting
+robin
+bulbul
+jay
+magpie
+chickadee
+water_ouzel
+kite
+bald_eagle
+vulture
+great_grey_owl
+European_fire_salamander
+common_newt
+eft
+spotted_salamander
+axolotl
+bullfrog
+tree_frog
+tailed_frog
+loggerhead
+leatherback_turtle
+mud_turtle
+terrapin
+box_turtle
+banded_gecko
+common_iguana
+American_chameleon
+whiptail
+agama
+frilled_lizard
+alligator_lizard
+Gila_monster
+green_lizard
+African_chameleon
+Komodo_dragon
+African_crocodile
+American_alligator
+triceratops
+thunder_snake
+ringneck_snake
+hognose_snake
+green_snake
+king_snake
+garter_snake
+water_snake
+vine_snake
+night_snake
+boa_constrictor
+rock_python
+Indian_cobra
+green_mamba
+sea_snake
+horned_viper
+diamondback
+sidewinder
+trilobite
+harvestman
+scorpion
+black_and_gold_garden_spider
+barn_spider
+garden_spider
+black_widow
+tarantula
+wolf_spider
+tick
+centipede
+black_grouse
+ptarmigan
+ruffed_grouse
+prairie_chicken
+peacock
+quail
+partridge
+African_grey
+macaw
+sulphur-crested_cockatoo
+lorikeet
+coucal
+bee_eater
+hornbill
+hummingbird
+jacamar
+toucan
+drake
+red-breasted_merganser
+goose
+black_swan
+tusker
+echidna
+platypus
+wallaby
+koala
+wombat
+jellyfish
+sea_anemone
+brain_coral
+flatworm
+nematode
+conch
+snail
+slug
+sea_slug
+chiton
+chambered_nautilus
+Dungeness_crab
+rock_crab
+fiddler_crab
+king_crab
+American_lobster
+spiny_lobster
+crayfish
+hermit_crab
+isopod
+white_stork
+black_stork
+spoonbill
+flamingo
+little_blue_heron
+American_egret
+bittern
+crane
+limpkin
+European_gallinule
+American_coot
+bustard
+ruddy_turnstone
+red-backed_sandpiper
+redshank
+dowitcher
+oystercatcher
+pelican
+king_penguin
+albatross
+grey_whale
+killer_whale
+dugong
+sea_lion
+Chihuahua
+Japanese_spaniel
+Maltese_dog
+Pekinese
+Shih-Tzu
+Blenheim_spaniel
+papillon
+toy_terrier
+Rhodesian_ridgeback
+Afghan_hound
+basset
+beagle
+bloodhound
+bluetick
+black-and-tan_coonhound
+Walker_hound
+English_foxhound
+redbone
+borzoi
+Irish_wolfhound
+Italian_greyhound
+whippet
+Ibizan_hound
+Norwegian_elkhound
+otterhound
+Saluki
+Scottish_deerhound
+Weimaraner
+Staffordshire_bullterrier
+American_Staffordshire_terrier
+Bedlington_terrier
+Border_terrier
+Kerry_blue_terrier
+Irish_terrier
+Norfolk_terrier
+Norwich_terrier
+Yorkshire_terrier
+wire-haired_fox_terrier
+Lakeland_terrier
+Sealyham_terrier
+Airedale
+cairn
+Australian_terrier
+Dandie_Dinmont
+Boston_bull
+miniature_schnauzer
+giant_schnauzer
+standard_schnauzer
+Scotch_terrier
+Tibetan_terrier
+silky_terrier
+soft-coated_wheaten_terrier
+West_Highland_white_terrier
+Lhasa
+flat-coated_retriever
+curly-coated_retriever
+golden_retriever
+Labrador_retriever
+Chesapeake_Bay_retriever
+German_short-haired_pointer
+vizsla
+English_setter
+Irish_setter
+Gordon_setter
+Brittany_spaniel
+clumber
+English_springer
+Welsh_springer_spaniel
+cocker_spaniel
+Sussex_spaniel
+Irish_water_spaniel
+kuvasz
+schipperke
+groenendael
+malinois
+briard
+kelpie
+komondor
+Old_English_sheepdog
+Shetland_sheepdog
+collie
+Border_collie
+Bouvier_des_Flandres
+Rottweiler
+German_shepherd
+Doberman
+miniature_pinscher
+Greater_Swiss_Mountain_dog
+Bernese_mountain_dog
+Appenzeller
+EntleBucher
+boxer
+bull_mastiff
+Tibetan_mastiff
+French_bulldog
+Great_Dane
+Saint_Bernard
