Merge pull request #9 from LdDl/issue-8

network_predict

.gitignore

@@ -1,10 +1,15 @@
 example/main
 example/sample.jpg
-example/coco.data
 example/coco.names
-example/yolov3-320.cfg
-example/yolov3-320.weights
-example/yolov3-416.cfg
-example/yolov3-416.weights
 example/yolov3.cfg
 example/yolov3.weights
+example/yolov4.cfg
+example/yolov4.weights
+darknet.h
+*.so
+predictions.png
+predictions.jpg
+main
+bad.list
+data
+.vscode

README.md

@@ -1,19 +1,29 @@
-# FORK of go-darknet https://github.com/gyonluks/go-darknet
-# go-darknet: Go bindings for Darknet
-
 [![GoDoc](https://godoc.org/github.com/LdDl/go-darknet?status.svg)](https://godoc.org/github.com/LdDl/go-darknet)
+[![Sourcegraph](https://sourcegraph.com/github.com/LdDl/go-darknet/-/badge.svg)](https://sourcegraph.com/github.com/LdDl/go-darknet?badge)
+[![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 is a Go package, which uses Cgo to enable Go applications to use
-YOLO in [Darknet].
 
-## License
+# 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].
 
-go-darknet follows [Darknet]'s [license].
+#### Since this repository https://github.com/gyonluks/go-darknet  is no longer maintained I decided to move on and make little different bindings for Darknet.
+#### This bindings aren't for [official implementation](https://github.com/pjreddie/darknet) but for [AlexeyAB's fork](https://github.com/AlexeyAB/darknet).
+
+#### Paper Yolo v4: https://arxiv.org/abs/2004.10934
+#### Paper Yolo v3: https://arxiv.org/abs/1804.02767
+
+## Table of Contents
+
+- [Requirements](#requirements)
+- [Installation](#installation)
+- [Usage](#usage)
+- [Documentation](#documentation)
+- [License](#license)
 
 ## Requirements
 
-For proper codebase please use fork of [darknet](https://github.com/LdDl/darknet)
+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)
-There are instructions for defining GPU/CPU + function for loading image from memory.
 
 In order to use go-darknet, `libdarknet.so` should be available in one of
 the following locations:
@@ -26,53 +36,123 @@ Also, [darknet.h] should be available in one of the following locations:
 * /usr/include
 * /usr/local/include
 
-## Install
+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
 go get github.com/LdDl/go-darknet
 ```
 
-The package name is `darknet`.
+## Usage
 
-## Use
+Example Go program is provided in the [example] directory. Please refer to the code on how to use this Go package.
 
-Example Go code/program is provided in the [example] directory. Please
+Building and running program:
-refer to the code on how to use this Go package.
-
-Building and running the example program is easy:
 
+Navigate to [example] folder
 ```shell
 cd $GOPATH/github.com/LdDl/go-darknet/example
-#download dataset (coco.names, coco.data, weights and configuration file)
+```
+
+Download dataset (sample of image, coco.names, yolov4.cfg (or v3), yolov4.weights(or v3)).
+```shell
+#for yolo v4
 ./download_data.sh
-#build program
+#for yolo v3
-go build main.go
+./download_data_v3.sh
-#run it
+```
-./main -configFile yolov3.cfg --dataConfigFile coco.data -imageFile sample.jpg -weightsFile yolov3.weights
+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.
+
+
+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
-truck (7): 95.6232% | start point: (78,69) | end point: (222, 291)
+traffic light (9): 73.5039% | start point: (238,73) | end point: (251, 106)
-truck (7): 81.5451% | start point: (0,114) | end point: (90, 329)
+truck (7): 96.6401% | start point: (95,79) | end point: (233, 287)
-car (2): 99.8129% | start point: (269,192) | end point: (421, 323)
+truck (7): 96.4774% | start point: (662,158) | end point: (800, 321)
-car (2): 99.6615% | start point: (567,188) | end point: (743, 329)
+truck (7): 96.1841% | start point: (0,77) | end point: (86, 333)
-car (2): 99.5795% | start point: (425,196) | end point: (544, 309)
+truck (7): 46.8695% | start point: (434,173) | end point: (559, 216)
-car (2): 96.5765% | start point: (678,185) | end point: (797, 320)
+car (2): 99.7370% | start point: (512,188) | end point: (741, 329)
-car (2): 91.5156% | start point: (391,209) | end point: (441, 291)
+car (2): 99.2533% | start point: (260,191) | end point: (422, 322)
-car (2): 88.1737% | start point: (507,193) | end point: (660, 324)
+car (2): 99.0333% | start point: (425,201) | end point: (547, 309)
-car (2): 83.6209% | start point: (71,199) | end point: (102, 281)
+car (2): 83.3919% | start point: (386,210) | end point: (437, 287)
-bicycle (1): 59.4000% | start point: (183,276) | end point: (257, 407)
+car (2): 75.8621% | start point: (73,199) | end point: (102, 274)
-person (0): 96.3393% | start point: (142,119) | end point: (285, 356)
+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
+```
+
+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
 
 See go-darknet's API documentation at [GoDoc].
 
+## License
+
+go-darknet follows [Darknet]'s [license].
+
+
 [Darknet]: https://github.com/pjreddie/darknet
 [license]: https://github.com/pjreddie/darknet/blob/master/LICENSE
-[darknet.h]: https://github.com/pjreddie/darknet/blob/master/include/darknet.h
+[darknet.h]: https://github.com/AlexeyAB/darknet/blob/master/include/darknet.h
-[include/darknet.h]: https://github.com/pjreddie/darknet/blob/master/include/darknet.h
+[include/darknet.h]: https://github.com/AlexeyAB/darknet/blob/master/include/darknet.h
-[Makefile]: https://github.com/pjreddie/darknet/blob/master/Makefile
+[Makefile]: https://github.com/alexeyab/darknet/blob/master/Makefile
 [example]: /example
 [GoDoc]: https://godoc.org/github.com/LdDl/go-darknet

classes.c

@@ -0,0 +1,8 @@
+#include <stdlib.h>
+
+char *get_class_name(char **names, int index, int names_len) {
+    if (index >= names_len) {
+        return NULL;
+    }
+    return names[index];
+}

