8 Commits

Author SHA1 Message Date
Dimitrii Lopanov
7f94c3bdcc readme and minor 2020-10-16 12:52:56 +03:00
Dimitrii Lopanov
e5d170ef8b inital rest example 2020-10-16 12:14:06 +03:00
Dimitrii Lopanov
85730b925c move base example to its own folder 2020-10-16 11:02:59 +03:00
Dimitrii Lopanov
55221029de Merge pull request #13 from LdDl/install-darknet
makefile and minor
2020-10-16 10:58:46 +03:00
Dimitrii Lopanov
e0a6735667 makefile and minor 2020-10-16 10:15:18 +03:00
Dimitrii
c9bbd3eee4 update darknet latest commit 2020-10-15 19:58:08 +03:00
Dimitrii Lopanov
5539377f1c Merge pull request #11 from LdDl/add-license-2
Create LICENSE
2020-10-15 17:22:26 +03:00
Dimitrii Lopanov
10cd5f6e1a Update issue templates 2020-10-15 17:22:14 +03:00
8 changed files with 551 additions and 98 deletions

26
.github/ISSUE_TEMPLATE/bug_report.md vendored Normal file
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@@ -0,0 +1,26 @@
---
name: Bug report
about: Create a report to help us improve
title: "[BUG]"
labels: bug, help wanted
assignees: LdDl
---
**Describe the bug**
A clear and concise description of what the bug is.
**To Reproduce**
Steps to reproduce the behavior
**Expected behavior**
A clear and concise description of what you expected to happen.
**Expected behavior**
A clear and concise description of what you expected to happen.
**Describe the solution you'd like and provide pseudocode examples if you can**
A clear and concise description of what you want to happen.
**Additional context**
Add any other context about the problem here.

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@@ -0,0 +1,20 @@
---
name: Feature request
about: Suggest an idea for this project
title: "[FEATURE REQUEST]"
labels: enhancement
assignees: LdDl
---
**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
**Describe the solution you'd like and provide pseudocode examples if you can**
A clear and concise description of what you want to happen.
**Describe alternatives you've considered and provide pseudocode examples if you can**
A clear and concise description of any alternative solutions or features you've considered.
**Additional context**
Add any other context or screenshots about the feature request here.

55
Makefile Normal file
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.ONESHELL:
.PHONY: download build clean
# Latest battletested AlexeyAB version of Darknet commit
LATEST_COMMIT?=d65909fbea471d06e52a2e4a41132380dc2edaa6
# Temporary folder for building Darknet
TMP_DIR?=/tmp/
# Download AlexeyAB version of Darknet
download:
rm -rf $(TMP_DIR)install_darknet
mkdir $(TMP_DIR)install_darknet
git clone https://github.com/AlexeyAB/darknet.git $(TMP_DIR)install_darknet
cd $(TMP_DIR)install_darknet
git checkout $(LATEST_COMMIT)
cd -
# Build AlexeyAB version of Darknet for usage with CPU only.
build:
cd $(TMP_DIR)install_darknet
sed -i -e 's/GPU=1/GPU=0/g' Makefile
sed -i -e 's/CUDNN=1/CUDNN=0/g' Makefile
sed -i -e 's/LIBSO=0/LIBSO=1/g' Makefile
$(MAKE) -j $(shell nproc --all)
$(MAKE) preinstall
cd -
# Build AlexeyAB version of Darknet for usage with both CPU and GPU (CUDA by NVIDIA).
build_gpu:
cd $(TMP_DIR)install_darknet
sed -i -e 's/GPU=0/GPU=1/g' Makefile
sed -i -e 's/CUDNN=0/CUDNN=1/g' Makefile
sed -i -e 's/LIBSO=0/LIBSO=1/g' Makefile
$(MAKE) -j $(shell nproc --all)
$(MAKE) preinstall
cd -
# Install system wide.
sudo_install:
cd $(TMP_DIR)install_darknet
sudo cp libdarknet.so /usr/lib/libdarknet.so
sudo cp include/darknet.h /usr/include/darknet.h
sudo ldconfig
cd -
# Cleanup temporary files for building process
clean:
rm -rf $(TMP_DIR)install_darknet
# Do every step for CPU-based only build.
install: download build sudo_install clean
# Do every step for both CPU and GPU-based build.
install_gpu: download build_gpu sudo_install clean

183
README.md
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@@ -3,7 +3,6 @@
[![Go Report Card](https://goreportcard.com/badge/github.com/LdDl/go-darknet)](https://goreportcard.com/report/github.com/LdDl/go-darknet)
[![GitHub tag](https://img.shields.io/github/tag/LdDl/go-darknet.svg)](https://github.com/LdDl/go-darknet/releases)