+Eskimo_dog
+malamute
+Siberian_husky
+dalmatian
+affenpinscher
+basenji
+pug
+Leonberg
+Newfoundland
+Great_Pyrenees
+Samoyed
+Pomeranian
+chow
+keeshond
+Brabancon_griffon
+Pembroke
+Cardigan
+toy_poodle
+miniature_poodle
+standard_poodle
+Mexican_hairless
+timber_wolf
+white_wolf
+red_wolf
+coyote
+dingo
+dhole
+African_hunting_dog
+hyena
+red_fox
+kit_fox
+Arctic_fox
+grey_fox
+tabby
+tiger_cat
+Persian_cat
+Siamese_cat
+Egyptian_cat
+cougar
+lynx
+leopard
+snow_leopard
+jaguar
+lion
+tiger
+cheetah
+brown_bear
+American_black_bear
+ice_bear
+sloth_bear
+mongoose
+meerkat
+tiger_beetle
+ladybug
+ground_beetle
+long-horned_beetle
+leaf_beetle
+dung_beetle
+rhinoceros_beetle
+weevil
+fly
+bee
+ant
+grasshopper
+cricket
+walking_stick
+cockroach
+mantis
+cicada
+leafhopper
+lacewing
+dragonfly
+damselfly
+admiral
+ringlet
+monarch
+cabbage_butterfly
+sulphur_butterfly
+lycaenid
+starfish
+sea_urchin
+sea_cucumber
+wood_rabbit
+hare
+Angora
+hamster
+porcupine
+fox_squirrel
+marmot
+beaver
+guinea_pig
+sorrel
+zebra
+hog
+wild_boar
+warthog
+hippopotamus
+ox
+water_buffalo
+bison
+ram
+bighorn
+ibex
+hartebeest
+impala
+gazelle
+Arabian_camel
+llama
+weasel
+mink
+polecat
+black-footed_ferret
+otter
+skunk
+badger
+armadillo
+three-toed_sloth
+orangutan
+gorilla
+chimpanzee
+gibbon
+siamang
+guenon
+patas
+baboon
+macaque
+langur
+colobus
+proboscis_monkey
+marmoset
+capuchin
+howler_monkey
+titi
+spider_monkey
+squirrel_monkey
+Madagascar_cat
+indri
+Indian_elephant
+African_elephant
+lesser_panda
+giant_panda
+barracouta
+eel
+coho
+rock_beauty
+anemone_fish
+sturgeon
+gar
+lionfish
+puffer
+abacus
+abaya
+academic_gown
+accordion
+acoustic_guitar
+aircraft_carrier
+airliner
+airship
+altar
+ambulance
+amphibian
+analog_clock
+apiary
+apron
+ashcan
+assault_rifle
+backpack
+bakery
+balance_beam
+balloon
+ballpoint
+Band_Aid
+banjo
+bannister
+barbell
+barber_chair
+barbershop
+barn
+barometer
+barrel
+barrow
+baseball
+basketball
+bassinet
+bassoon
+bathing_cap
+bath_towel
+bathtub
+beach_wagon
+beacon
+beaker
+bearskin
+beer_bottle
+beer_glass
+bell_cote
+bib
+bicycle-built-for-two
+bikini
+binder
+binoculars
+birdhouse
+boathouse
+bobsled
+bolo_tie
+bonnet
+bookcase
+bookshop
+bottlecap
+bow
+bow_tie
+brass
+brassiere
+breakwater
+breastplate
+broom
+bucket
+buckle
+bulletproof_vest
+bullet_train
+butcher_shop
+cab
+caldron
+candle
+cannon
+canoe
+can_opener
+cardigan
+car_mirror
+carousel
+carpenter\s_kit
+carton
+car_wheel
+cash_machine
+cassette
+cassette_player
+castle
+catamaran
+CD_player
+cello
+cellular_telephone
+chain
+chainlink_fence
+chain_mail
+chain_saw
+chest
+chiffonier
+chime
+china_cabinet
+Christmas_stocking
+church
+cinema
+cleaver
+cliff_dwelling
+cloak
+clog
+cocktail_shaker
+coffee_mug
+coffeepot
+coil
+combination_lock
+computer_keyboard
+confectionery
+container_ship
+convertible
+corkscrew
+cornet
+cowboy_boot
+cowboy_hat
+cradle
+crane
+crash_helmet
+crate
+crib
+Crock_Pot
+croquet_ball
+crutch
+cuirass
+dam
+desk
+desktop_computer
+dial_telephone
+diaper
+digital_clock
+digital_watch
+dining_table
+dishrag
+dishwasher
+disk_brake
+dock
+dogsled
+dome
+doormat
+drilling_platform
+drum
+drumstick
+dumbbell
+Dutch_oven
+electric_fan
+electric_guitar
+electric_locomotive