classes.go

@@ -0,0 +1,14 @@
+package darknet
+
+// #include <stdlib.h>
+// #include "classes.h"
+import "C"
+
+func makeClassNames(names **C.char, classes int) []string {
+	out := make([]string, classes)
+	for i := 0; i < classes; i++ {
+		n := C.get_class_name(names, C.int(i), C.int(classes))
+		out[i] = C.GoString(n)
+	}
+	return out
+}

classes.h

@@ -0,0 +1,3 @@
+#pragma once
+
+extern char *get_class_name(char **names, int index, int names_len);

classnames.c

@@ -1,24 +0,0 @@
-#include <stdlib.h>
-
-#include <darknet.h>
-
-void free_class_names(char **names)
-{
-    free(names);
-}
-
-char ** read_class_names(char *data_cfg)
-{
-    list *options = read_data_cfg(data_cfg);
-    char *name_list = option_find_str(options, "names", "data/names.list");
-    return get_labels(name_list);
-}
-
-char * get_class_name(char **names, int index, int names_len)
-{
-    if (index >= names_len) {
-        return NULL;
-    }
-
-    return names[index];
-}

classnames.go

@@ -1,28 +0,0 @@
-package darknet
-
-// #include <stdlib.h>
-// #include "classnames.h"
-import "C"
-import "unsafe"
-
-func freeClassNames(names **C.char) {
-	C.free_class_names(names)
-}
-
-func loadClassNames(dataConfigFile string) **C.char {
-	d := C.CString(dataConfigFile)
-	defer C.free(unsafe.Pointer(d))
-
-	return C.read_class_names(d)
-}
-
-func makeClassNames(names **C.char, classes int) []string {
-	out := make([]string, classes)
-	for i := 0; i < classes; i++ {
-		n := C.get_class_name(names, C.int(i), C.int(classes))
-		s := C.GoString(n)
-		out[i] = s
-	}
-
-	return out
-}

classnames.h

@@ -1,5 +0,0 @@
-#pragma once
-
-extern void free_class_names(char **names);
-extern char ** read_class_names(char *data_cfg);
-extern char * get_class_name(char **names, int index, int names_len);

darknet.go

@@ -1,5 +1,5 @@
 package darknet
 
 // #cgo CFLAGS: -I/usr/local/include -I/usr/local/cuda/include
-// #cgo LDFLAGS: -L/usr/local/lib -ldarknet -lm
+// #cgo LDFLAGS: -L/usr/lib -ldarknet -lm
 import "C"

detection.c

@@ -1,19 +1,17 @@
 #include <darknet.h>
 
-detection * get_detection(detection *dets, int index, int dets_len)
+#include "detection.h"
-{
+
+detection *get_detection(detection *dets, int index, int dets_len) {
     if (index >= dets_len) {
         return NULL;
     }
-
     return dets + index;
 }
 
-float get_detection_probability(detection *det, int index, int prob_len)
+float get_detection_probability(detection *det, int index, int prob_len) {
-{
     if (index >= prob_len) {
         return .0;
     }
-
     return det->prob[index];
 }

detection.go

@@ -25,19 +25,15 @@ type DetectionResult struct {
 	OverallTimeTaken     time.Duration
 }
 
-func makeDetection(img *Image, det *C.detection, threshold float32, classes int,
+func makeDetection(img *DarknetImage, det *C.detection, threshold float32, classes int, classNames []string) *Detection {
-	classNames []string) *Detection {
-
 	if det == nil {
 		return &Detection{}
 	}
 	dClassIDs := make([]int, 0)
 	dClassNames := make([]string, 0)
 	dProbs := make([]float32, 0)
-
 	for i := 0; i < int(classes); i++ {
-		dProb := float32(
+		dProb := float32(C.get_detection_probability(det, C.int(i), C.int(classes)))
-			C.get_detection_probability(det, C.int(i), C.int(classes)))
 		if dProb > threshold {
 			dClassIDs = append(dClassIDs, i)
 			cN := classNames[i]
@@ -45,7 +41,6 @@ func makeDetection(img *Image, det *C.detection, threshold float32, classes int,
 			dProbs = append(dProbs, dProb*100)
 		}
 	}
-
 	fImgW := C.float(img.Width)
 	fImgH := C.float(img.Height)
 	halfRatioW := det.bbox.w / 2.0
@@ -66,19 +61,16 @@ func makeDetection(img *Image, det *C.detection, threshold float32, classes int,
 		ClassNames:    dClassNames,
 		Probabilities: dProbs,
 	}
-
 	return &out
 }
 
-func makeDetections(img *Image, detections *C.detection, detectionsLength int,
+func makeDetections(img *DarknetImage, detections *C.detection, detectionsLength int, threshold float32, classes int, classNames []string) []*Detection {
-	threshold float32, classes int, classNames []string) []*Detection {
 	// Make list of detection objects.
 	ds := make([]*Detection, detectionsLength)
 	for i := 0; i < int(detectionsLength); i++ {
-		det := C.get_detection(detections, C.int(i), C.int(classes))
+		det := C.get_detection(detections, C.int(i), C.int(detectionsLength))
 		d := makeDetection(img, det, threshold, classes, classNames)
 		ds[i] = d
 	}
-
 	return ds
 }

docker/.env

@@ -0,0 +1 @@
+NAMESPACE=darknet

docker/Dockerfile

@@ -0,0 +1,40 @@
+# Build phase
+FROM ubuntu:18.04 as builder
+
+ENV darknet_commit=a234a5022333c930de08f2470184ef4e0c68356e
+
+WORKDIR /root/build
+COPY Makefile.cpu .
+RUN apt-get -y update && \
+	apt-get -y install --no-install-recommends git build-essential ca-certificates && \
+	git clone https://github.com/AlexeyAB/darknet && \
+	cd darknet && \
+	git checkout $darknet_commit && \
+	cp -f /root/build/Makefile.cpu Makefile && \
+	make
+
+# Final Image
+FROM golang:1.14
+
+RUN apt-get -y update && \
+        apt-get -y install --no-install-recommends nano bash jq
+
+WORKDIR /root
+COPY --from=builder /root/build/darknet/darknet \
+	/root/build/darknet/libdarknet.so \
+	/root/build/darknet/include/darknet.h \
+	./staging/
+
+RUN mv staging/darknet /usr/local/bin && \
+	mv staging/darknet.h /usr/include && \
+	mv staging/libdarknet.so /usr/lib && \
+	rm -rf staging
+
+RUN go get -u github.com/LdDl/go-darknet \
+    && go get -u github.com/disintegration/imaging
+
+WORKDIR /darknet
+
+COPY download_data.sh .
+
+CMD ["/bin/bash"]