# go-darknet: Go bindings for Darknet (Yolo V4, Yolo V3)
### go-darknet is a Go package, which uses Cgo to enable Go applications to use YOLO V4/V3 in [Darknet].
@@ -23,29 +22,20 @@
## Requirements
For proper codebase please use fork of [darknet](https://github.com/AlexeyAB/darknet). Latest commit I've tested [here](https://github.com/AlexeyAB/darknet/commit/9dc897d2c77d5ef43a6b237b717437375765b527)
You need to install fork of [darknet](https://github.com/AlexeyAB/darknet). Latest commit I've tested is [here](https://github.com/AlexeyAB/darknet/commit/d65909fbea471d06e52a2e4a41132380dc2edaa6)
In order to use go-darknet, `libdarknet.so` should be available in one of
the following locations:
Use provided [Makefile](Makefile).
* /usr/lib
* /usr/local/lib
* For CPU-based instalattion:
```shell
make install
```
* For both CPU and GPU-based instalattion:
```shell
make install_gpu
```
Note: If you want to have GPU-acceleration before running command above install [CUDA](https://developer.nvidia.com/cuda-downloads) and [cuDNN](https://developer.nvidia.com/cudnn) (Latest CUDA version I've tested is [10.2](https://developer.nvidia.com/cuda-10.2-download-archive) and cuDNN is [7.6.5](https://developer.nvidia.com/rdp/cudnn-archive#a-collapse765-102))
Also, [darknet.h] should be available in one of the following locations:
* /usr/include
* /usr/local/include
To achieve it, after Darknet compilation (via make) execute following command:
```shell
# Copy *.so to /usr/lib + /usr/include (or /usr/local/lib + /usr/local/include)
sudo cp libdarknet.so /usr/lib/libdarknet.so && sudo cp include/darknet.h /usr/include/darknet.h
# sudo cp libdarknet.so /usr/local/lib/libdarknet.so && sudo cp include/darknet.h /usr/local/include/darknet.h
```
Note: do not forget to set LIBSO=1 in Makefile before executing 'make':
```Makefile
LIBSO=1
```
## Installation
```shell
@@ -58,87 +48,88 @@ Example Go program is provided in the [example] directory. Please refer to the c
Building and running program:
Navigate to [example] folder
```shell
cd $GOPATH/github.com/LdDl/go-darknet/example
```
* Navigate to [example] folder
```shell
cd $GOPATH/github.com/LdDl/go-darknet/example/base_example
```
Download dataset (sample of image, coco.names, yolov4.cfg (or v3), yolov4.weights(or v3)).
```shell
#for yolo v4
./download_data.sh
#for yolo v3
./download_data_v3.sh
```
Note: you don't need *coco.data* file anymore, because sh-script above does insert *coco.names* into 'names' field in *yolov4.cfg* file (so AlexeyAB's fork can deal with it properly)
So last rows in yolov4.cfg file will look like:
```bash
......
[yolo]
.....
iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6
* Download dataset (sample of image, coco.names, yolov4.cfg (or v3), yolov4.weights(or v3)).
```shell
#for yolo v4
./download_data.sh
#for yolo v3
./download_data_v3.sh
```
* Note: you don't need *coco.data* file anymore, because sh-script above does insert *coco.names* into 'names' field in *yolov4.cfg* file (so AlexeyAB's fork can deal with it properly)
So last rows in yolov4.cfg file will look like:
```bash
......
[yolo]
.....
iou_loss=ciou
nms_kind=greedynms
beta_nms=0.6
names = coco.names # this is path to coco.names file
```
Also do not forget change batch and subdivisions sizes from:
```shell
batch=64
subdivisions=8
```
to
```shell
batch=1
subdivisions=1
```
It will reduce amount of VRAM used for detector test.
names = coco.names # this is path to coco.names file
```
* Also do not forget change batch and subdivisions sizes from:
```shell
batch=64
subdivisions=8
```
to
```shell
batch=1
subdivisions=1
```
It will reduce amount of VRAM used for detector test.