+entertainment_center
+envelope
+espresso_maker
+face_powder
+feather_boa
+file
+fireboat
+fire_engine
+fire_screen
+flagpole
+flute
+folding_chair
+football_helmet
+forklift
+fountain
+fountain_pen
+four-poster
+freight_car
+French_horn
+frying_pan
+fur_coat
+garbage_truck
+gasmask
+gas_pump
+goblet
+go-kart
+golf_ball
+golfcart
+gondola
+gong
+gown
+grand_piano
+greenhouse
+grille
+grocery_store
+guillotine
+hair_slide
+hair_spray
+half_track
+hammer
+hamper
+hand_blower
+hand-held_computer
+handkerchief
+hard_disc
+harmonica
+harp
+harvester
+hatchet
+holster
+home_theater
+honeycomb
+hook
+hoopskirt
+horizontal_bar
+horse_cart
+hourglass
+iPod
+iron
+jack-o\-lantern
+jean
+jeep
+jersey
+jigsaw_puzzle
+jinrikisha
+joystick
+kimono
+knee_pad
+knot
+lab_coat
+ladle
+lampshade
+laptop
+lawn_mower
+lens_cap
+letter_opener
+library
+lifeboat
+lighter
+limousine
+liner
+lipstick
+Loafer
+lotion
+loudspeaker
+loupe
+lumbermill
+magnetic_compass
+mailbag
+mailbox
+maillot
+maillot
+manhole_cover
+maraca
+marimba
+mask
+matchstick
+maypole
+maze
+measuring_cup
+medicine_chest
+megalith
+microphone
+microwave
+military_uniform
+milk_can
+minibus
+miniskirt
+minivan
+missile
+mitten
+mixing_bowl
+mobile_home
+Model_T
+modem
+monastery
+monitor
+moped
+mortar
+mortarboard
+mosque
+mosquito_net
+motor_scooter
+mountain_bike
+mountain_tent
+mouse
+mousetrap
+moving_van
+muzzle
+nail
+neck_brace
+necklace
+nipple
+notebook
+obelisk
+oboe
+ocarina
+odometer
+oil_filter
+organ
+oscilloscope
+overskirt
+oxcart
+oxygen_mask
+packet
+paddle
+paddlewheel
+padlock
+paintbrush
+pajama
+palace
+panpipe
+paper_towel
+parachute
+parallel_bars
+park_bench
+parking_meter
+passenger_car
+patio
+pay-phone
+pedestal
+pencil_box
+pencil_sharpener
+perfume
+Petri_dish
+photocopier
+pick
+pickelhaube
+picket_fence
+pickup
+pier
+piggy_bank
+pill_bottle
+pillow
+ping-pong_ball
+pinwheel
+pirate
+pitcher
+plane
+planetarium
+plastic_bag
+plate_rack
+plow
+plunger
+Polaroid_camera
+pole
+police_van
+poncho
+pool_table
+pop_bottle
+pot
+potter\s_wheel
+power_drill
+prayer_rug
+printer
+prison
+projectile
+projector
+puck
+punching_bag
+purse
+quill
+quilt
+racer
+racket
+radiator
+radio
+radio_telescope
+rain_barrel
+recreational_vehicle
+reel
+reflex_camera
+refrigerator
+remote_control
+restaurant
+revolver
+rifle
+rocking_chair
+rotisserie
+rubber_eraser
+rugby_ball
+rule
+running_shoe
+safe
+safety_pin
+saltshaker
+sandal
+sarong
+sax
+scabbard
+scale
+school_bus
+schooner
+scoreboard
+screen
+screw
+screwdriver
+seat_belt
+sewing_machine
+shield
+shoe_shop
+shoji
+shopping_basket
+shopping_cart
+shovel
+shower_cap
+shower_curtain
+ski
+ski_mask
+sleeping_bag
+slide_rule
+sliding_door
+slot
+snorkel
+snowmobile
+snowplow
+soap_dispenser
+soccer_ball
+sock
+solar_dish
+sombrero
+soup_bowl
+space_bar
+space_heater
+space_shuttle
+spatula
+speedboat
+spider_web
+spindle
+sports_car
+spotlight
+stage
+steam_locomotive
+steel_arch_bridge
+steel_drum
+stethoscope
+stole
+stone_wall
+stopwatch
+stove
+strainer
+streetcar
+stretcher
+studio_couch
+stupa
+submarine
+suit
+sundial
+sunglass
+sunglasses
+sunscreen
+suspension_bridge
+swab
+sweatshirt
+swimming_trunks
+swing
+switch
+syringe
+table_lamp
+tank
+tape_player
+teapot