docker/Dockerfile.gpu

@@ -0,0 +1,52 @@
+# Build phase
+FROM nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04 as builder
+
+ENV darknet_commit=a234a5022333c930de08f2470184ef4e0c68356e
+
+WORKDIR /root/build
+COPY Makefile.gpu .
+RUN apt-get -y update && \
+	apt-get -y install git build-essential && \
+	git clone https://github.com/AlexeyAB/darknet.git && \
+	cd darknet && \
+	git checkout $darknet_commit && \
+        cp -f /root/build/Makefile.gpu Makefile && \
+	make
+
+# Final Image
+FROM nvidia/cuda:10.0-cudnn7-runtime-ubuntu18.04
+
+WORKDIR /root
+COPY --from=builder /root/build/darknet/darknet \
+	/root/build/darknet/libdarknet.so \
+	/root/build/darknet/include/darknet.h \
+	./staging/
+
+RUN mv staging/darknet /usr/local/bin && \
+	mv staging/darknet.h /usr/include && \
+	mv staging/libdarknet.so /usr/lib && \
+	rm -rf staging
+
+WORKDIR /tmp
+RUN cd /tmp \
+    && apt-get -y update \
+    && apt-get install -y wget git gcc \ 
+    && wget https://dl.google.com/go/go1.14.linux-amd64.tar.gz \
+    && tar -xvf go1.14.linux-amd64.tar.gz \
+    && mv go /usr/local
+
+RUN cp /usr/local/cuda-10.0/compat/* /usr/local/cuda-10.0/targets/x86_64-linux/lib/
+
+ENV GOROOT=/usr/local/go
+ENV GOPATH=/go
+ENV PATH=$GOPATH/bin:$GOROOT/bin:$PATH
+ENV LIBRARY_PATH=$LIBRARY_PATH:/usr/local/cuda-10.0/compat/
+
+RUN go get -u github.com/LdDl/go-darknet \
+    && go get -u github.com/disintegration/imaging
+
+WORKDIR /darknet
+
+COPY download_data.sh .
+
+CMD ["/bin/bash"]