Build and run program
Yolo V4:
```shell
go build main.go && ./main --configFile=yolov4.cfg --weightsFile=yolov4.weights --imageFile=sample.jpg
```
* Build and run program
Yolo V4:
```shell
go build main.go && ./main --configFile=yolov4.cfg --weightsFile=yolov4.weights --imageFile=sample.jpg
```
Output should be something like this:
```shell
traffic light (9): 73.5039% | start point: (238,73) | end point: (251, 106)
truck (7): 96.6401% | start point: (95,79) | end point: (233, 287)
truck (7): 96.4774% | start point: (662,158) | end point: (800, 321)
truck (7): 96.1841% | start point: (0,77) | end point: (86, 333)
truck (7): 46.8695% | start point: (434,173) | end point: (559, 216)
car (2): 99.7370% | start point: (512,188) | end point: (741, 329)
car (2): 99.2533% | start point: (260,191) | end point: (422, 322)
car (2): 99.0333% | start point: (425,201) | end point: (547, 309)
car (2): 83.3919% | start point: (386,210) | end point: (437, 287)
car (2): 75.8621% | start point: (73,199) | end point: (102, 274)
car (2): 39.1925% | start point: (386,206) | end point: (442, 240)
bicycle (1): 76.3121% | start point: (189,298) | end point: (253, 402)
person (0): 97.7213% | start point: (141,129) | end point: (283, 362)
```
Output should be something like this:
```shell
traffic light (9): 73.5039% | start point: (238,73) | end point: (251, 106)
truck (7): 96.6401% | start point: (95,79) | end point: (233, 287)
truck (7): 96.4774% | start point: (662,158) | end point: (800, 321)
truck (7): 96.1841% | start point: (0,77) | end point: (86, 333)
truck (7): 46.8695% | start point: (434,173) | end point: (559, 216)
car (2): 99.7370% | start point: (512,188) | end point: (741, 329)
car (2): 99.2533% | start point: (260,191) | end point: (422, 322)
car (2): 99.0333% | start point: (425,201) | end point: (547, 309)
car (2): 83.3919% | start point: (386,210) | end point: (437, 287)
car (2): 75.8621% | start point: (73,199) | end point: (102, 274)
car (2): 39.1925% | start point: (386,206) | end point: (442, 240)
bicycle (1): 76.3121% | start point: (189,298) | end point: (253, 402)
person (0): 97.7213% | start point: (141,129) | end point: (283, 362)
```
Yolo V3:
```
go build main.go && ./main --configFile=yolov3.cfg --weightsFile=yolov3.weights --imageFile=sample.jpg
```
Yolo V3:
```
go build main.go && ./main --configFile=yolov3.cfg --weightsFile=yolov3.weights --imageFile=sample.jpg
```
Output should be something like this:
```shell
truck (7): 49.5197% | start point: (0,136) | end point: (85, 311)
car (2): 36.3747% | start point: (95,152) | end point: (186, 283)
truck (7): 48.4384% | start point: (95,152) | end point: (186, 283)
truck (7): 45.6590% | start point: (694,178) | end point: (798, 310)
car (2): 76.8379% | start point: (1,145) | end point: (84, 324)
truck (7): 25.5731% | start point: (107,89) | end point: (215, 263)
car (2): 99.8783% | start point: (511,185) | end point: (748, 328)
car (2): 99.8194% | start point: (261,189) | end point: (427, 322)
car (2): 99.6408% | start point: (426,197) | end point: (539, 311)
car (2): 74.5610% | start point: (692,186) | end point: (796, 316)
car (2): 72.8053% | start point: (388,206) | end point: (437, 276)
bicycle (1): 72.2932% | start point: (178,270) | end point: (268, 406)
person (0): 97.3026% | start point: (143,135) | end point: (268, 343)
```
Output should be something like this:
```shell
truck (7): 49.5197% | start point: (0,136) | end point: (85, 311)
car (2): 36.3747% | start point: (95,152) | end point: (186, 283)
truck (7): 48.4384% | start point: (95,152) | end point: (186, 283)
truck (7): 45.6590% | start point: (694,178) | end point: (798, 310)
car (2): 76.8379% | start point: (1,145) | end point: (84, 324)
truck (7): 25.5731% | start point: (107,89) | end point: (215, 263)
car (2): 99.8783% | start point: (511,185) | end point: (748, 328)
car (2): 99.8194% | start point: (261,189) | end point: (427, 322)
car (2): 99.6408% | start point: (426,197) | end point: (539, 311)
car (2): 74.5610% | start point: (692,186) | end point: (796, 316)
car (2): 72.8053% | start point: (388,206) | end point: (437, 276)
bicycle (1): 72.2932% | start point: (178,270) | end point: (268, 406)
person (0): 97.3026% | start point: (143,135) | end point: (268, 343)
```
## Documentation
@@ -154,5 +145,5 @@ go-darknet follows [Darknet]'s [license].