+teddy
+television
+tennis_ball
+thatch
+theater_curtain
+thimble
+thresher
+throne
+tile_roof
+toaster
+tobacco_shop
+toilet_seat
+torch
+totem_pole
+tow_truck
+toyshop
+tractor
+trailer_truck
+tray
+trench_coat
+tricycle
+trimaran
+tripod
+triumphal_arch
+trolleybus
+trombone
+tub
+turnstile
+typewriter_keyboard
+umbrella
+unicycle
+upright
+vacuum
+vase
+vault
+velvet
+vending_machine
+vestment
+viaduct
+violin
+volleyball
+waffle_iron
+wall_clock
+wallet
+wardrobe
+warplane
+washbasin
+washer
+water_bottle
+water_jug
+water_tower
+whiskey_jug
+whistle
+wig
+window_screen
+window_shade
+Windsor_tie
+wine_bottle
+wing
+wok
+wooden_spoon
+wool
+worm_fence
+wreck
+yawl
+yurt
+web_site
+comic_book
+crossword_puzzle
+street_sign
+traffic_light
+book_jacket
+menu
+plate
+guacamole
+consomme
+hot_pot
+trifle
+ice_cream
+ice_lolly
+French_loaf
+bagel
+pretzel
+cheeseburger
+hotdog
+mashed_potato
+head_cabbage
+broccoli
+cauliflower
+zucchini
+spaghetti_squash
+acorn_squash
+butternut_squash
+cucumber
+artichoke
+bell_pepper
+cardoon
+mushroom
+Granny_Smith
+strawberry
+orange
+lemon
+fig
+pineapple
+banana
+jackfruit
+custard_apple
+pomegranate
+hay
+carbonara
+chocolate_sauce
+dough
+meat_loaf
+pizza
+potpie
+burrito
+red_wine
+espresso
+cup
+eggnog
+alp
+bubble
+cliff
+coral_reef
+geyser
+lakeside
+promontory
+sandbar
+seashore
+valley
+volcano
+ballplayer
+groom
+scuba_diver
+rapeseed
+daisy
+yellow_lady\s_slipper
+corn
+acorn
+hip
+buckeye
+coral_fungus
+agaric
+gyromitra
+stinkhorn
+earthstar
+hen-of-the-woods
+bolete
+ear
+toilet_tissue
\ No newline at end of file

src/Helpers.cpp

+#include <filesystem>
+#include <fstream>
+#include <iostream>
+#include <array>
+#include "Helpers.h"
+#include<opencv2/core.hpp>
+#include<opencv2/highgui.hpp>
+#include<opencv2/imgproc.hpp>
+
+static std::vector<float> loadImage(const std::string& filename, int sizeX = 224, int sizeY = 224)
+{
+    cv::Mat image = cv::imread(filename);
+    if (image.empty()) {
+        std::cout << "No image found.";
+    }
+
+    // convert from BGR to RGB
+    cv::cvtColor(image, image, cv::COLOR_BGR2RGB);
+
+    // resize
+    cv::resize(image, image, cv::Size(sizeX, sizeY));
+
+    // reshape to 1D
+    image = image.reshape(1, 1);
+
+    // uint_8, [0, 255] -> float, [0, 1]
+    // Normalize number to between 0 and 1
+    // Convert to vector<float> from cv::Mat.
+    std::vector<float> vec;
+    image.convertTo(vec, CV_32FC1, 1. / 255);
+
+    // Transpose (Height, Width, Channel)(224,224,3) to (Chanel, Height, Width)(3,224,224)
+    std::vector<float> output;
+    for (size_t ch = 0; ch < 3; ++ch) {
+        for (size_t i = ch; i < vec.size(); i += 3) {
+            output.emplace_back(vec[i]);
+        }
+    }
+    return output;
+}
+
+static std::vector<std::string> loadLabels(const std::string& filename)
+{
+    std::vector<std::string> output;
+
+    std::ifstream file(filename);
+    if (file) {
+        std::string s;
+        while (getline(file, s)) {
+            output.emplace_back(s);
+        }
+        file.close();
+    }
+
+    return output;
+}
\ No newline at end of file

src/resnet50.cpp

+// OnnxRuntimeResNet.cpp : This file contains the 'main' function. Program execution begins and ends there.