docker/Makefile.cpu

@@ -0,0 +1,185 @@
+GPU=0
+CUDNN=0
+CUDNN_HALF=0
+OPENCV=0
+AVX=1
+OPENMP=1
+LIBSO=1
+ZED_CAMERA=0 # ZED SDK 3.0 and above
+ZED_CAMERA_v2_8=0 # ZED SDK 2.X
+
+# set GPU=1 and CUDNN=1 to speedup on GPU
+# set CUDNN_HALF=1 to further speedup 3 x times (Mixed-precision on Tensor Cores) GPU: Volta, Xavier, Turing and higher
+# set AVX=1 and OPENMP=1 to speedup on CPU (if error occurs then set AVX=0)
+
+USE_CPP=0
+DEBUG=0
+
+ARCH= -gencode arch=compute_30,code=sm_30 \
+      -gencode arch=compute_35,code=sm_35 \
+      -gencode arch=compute_50,code=[sm_50,compute_50] \
+      -gencode arch=compute_52,code=[sm_52,compute_52] \
+	  -gencode arch=compute_61,code=[sm_61,compute_61]
+
+OS := $(shell uname)
+
+# Tesla V100
+# ARCH= -gencode arch=compute_70,code=[sm_70,compute_70]
+
+# GeForce RTX 2080 Ti, RTX 2080, RTX 2070, Quadro RTX 8000, Quadro RTX 6000, Quadro RTX 5000, Tesla T4, XNOR Tensor Cores
+# ARCH= -gencode arch=compute_75,code=[sm_75,compute_75]
+
+# Jetson XAVIER
+# ARCH= -gencode arch=compute_72,code=[sm_72,compute_72]
+
+# GTX 1080, GTX 1070, GTX 1060, GTX 1050, GTX 1030, Titan Xp, Tesla P40, Tesla P4
+# ARCH= -gencode arch=compute_61,code=sm_61 -gencode arch=compute_61,code=compute_61
+
+# GP100/Tesla P100 - DGX-1
+# ARCH= -gencode arch=compute_60,code=sm_60
+
+# For Jetson TX1, Tegra X1, DRIVE CX, DRIVE PX - uncomment:
+# ARCH= -gencode arch=compute_53,code=[sm_53,compute_53]
+
+# For Jetson Tx2 or Drive-PX2 uncomment:
+# ARCH= -gencode arch=compute_62,code=[sm_62,compute_62]
+
+
+# VPATH=./src/
+VPATH=./src/:./examples
+SLIB=libdarknet.so
+
+EXEC=darknet
+OBJDIR=./obj/
+
+ifeq ($(LIBSO), 1)
+LIBNAMESO=libdarknet.so
+APPNAMESO=uselib
+endif
+
+ifeq ($(USE_CPP), 1)
+CC=g++
+else
+CC=gcc
+endif
+
+CPP=g++ -std=c++11
+NVCC=nvcc
+OPTS=-Ofast
+LDFLAGS= -lm -pthread
+COMMON= -Iinclude/ -I3rdparty/stb/include
+CFLAGS=-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC
+
+ifeq ($(DEBUG), 1)
+#OPTS= -O0 -g
+#OPTS= -Og -g
+COMMON+= -DDEBUG
+CFLAGS+= -DDEBUG
+else
+ifeq ($(AVX), 1)
+CFLAGS+= -ffp-contract=fast -mavx -mavx2 -msse3 -msse4.1 -msse4.2 -msse4a
+endif
+endif
+
+CFLAGS+=$(OPTS)
+
+ifneq (,$(findstring MSYS_NT,$(OS)))
+LDFLAGS+=-lws2_32
+endif
+
+ifeq ($(OPENCV), 1)
+COMMON+= -DOPENCV
+CFLAGS+= -DOPENCV
+LDFLAGS+= `pkg-config --libs opencv4 2> /dev/null || pkg-config --libs opencv`
+COMMON+= `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv`
+endif
+
+ifeq ($(OPENMP), 1)
+CFLAGS+= -fopenmp
+LDFLAGS+= -lgomp
+endif
+
+ifeq ($(GPU), 1)
+COMMON+= -DGPU -I/usr/local/cuda/include/
+CFLAGS+= -DGPU
+ifeq ($(OS),Darwin) #MAC
+LDFLAGS+= -L/usr/local/cuda/lib -lcuda -lcudart -lcublas -lcurand
+else
+LDFLAGS+= -L/usr/local/cuda/lib64 -lcuda -lcudart -lcublas -lcurand
+endif
+endif
+
+ifeq ($(CUDNN), 1)
+COMMON+= -DCUDNN
+ifeq ($(OS),Darwin) #MAC
+CFLAGS+= -DCUDNN -I/usr/local/cuda/include
+LDFLAGS+= -L/usr/local/cuda/lib -lcudnn
+else
+CFLAGS+= -DCUDNN -I/usr/local/cudnn/include
+LDFLAGS+= -L/usr/local/cudnn/lib64 -lcudnn
+endif
+endif
+
+ifeq ($(CUDNN_HALF), 1)
+COMMON+= -DCUDNN_HALF
+CFLAGS+= -DCUDNN_HALF
+ARCH+= -gencode arch=compute_70,code=[sm_70,compute_70]
+endif
+
+ifeq ($(ZED_CAMERA), 1)
+CFLAGS+= -DZED_STEREO -I/usr/local/zed/include
+ifeq ($(ZED_CAMERA_v2_8), 1)
+LDFLAGS+= -L/usr/local/zed/lib -lsl_core -lsl_input -lsl_zed
+#-lstdc++ -D_GLIBCXX_USE_CXX11_ABI=0 
+else
+LDFLAGS+= -L/usr/local/zed/lib -lsl_zed
+#-lstdc++ -D_GLIBCXX_USE_CXX11_ABI=0 
+endif
+endif
+
+OBJ=image_opencv.o http_stream.o gemm.o utils.o dark_cuda.o convolutional_layer.o list.o image.o activations.o im2col.o col2im.o blas.o crop_layer.o dropout_layer.o maxpool_layer.o softmax_layer.o data.o matrix.o network.o connected_layer.o cost_layer.o parser.o option_list.o darknet.o detection_layer.o captcha.o route_layer.o writing.o box.o nightmare.o normalization_layer.o avgpool_layer.o coco.o dice.o yolo.o detector.o layer.o compare.o classifier.o local_layer.o swag.o shortcut_layer.o activation_layer.o rnn_layer.o gru_layer.o rnn.o rnn_vid.o crnn_layer.o demo.o tag.o cifar.o go.o batchnorm_layer.o art.o region_layer.o reorg_layer.o reorg_old_layer.o super.o voxel.o tree.o yolo_layer.o gaussian_yolo_layer.o upsample_layer.o lstm_layer.o conv_lstm_layer.o scale_channels_layer.o sam_layer.o
+ifeq ($(GPU), 1) 
+LDFLAGS+= -lstdc++ 
+OBJ+=convolutional_kernels.o activation_kernels.o im2col_kernels.o col2im_kernels.o blas_kernels.o crop_layer_kernels.o dropout_layer_kernels.o maxpool_layer_kernels.o network_kernels.o avgpool_layer_kernels.o
+endif
+
+OBJS = $(addprefix $(OBJDIR), $(OBJ))
+DEPS = $(wildcard src/*.h) Makefile include/darknet.h
+
+all: $(OBJDIR) backup results setchmod $(EXEC) $(LIBNAMESO) $(APPNAMESO)
+
+ifeq ($(LIBSO), 1)
+CFLAGS+= -fPIC
+
+$(LIBNAMESO): $(OBJDIR) $(OBJS) include/yolo_v2_class.hpp src/yolo_v2_class.cpp
+	$(CPP) -shared -std=c++11 -fvisibility=hidden -DLIB_EXPORTS $(COMMON) $(CFLAGS) $(OBJS) src/yolo_v2_class.cpp -o $@ $(LDFLAGS)
+
+$(APPNAMESO): $(LIBNAMESO) include/yolo_v2_class.hpp src/yolo_console_dll.cpp
+	$(CPP) -std=c++11 $(COMMON) $(CFLAGS) -o $@ src/yolo_console_dll.cpp $(LDFLAGS) -L ./ -l:$(LIBNAMESO)
+endif
+
+$(EXEC): $(OBJS)
+	$(CPP) -std=c++11 $(COMMON) $(CFLAGS) $^ -o $@ $(LDFLAGS)
+
+$(OBJDIR)%.o: %.c $(DEPS)
+	$(CC) $(COMMON) $(CFLAGS) -c $< -o $@
+
+$(OBJDIR)%.o: %.cpp $(DEPS)
+	$(CPP) -std=c++11 $(COMMON) $(CFLAGS) -c $< -o $@
+
+$(OBJDIR)%.o: %.cu $(DEPS)
+	$(NVCC) $(ARCH) $(COMMON) --compiler-options "$(CFLAGS)" -c $< -o $@
+
+$(OBJDIR):
+	mkdir -p $(OBJDIR)
+backup:
+	mkdir -p backup
+results:
+	mkdir -p results
+setchmod:
+	chmod +x *.sh
+
+.PHONY: clean
+
+clean:
+	rm -rf $(OBJS) $(EXEC) $(LIBNAMESO) $(APPNAMESO)