[darknet.h]: https://github.com/AlexeyAB/darknet/blob/master/include/darknet.h
[include/darknet.h]: https://github.com/AlexeyAB/darknet/blob/master/include/darknet.h
[Makefile]: https://github.com/alexeyab/darknet/blob/master/Makefile
[example]: /example
[example]: /example/base_example
[GoDoc]: https://godoc.org/github.com/LdDl/go-darknet

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@@ -8,12 +8,12 @@ This is an example Go application which uses go-darknet.
Navigate to example folder:
```shell
cd $GOPATH/github.com/LdDl/go-darknet/example
cd $GOPATH/github.com/LdDl/go-darknet/example/base_example
```
Download dataset (sample of image, coco.names, yolov3.cfg, yolov3.weights).
```shell
./download_data.sh
./download_data_v3.sh
```
Note: you don't need *coco.data* file anymore, because script below does insert *coco.names* into 'names' filed in *yolov3.cfg* file (so AlexeyAB's fork can deal with it properly)
So last rows in yolov3.cfg file will look like:

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@@ -0,0 +1,221 @@
# Example Go application using go-darknet and REST
This is an example Go server application (in terms of REST) which uses go-darknet.
## Run
Navigate to example folder:
```shell
cd $GOPATH/github.com/LdDl/go-darknet/example/rest_example
```
Download dataset (sample of image, coco.names, yolov3.cfg, yolov3.weights).
```shell
./download_data_v3.sh
```
Note: you don't need *coco.data* file anymore, because script below does insert *coco.names* into 'names' filed in *yolov3.cfg* file (so AlexeyAB's fork can deal with it properly)
So last rows in yolov3.cfg file will look like:
```bash
......
[yolo]
mask = 0,1,2
anchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326
classes=80
num=9
jitter=.3
ignore_thresh = .7
truth_thresh = 1
random=1
names = coco.names # this is path to coco.names file
```
Build and run program
```
go build main.go && ./main --configFile=yolov3.cfg --weightsFile=yolov3.weights --port 8090
```
After server started check if REST-requests works. We provide cURL-based example
```shell
curl -F 'image=@sample.jpg' 'http://localhost:8090/detect_objects'
```
Servers response should be something like this:
```json
{
"net_time": "43.269289ms",
"overall_time": "43.551604ms",
"num_detections": 44,
"detections": [
{
"class_id": 7,
"class_name": "truck",
"probability": 49.51231,
"start_point": {
"x": 0,
"y": 136
},
"end_point": {
"x": 85,
"y": 311
}
},
{
"class_id": 2,
"class_name": "car",
"probability": 36.36933,
"start_point": {
"x": 95,
"y": 152
},
"end_point": {
"x": 186,
"y": 283
}
},
{
"class_id": 7,
"class_name": "truck",
"probability": 48.417683,
"start_point": {
"x": 95,
"y": 152
},
"end_point": {
"x": 186,
"y": 283
}
},
{
"class_id": 7,
"class_name": "truck",
"probability": 45.652023,
"start_point": {
"x": 694,
"y": 178
},
"end_point": {
"x": 798,
"y": 310
}
},
{
"class_id": 2,
"class_name": "car",
"probability": 76.8402,
"start_point": {
"x": 1,
"y": 145
},
"end_point": {
"x": 84,
"y": 324
}
},
{
"class_id": 7,
"class_name": "truck",
"probability": 25.592052,
"start_point": {
"x": 107,
"y": 89
},
"end_point": {
"x": 215,
"y": 263
}
},
{
"class_id": 2,
"class_name": "car",
"probability": 99.87823,
"start_point": {
"x": 511,
"y": 185
},
"end_point": {
"x": 748,
"y": 328
}
},
{
"class_id": 2,
"class_name": "car",
"probability": 99.819336,
"start_point": {
"x": 261,
"y": 189
},
"end_point": {
"x": 427,
"y": 322
}
},
{
"class_id": 2,
"class_name": "car",
"probability": 99.64055,
"start_point": {
"x": 426,
"y": 197
},
"end_point": {
"x": 539,
"y": 311
}
},
{
"class_id": 2,
"class_name": "car",
"probability": 74.56263,
"start_point": {
"x": 692,