+
+#include <onnxruntime_cxx_api.h>
+#include <iostream>
+#include <string.h>
+
+#include "Helpers.cpp"
+
+int main()
+{
+    Ort::Env env(ORT_LOGGING_LEVEL_ERROR, "resnet4multi_batch");
+    Ort::RunOptions runOptions;
+    Ort::Session session(nullptr);
+
+    constexpr int64_t Batchsize = 5;
+    constexpr int64_t numChannels = 3;
+    constexpr int64_t width = 224;
+    constexpr int64_t height = 224;
+    constexpr int64_t numClasses = 1000;
+    constexpr int64_t numInputElements = numChannels * height * width;
+    const std::string labelFile = "../models/imagenet_classes.txt";
+    auto modelPath = "../models/resnet50-v2-7.onnx";
+
+    //load labels
+    std::vector<std::string> labels = loadLabels(labelFile);
+    if (labels.empty()) {
+        std::cout << "Failed to load labels: " << labelFile << std::endl;
+        return 1;
+    }
+
+    std::string imagePath = "../images/";
+    std::string _strPattern = imagePath + "*.JPEG";  // test_images
+    std::vector<cv::String> filesVec;
+    cv::glob(_strPattern, filesVec);
+    std::vector<std::vector<float>> ImageBatch;
+    for (int i = 0; i < Batchsize; i++)
+    {
+        const std::vector<float> imageVec = loadImage(filesVec[i]);
+        if (imageVec.empty()) {
+            std::cout << "Failed to load image: " << filesVec[i] << std::endl;
+            return 1;
+        }
+        if (imageVec.size() != numInputElements) {
+
+            std::cout << "Invalid image format. Must be 224x224 RGB image." << std::endl;
+            return 1;
+        }
+        ImageBatch.push_back(imageVec);
+    }
+
+    // Use CUDA GPU
+    Ort::SessionOptions session_options;
+
+    OrtROCMProviderOptions options;
+    options.device_id = 0;
+    session_options.AppendExecutionProvider_ROCM(options);
+    session_options.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_EXTENDED);
+    //create session
+    session = Ort::Session(env, modelPath, session_options);
+
+    // Use CPU
+    //session = Ort::Session(env, modelPath, Ort::SessionOptions{ nullptr });
+
+
+    // Define shape
+    const std::array<int64_t, 4> inputShape = { Batchsize, numChannels, height, width };
+    const std::array<int64_t, 2> outputShape = { Batchsize, numClasses };
+
+
+
+    // Define array
+    std::vector<float> input(Batchsize * numInputElements);
+    std::vector<float> results(Batchsize * numClasses);
+
+    // Define Tensor
+    auto memory_info = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeCPU);
+    auto inputTensor = Ort::Value::CreateTensor<float>(memory_info, input.data(), input.size(), inputShape.data(), inputShape.size());
+    auto outputTensor = Ort::Value::CreateTensor<float>(memory_info, results.data(), results.size(), outputShape.data(), outputShape.size());
+
+    // Copy image data to input array
+    for (int i = 0; i < Batchsize; ++i) {
+        std::copy(ImageBatch[i].begin(), ImageBatch[i].end(), input.begin() + i * numInputElements);
+    }
+
+    // Define names
+    Ort::AllocatorWithDefaultOptions ort_alloc;
+    Ort::AllocatedStringPtr inputName = session.GetInputNameAllocated(0, ort_alloc);
+    Ort::AllocatedStringPtr outputName = session.GetOutputNameAllocated(0, ort_alloc);
+    const std::array<const char*, 1> inputNames = { inputName.get() };
+    const std::array<const char*, 1> outputNames = { outputName.get() };
+    inputName.release();
+    outputName.release();
+
+    // Run inference
+    try {
+        session.Run(runOptions, inputNames.data(), &inputTensor, 1, outputNames.data(), &outputTensor, 1);
+    }
+    catch (Ort::Exception& e) {
+        std::cout << e.what() << std::endl;
+        return 1;
+    }
+
+    // Sort results and show Top5 for each image in the batch
+    for (int b = 0; b < Batchsize; b++) {
+        std::vector<std::pair<size_t, float>> indexValuePairs;
+        for (size_t i = 0; i < numClasses; ++i) {
+            indexValuePairs.emplace_back(i, results[b * numClasses + i]);
+        }
+        std::sort(indexValuePairs.begin(), indexValuePairs.end(), [](const auto& lhs, const auto& rhs) { return lhs.second > rhs.second; });
+
+        std::cout << "Image " << b + 1 << "-" << filesVec[b] <<std::endl;
+        // Show Top5
+        for (size_t i = 0; i < 5; ++i) {
+            const auto& result = indexValuePairs[i];
+            std::cout << i + 1 << ": " << labels[result.first] << " " << result.second << std::endl;
+        }
+    }
+    return 0;
+}
\ No newline at end of file