docker/Makefile.gpu

@@ -0,0 +1,186 @@
+
+GPU=1
+CUDNN=1
+CUDNN_HALF=0
+OPENCV=0
+AVX=0
+OPENMP=0
+LIBSO=1
+ZED_CAMERA=0 # ZED SDK 3.0 and above
+ZED_CAMERA_v2_8=0 # ZED SDK 2.X
+
+# set GPU=1 and CUDNN=1 to speedup on GPU
+# set CUDNN_HALF=1 to further speedup 3 x times (Mixed-precision on Tensor Cores) GPU: Volta, Xavier, Turing and higher
+# set AVX=1 and OPENMP=1 to speedup on CPU (if error occurs then set AVX=0)
+
+USE_CPP=0
+DEBUG=0
+
+ARCH= -gencode arch=compute_30,code=sm_30 \
+      -gencode arch=compute_35,code=sm_35 \
+      -gencode arch=compute_50,code=[sm_50,compute_50] \
+      -gencode arch=compute_52,code=[sm_52,compute_52] \
+	  -gencode arch=compute_61,code=[sm_61,compute_61]
+
+OS := $(shell uname)
+
+# Tesla V100
+# ARCH= -gencode arch=compute_70,code=[sm_70,compute_70]
+
+# GeForce RTX 2080 Ti, RTX 2080, RTX 2070, Quadro RTX 8000, Quadro RTX 6000, Quadro RTX 5000, Tesla T4, XNOR Tensor Cores
+# ARCH= -gencode arch=compute_75,code=[sm_75,compute_75]
+
+# Jetson XAVIER
+# ARCH= -gencode arch=compute_72,code=[sm_72,compute_72]
+
+# GTX 1080, GTX 1070, GTX 1060, GTX 1050, GTX 1030, Titan Xp, Tesla P40, Tesla P4
+# ARCH= -gencode arch=compute_61,code=sm_61 -gencode arch=compute_61,code=compute_61
+
+# GP100/Tesla P100 - DGX-1
+# ARCH= -gencode arch=compute_60,code=sm_60
+
+# For Jetson TX1, Tegra X1, DRIVE CX, DRIVE PX - uncomment:
+# ARCH= -gencode arch=compute_53,code=[sm_53,compute_53]
+
+# For Jetson Tx2 or Drive-PX2 uncomment:
+# ARCH= -gencode arch=compute_62,code=[sm_62,compute_62]
+
+
+# VPATH=./src/
+VPATH=./src/:./examples
+SLIB=libdarknet.so
+
+EXEC=darknet
+OBJDIR=./obj/
+
+ifeq ($(LIBSO), 1)
+LIBNAMESO=libdarknet.so
+APPNAMESO=uselib
+endif
+
+ifeq ($(USE_CPP), 1)
+CC=g++
+else
+CC=gcc
+endif
+
+CPP=g++ -std=c++11
+NVCC=nvcc
+OPTS=-Ofast
+LDFLAGS= -lm -pthread
+COMMON= -Iinclude/ -I3rdparty/stb/include
+CFLAGS=-Wall -Wfatal-errors -Wno-unused-result -Wno-unknown-pragmas -fPIC
+
+ifeq ($(DEBUG), 1)
+#OPTS= -O0 -g
+#OPTS= -Og -g
+COMMON+= -DDEBUG
+CFLAGS+= -DDEBUG
+else
+ifeq ($(AVX), 1)
+CFLAGS+= -ffp-contract=fast -mavx -mavx2 -msse3 -msse4.1 -msse4.2 -msse4a
+endif
+endif
+
+CFLAGS+=$(OPTS)
+
+ifneq (,$(findstring MSYS_NT,$(OS)))
+LDFLAGS+=-lws2_32
+endif
+
+ifeq ($(OPENCV), 1)
+COMMON+= -DOPENCV
+CFLAGS+= -DOPENCV
+LDFLAGS+= `pkg-config --libs opencv4 2> /dev/null || pkg-config --libs opencv`
+COMMON+= `pkg-config --cflags opencv4 2> /dev/null || pkg-config --cflags opencv`
+endif
+
+ifeq ($(OPENMP), 1)
+CFLAGS+= -fopenmp
+LDFLAGS+= -lgomp
+endif
+
+ifeq ($(GPU), 1)
+COMMON+= -DGPU -I/usr/local/cuda/include/
+CFLAGS+= -DGPU
+ifeq ($(OS),Darwin) #MAC
+LDFLAGS+= -L/usr/local/cuda/lib -lcuda -lcudart -lcublas -lcurand
+else
+LDFLAGS+= -L/usr/local/cuda/lib64 -lcuda -lcudart -lcublas -lcurand
+endif
+endif
+
+ifeq ($(CUDNN), 1)
+COMMON+= -DCUDNN
+ifeq ($(OS),Darwin) #MAC
+CFLAGS+= -DCUDNN -I/usr/local/cuda/include
+LDFLAGS+= -L/usr/local/cuda/lib -lcudnn
+else
+CFLAGS+= -DCUDNN -I/usr/local/cudnn/include
+LDFLAGS+= -L/usr/local/cudnn/lib64 -lcudnn
+endif
+endif
+
+ifeq ($(CUDNN_HALF), 1)
+COMMON+= -DCUDNN_HALF
+CFLAGS+= -DCUDNN_HALF
+ARCH+= -gencode arch=compute_70,code=[sm_70,compute_70]
+endif
+
+ifeq ($(ZED_CAMERA), 1)
+CFLAGS+= -DZED_STEREO -I/usr/local/zed/include
+ifeq ($(ZED_CAMERA_v2_8), 1)
+LDFLAGS+= -L/usr/local/zed/lib -lsl_core -lsl_input -lsl_zed
+#-lstdc++ -D_GLIBCXX_USE_CXX11_ABI=0 
+else
+LDFLAGS+= -L/usr/local/zed/lib -lsl_zed
+#-lstdc++ -D_GLIBCXX_USE_CXX11_ABI=0 
+endif
+endif
+
+OBJ=image_opencv.o http_stream.o gemm.o utils.o dark_cuda.o convolutional_layer.o list.o image.o activations.o im2col.o col2im.o blas.o crop_layer.o dropout_layer.o maxpool_layer.o softmax_layer.o data.o matrix.o network.o connected_layer.o cost_layer.o parser.o option_list.o darknet.o detection_layer.o captcha.o route_layer.o writing.o box.o nightmare.o normalization_layer.o avgpool_layer.o coco.o dice.o yolo.o detector.o layer.o compare.o classifier.o local_layer.o swag.o shortcut_layer.o activation_layer.o rnn_layer.o gru_layer.o rnn.o rnn_vid.o crnn_layer.o demo.o tag.o cifar.o go.o batchnorm_layer.o art.o region_layer.o reorg_layer.o reorg_old_layer.o super.o voxel.o tree.o yolo_layer.o gaussian_yolo_layer.o upsample_layer.o lstm_layer.o conv_lstm_layer.o scale_channels_layer.o sam_layer.o
+ifeq ($(GPU), 1) 
+LDFLAGS+= -lstdc++ 
+OBJ+=convolutional_kernels.o activation_kernels.o im2col_kernels.o col2im_kernels.o blas_kernels.o crop_layer_kernels.o dropout_layer_kernels.o maxpool_layer_kernels.o network_kernels.o avgpool_layer_kernels.o
+endif
+
+OBJS = $(addprefix $(OBJDIR), $(OBJ))
+DEPS = $(wildcard src/*.h) Makefile include/darknet.h
+
+all: $(OBJDIR) backup results setchmod $(EXEC) $(LIBNAMESO) $(APPNAMESO)
+
+ifeq ($(LIBSO), 1)
+CFLAGS+= -fPIC
+
+$(LIBNAMESO): $(OBJDIR) $(OBJS) include/yolo_v2_class.hpp src/yolo_v2_class.cpp
+	$(CPP) -shared -std=c++11 -fvisibility=hidden -DLIB_EXPORTS $(COMMON) $(CFLAGS) $(OBJS) src/yolo_v2_class.cpp -o $@ $(LDFLAGS)
+
+$(APPNAMESO): $(LIBNAMESO) include/yolo_v2_class.hpp src/yolo_console_dll.cpp
+	$(CPP) -std=c++11 $(COMMON) $(CFLAGS) -o $@ src/yolo_console_dll.cpp $(LDFLAGS) -L ./ -l:$(LIBNAMESO)
+endif
+
+$(EXEC): $(OBJS)
+	$(CPP) -std=c++11 $(COMMON) $(CFLAGS) $^ -o $@ $(LDFLAGS)
+
+$(OBJDIR)%.o: %.c $(DEPS)
+	$(CC) $(COMMON) $(CFLAGS) -c $< -o $@
+
+$(OBJDIR)%.o: %.cpp $(DEPS)
+	$(CPP) -std=c++11 $(COMMON) $(CFLAGS) -c $< -o $@
+
+$(OBJDIR)%.o: %.cu $(DEPS)
+	$(NVCC) $(ARCH) $(COMMON) --compiler-options "$(CFLAGS)" -c $< -o $@
+
+$(OBJDIR):
+	mkdir -p $(OBJDIR)
+backup:
+	mkdir -p backup
+results:
+	mkdir -p results
+setchmod:
+	chmod +x *.sh
+
+.PHONY: clean
+
+clean:
+	rm -rf $(OBJS) $(EXEC) $(LIBNAMESO) $(APPNAMESO)