"y": 186
},
"end_point": {
"x": 796,
"y": 316
}
},
{
"class_id": 2,
"class_name": "car",
"probability": 72.79756,
"start_point": {
"x": 388,
"y": 206
},
"end_point": {
"x": 437,
"y": 276
}
},
{
"class_id": 1,
"class_name": "bicycle",
"probability": 72.27595,
"start_point": {
"x": 178,
"y": 270
},
"end_point": {
"x": 268,
"y": 406
}
},
{
"class_id": 0,
"class_name": "person",
"probability": 97.30075,
"start_point": {
"x": 143,
"y": 135
},
"end_point": {
"x": 268,
"y": 343
}
}
]
}
```

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@@ -0,0 +1,140 @@
package main
import (
"bytes"
"encoding/json"
"flag"
"fmt"
"image"
_ "image/jpeg"
"io/ioutil"
"log"
"net/http"
"github.com/LdDl/go-darknet"
)
var configFile = flag.String("configFile", "",
"Path to network layer configuration file. Example: cfg/yolov3.cfg")
var weightsFile = flag.String("weightsFile", "",
"Path to weights file. Example: yolov3.weights")
var serverPort = flag.Int("port", 8090,
"Listening port")
func main() {
flag.Parse()
if *configFile == "" || *weightsFile == "" {
flag.Usage()
return
}
n := darknet.YOLONetwork{
GPUDeviceIndex: 0,
NetworkConfigurationFile: *configFile,
WeightsFile: *weightsFile,
Threshold: .25,
}
if err := n.Init(); err != nil {
log.Println(err)
return
}
defer n.Close()
http.HandleFunc("/detect_objects", detectObjects(&n))
http.ListenAndServe(fmt.Sprintf(":%d", *serverPort), nil)
}
// DarknetResp Response
type DarknetResp struct {
NetTime string `json:"net_time"`
OverallTime string `json:"overall_time"`
Detections []*DarknetDetection `json:"detections"`
}
// DarknetDetection Information about single detection
type DarknetDetection struct {
ClassID int `json:"class_id"`
ClassName string `json:"class_name"`
Probability float32 `json:"probability"`
StartPoint *DarknetPoint `json:"start_point"`
EndPoint *DarknetPoint `json:"end_point"`
}
// DarknetPoint image.Image point
type DarknetPoint struct {
X int `json:"x"`
Y int `json:"y"`
}
func detectObjects(n *darknet.YOLONetwork) func(w http.ResponseWriter, req *http.Request) {
return func(w http.ResponseWriter, req *http.Request) {
// Restrict file size up to 10mb
req.ParseMultipartForm(10 << 20)
file, _, err := req.FormFile("image")
if err != nil {
fmt.Fprintf(w, fmt.Sprintf("Error reading FormFile: %s", err.Error()))
return
}
defer file.Close()
fileBytes, err := ioutil.ReadAll(file)
if err != nil {
fmt.Fprintf(w, fmt.Sprintf("Error reading bytes: %s", err.Error()))
return
}
imgSrc, _, err := image.Decode(bytes.NewReader(fileBytes))
if err != nil {
fmt.Fprintf(w, fmt.Sprintf("Error decoding bytes to image: %s", err.Error()))
return
}
imgDarknet, err := darknet.Image2Float32(imgSrc)
if err != nil {
fmt.Fprintf(w, fmt.Sprintf("Error converting image.Image to darknet.DarknetImage: %s", err.Error()))
return
}
defer imgDarknet.Close()
dr, err := n.Detect(imgDarknet)
if err != nil {
fmt.Fprintf(w, fmt.Sprintf("Error detecting objects: %s", err.Error()))
return
}
resp := DarknetResp{
NetTime: fmt.Sprintf("%v", dr.NetworkOnlyTimeTaken),
OverallTime: fmt.Sprintf("%v", dr.OverallTimeTaken),
Detections: []*DarknetDetection{},
}
for _, d := range dr.Detections {
for i := range d.ClassIDs {
bBox := d.BoundingBox
resp.Detections = append(resp.Detections, &DarknetDetection{
ClassID: d.ClassIDs[i],
ClassName: d.ClassNames[i],
Probability: d.Probabilities[i],
StartPoint: &DarknetPoint{
X: bBox.StartPoint.X,
Y: bBox.StartPoint.Y,
},
EndPoint: &DarknetPoint{
X: bBox.EndPoint.X,
Y: bBox.EndPoint.Y,
},
})
}
}
respBytes, err := json.Marshal(resp)
if err != nil {
fmt.Fprintf(w, fmt.Sprintf("Error encoding response: %s", err.Error()))
return
}
fmt.Fprintf(w, string(respBytes))
}
}