docker/docker-compose.yml

@@ -0,0 +1,32 @@
+---
+version: '3.7'
+services:
+
+  sidekiq: &darknet_base 
+    container_name: ${NAMESPACE}-sidekiq
+    build:
+      context: .
+      dockerfile: Dockerfile
+    image: go-darknet:latest
+    working_dir: /darknet
+    volumes:
+    - darknet-data:/darknet/models
+    command: /darknet/download_data.sh
+
+  darknet:
+    <<: *darknet_base
+    container_name: ${NAMESPACE}-api
+    ports:
+    - "9003:9003"
+    restart: unless-stopped
+    depends_on:
+    - sidekiq
+    command: ["/bin/bash"]
+    # command: ["darknet-server"]
+
+volumes:
+  darknet-data:
+    driver_opts:
+      type: none
+      o: bind
+      device: ${PWD}/models

docker/download_data.sh

@@ -0,0 +1,10 @@
+#!/bin/sh
+
+# set -x
+# set -e
+
+wget -nc --output-document=sample.jpg https://cdn-images-1.medium.com/max/800/1*EYFejGUjvjPcc4PZTwoufw.jpeg
+wget -nc --output-document=./models/coco.names https://raw.githubusercontent.com/AlexeyAB/darknet/master/data/coco.names
+wget -nc --output-document=./models/yolov3.cfg https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov3.cfg
+sed -i -e "\$anames = coco.names" ./models/yolov3.cfg
+wget -nc --output-document=./models/yolov3.weights https://pjreddie.com/media/files/yolov3.weights

docker/models/.gitignore

@@ -0,0 +1,2 @@
+*
+!.gitignore

example/README.md

@@ -2,33 +2,53 @@
 
 This is an example Go application which uses go-darknet.
 
-## Install
-
-```shell
-go get github.com/LdDl/go-darknet
-go install github.com/LdDl/go-darknet/example
-
-# Alternatively
-go build github.com/LdDl/go-darknet/example
-```
-
-An executable named `example` should be in your `$GOPATH/bin`, if using
-`go install`; otherwise it will be in your current working directory (`$PWD`),
-if using `go build`.
 
 ## Run
 
+Navigate to example folder:
+
 ```shell
-$GOPATH/bin/example
+cd $GOPATH/github.com/LdDl/go-darknet/example
 ```
-or
+
-```go
+Download dataset (sample of image, coco.names, yolov3.cfg, yolov3.weights).
-go run main.go -configFile=yolov3-320.cfg -dataConfigFile=coco.data -imageFile=sample.jpg -weightsFile=yolov3.weights
+```shell
+./download_data.sh
+```
+Note: you don't need *coco.data* file anymore, because script below does insert *coco.names* into 'names' filed in *yolov3.cfg* file (so AlexeyAB's fork can deal with it properly)
+So last rows in yolov3.cfg file will look like:
+```bash
+......
+[yolo]
+mask = 0,1,2
+anchors = 10,13,  16,30,  33,23,  30,61,  62,45,  59,119,  116,90,  156,198,  373,326
+classes=80
+num=9
+jitter=.3
+ignore_thresh = .7
+truth_thresh = 1
+random=1
+names = coco.names # this is path to coco.names file
 ```
-Please ensure that `libdarknet.so` is in your `$LD_LIBRARY_PATH`.
 
-## Notes
+Build and run program
+```
+go build main.go && ./main --configFile=yolov3.cfg --weightsFile=yolov3.weights --imageFile=sample.jpg
+```
 
-Note that the bounding boxes' values are ratios. To get the actual values, use
+Output should be something like this:
-the ratios and multiply with either the image's width or height, depending on
+```shell
-which ratio is used.
+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)
+```

example/download_data.sh

@@ -1,6 +1,5 @@
 wget --output-document=sample.jpg https://cdn-images-1.medium.com/max/800/1*EYFejGUjvjPcc4PZTwoufw.jpeg
-wget --output-document=coco.names https://raw.githubusercontent.com/pjreddie/darknet/master/data/coco.names
+wget --output-document=coco.names https://raw.githubusercontent.com/AlexeyAB/darknet/master/data/coco.names
-wget --output-document=coco.data https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/coco.data
+wget --output-document=yolov4.cfg https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov4.cfg
-sed -i 's#data/coco.names#coco.names#g' coco.data
+sed -i -e "\$anames = coco.names" yolov4.cfg
-wget --output-document=yolov3.cfg https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov3.cfg
+wget --output-document=yolov4.weights https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v3_optimal/yolov4.weights
-wget --output-document=yolov3.weights https://pjreddie.com/media/files/yolov3.weights

example/download_data_v3.sh

@@ -0,0 +1,5 @@
+wget --output-document=sample.jpg https://cdn-images-1.medium.com/max/800/1*EYFejGUjvjPcc4PZTwoufw.jpeg
+wget --output-document=coco.names https://raw.githubusercontent.com/AlexeyAB/darknet/master/data/coco.names
+wget --output-document=yolov3.cfg https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov3.cfg
+sed -i -e "\$anames = coco.names" yolov3.cfg
+wget --output-document=yolov3.weights https://pjreddie.com/media/files/yolov3.weights

example/main.go

@@ -1,15 +1,19 @@
 package main
 
 import (
+	"bytes"
 	"flag"
 	"fmt"
+	"image"
+	"image/jpeg"
 	"log"
+	"math"
+	"os"
 
 	darknet "github.com/LdDl/go-darknet"
+	"github.com/disintegration/imaging"
 )
 
-var dataConfigFile = flag.String("dataConfigFile", "",
-	"Path to data configuration file. Example: cfg/coco.data")
 var configFile = flag.String("configFile", "",
 	"Path to network layer configuration file. Example: cfg/yolov3.cfg")
 var weightsFile = flag.String("weightsFile", "",
@@ -24,7 +28,7 @@ func printError(err error) {
 func main() {
 	flag.Parse()
 
-	if *dataConfigFile == "" || *configFile == "" || *weightsFile == "" ||
+	if *configFile == "" || *weightsFile == "" ||
 		*imageFile == "" {
 
 		flag.Usage()
@@ -33,10 +37,9 @@ func main() {
 
 	n := darknet.YOLONetwork{
 		GPUDeviceIndex:           0,
-		DataConfigurationFile:    *dataConfigFile,
 		NetworkConfigurationFile: *configFile,
 		WeightsFile:              *weightsFile,
-		Threshold:                .5,
+		Threshold:                .25,
 	}
 	if err := n.Init(); err != nil {
 		printError(err)
@@ -44,14 +47,23 @@ func main() {
 	}
 	defer n.Close()
 
-	img, err := darknet.ImageFromPath(*imageFile)
+	infile, err := os.Open(*imageFile)
 	if err != nil {
-		printError(err)
+		panic(err.Error())
-		return
+	}
+	defer infile.Close()
+	src, err := jpeg.Decode(infile)
+	if err != nil {
+		panic(err.Error())
 	}
-	defer img.Close()
 
-	dr, err := n.Detect(img)
+	imgDarknet, err := darknet.Image2Float32(src)
+	if err != nil {
+		panic(err.Error())
+	}
+	defer imgDarknet.Close()
+
+	dr, err := n.Detect(imgDarknet)
 	if err != nil {
 		printError(err)
 		return
@@ -60,7 +72,6 @@ func main() {
 	log.Println("Network-only time taken:", dr.NetworkOnlyTimeTaken)
 	log.Println("Overall time taken:", dr.OverallTimeTaken, len(dr.Detections))
 	for _, d := range dr.Detections {
-
 		for i := range d.ClassIDs {
 			bBox := d.BoundingBox
 			fmt.Printf("%s (%d): %.4f%% | start point: (%d,%d) | end point: (%d, %d)\n",
@@ -69,6 +80,43 @@ func main() {
 				bBox.StartPoint.X, bBox.StartPoint.Y,
 				bBox.EndPoint.X, bBox.EndPoint.Y,
 			)
+
+			// Uncomment code below if you want save cropped objects to files
+			// minX, minY := float64(bBox.StartPoint.X), float64(bBox.StartPoint.Y)
+			// maxX, maxY := float64(bBox.EndPoint.X), float64(bBox.EndPoint.Y)
+			// rect := image.Rect(round(minX), round(minY), round(maxX), round(maxY))
+			// err := saveToFile(src, rect, fmt.Sprintf("crop_%d.jpeg", i))
+			// if err != nil {
+			// 	fmt.Println(err)
+			// 	return
+			// }
 		}
 	}
 }
+
+func imageToBytes(img image.Image) ([]byte, error) {
+	buf := new(bytes.Buffer)
+	err := jpeg.Encode(buf, img, nil)
+	return buf.Bytes(), err
+}
+
+func round(v float64) int {
+	if v >= 0 {
+		return int(math.Floor(v + 0.5))
+	}
+	return int(math.Ceil(v - 0.5))
+}
+
+func saveToFile(imgSrc image.Image, bbox image.Rectangle, fname string) error {
+	rectcropimg := imaging.Crop(imgSrc, bbox)
+	f, err := os.Create(fname)
+	if err != nil {
+		return err
+	}
+	defer f.Close()
+	err = jpeg.Encode(f, rectcropimg, nil)
+	if err != nil {
+		return err
+	}
+	return nil
+}

image.c

@@ -0,0 +1,13 @@
+#include <darknet.h>
+
+void fill_image_f32(image* im, int w, int h, int c, float* data) {
+    int i;
+    for (i = 0; i < w*h*c; i++) {
+        im->data[i] = data[i];
+    }
+}
+
+void set_data_f32_val(float* data, int index, float value) {
+    data[index] = value;
+}
+

image.go

@@ -1,66 +1,84 @@
 package darknet
 
-// #include <darknet.h>
+// #include <stdlib.h>
+// #include "image.h"
 import "C"
 import (
-	"errors"
+	"image"
 	"unsafe"
+
+	"golang.org/x/image/draw"
 )
 
-// Image represents the image buffer.
+// DarknetImage represents the image buffer.
-type Image struct {
+type DarknetImage struct {
 	Width  int
 	Height int
-
+	ans    []float32
 	image  C.image
 }
 
-var (
-	errUnableToLoadImage = errors.New("unable to load image")
-)
-
 // Close and release resources.
-func (img *Image) Close() error {
+func (img *DarknetImage) Close() error {
 	C.free_image(img.image)
+	img.ans = nil
 	return nil
 }
 
-// ImageFromPath reads image file specified by path.
+// https://stackoverflow.com/questions/33186783/get-a-pixel-array-from-from-golang-image-image/59747737#59747737
-func ImageFromPath(path string) (*Image, error) {
+func imgTofloat32(src image.Image) []float32 {
-	p := C.CString(path)
+	bounds := src.Bounds()
-	defer C.free(unsafe.Pointer(p))
+	width, height := bounds.Max.X, bounds.Max.Y
+	srcRGBA := image.NewRGBA(src.Bounds())
+	draw.Copy(srcRGBA, image.Point{}, src, src.Bounds(), draw.Src, nil)
 
-	img := Image{
+	red := make([]float32, 0, width*height)
-		image: C.load_image_color(p, 0, 0),
+	green := make([]float32, 0, width*height)
+	blue := make([]float32, 0, width*height)
+	for y := 0; y < height; y++ {
+		for x := 0; x < width; x++ {
+			idxSource := (y*width + x) * 4
+			pix := srcRGBA.Pix[idxSource : idxSource+4]
+			rpix, gpix, bpix := float32(pix[0])/257.0, float32(pix[1])/257.0, float32(pix[2])/257.0
+			red = append(red, rpix)
+			green = append(green, gpix)
+			blue = append(blue, bpix)
+		}
+	}
+	srcRGBA = nil
+
+	ans := make([]float32, len(red)+len(green)+len(blue))
+	copy(ans[:len(red)], red)
+	copy(ans[len(red):len(red)+len(green)], green)
+	copy(ans[len(red)+len(green):], blue)
+	red = nil
+	green = nil
+	blue = nil
+	return ans
 }
 
-	if img.image.data == nil {
+// Image2Float32 Returns []float32 representation of image.Image
-		return nil, errUnableToLoadImage
+func Image2Float32(img image.Image) (*DarknetImage, error) {
+	// ans := imgTofloat32(img)
+	width := img.Bounds().Dx()
+	height := img.Bounds().Dy()
+	imgDarknet := &DarknetImage{
+		Width:  width,
+		Height: height,
+		ans:    imgTofloat32(img),
+		image:  C.make_image(C.int(width), C.int(height), 3),
+	}
+	C.fill_image_f32(&imgDarknet.image, C.int(width), C.int(height), 3, (*C.float)(unsafe.Pointer(&imgDarknet.ans[0])))
+	return imgDarknet, nil
 }
 
-	img.Width = int(img.image.w)
+// Float32ToDarknetImage Converts []float32 to darknet image
-	img.Height = int(img.image.h)
+func Float32ToDarknetImage(flatten []float32, width, height int) (*DarknetImage, error) {
-
+	imgDarknet := &DarknetImage{
-	return &img, nil
+		Width:  width,
+		Height: height,
+		image:  C.make_image(C.int(width), C.int(height), 3),
 	}
-
+	C.fill_image_f32(&imgDarknet.image, C.int(width), C.int(height), 3, (*C.float)(unsafe.Pointer(&flatten[0])))
-// ImageFromMemory reads image file data represented by the specified byte
+	return imgDarknet, nil
-// slice.
-func ImageFromMemory(buf []byte) (*Image, error) {
-	cBuf := C.CBytes(buf)
-	defer C.free(cBuf)
-
-	img := Image{
-		image: C.load_image_from_memory_color((*C.uchar)(cBuf),
-			C.int(len(buf)), 0, 0),
-	}
-
-	if img.image.data == nil {
-		return nil, errUnableToLoadImage
-	}
-
-	img.Width = int(img.image.w)
-	img.Height = int(img.image.h)
-
-	return &img, nil
 }

image.h

@@ -0,0 +1,6 @@
+#pragma once
+
+#include <darknet.h>
+
+extern void fill_image_f32(image *im, int w, int h, int c, float* data);
+extern void set_data_f32_val(float* data, int index, float value);

network.c

@@ -4,19 +4,23 @@
 
 #include "network.h"
 
-int get_network_layer_classes(network *n, int index) {
+#include "detection.h"
-	return n->layers[index].classes;
-}
 
-struct network_box_result perform_network_detect(network *n, image *img, int classes, float thresh, float hier_thresh, float nms) {
+struct network_box_result perform_network_detect(network *n, image *img, int classes, float thresh, float hier_thresh, float nms, int letter_box) {
-    image sized = letterbox_image(*img, n->w, n->h);
+    image sized;
+    if (letter_box) {
+        sized = letterbox_image(*img, n->w, n->h);
+    } else {
+        sized = resize_image(*img, n->w, n->h);
+    }
     struct network_box_result result = { NULL };
-    float *X = sized.data;
+    network_predict(*n, sized.data);
-    network_predict(n, X);
+    int nboxes = 0;
-    result.detections = get_network_boxes(n, img->w, img->h,thresh, hier_thresh, 0, 1, &result.detections_len);
+    result.detections = get_network_boxes(n, img->w, img->h, thresh, hier_thresh, 0, 1, &result.detections_len, letter_box);
     if (nms) {
         do_nms_sort(result.detections, result.detections_len, classes, nms);
     }
     free_image(sized);
     return result;
 }
+

network.go

@@ -15,7 +15,6 @@ import (
 // YOLONetwork represents a neural network using YOLO.
 type YOLONetwork struct {
 	GPUDeviceIndex           int
-	DataConfigurationFile    string
 	NetworkConfigurationFile string
 	WeightsFile              string
 	Threshold                float32
@@ -29,8 +28,8 @@ type YOLONetwork struct {
 }
 
 var (
-	errNetworkNotInit      = errors.New("network not initialised")
+	errNetworkNotInit      = errors.New("Network not initialised")
-	errUnableToInitNetwork = errors.New("unable to initialise")
+	errUnableToInitNetwork = errors.New("Unable to initialise")
 )
 
 // Init the network.
@@ -39,29 +38,18 @@ func (n *YOLONetwork) Init() error {
 	defer C.free(unsafe.Pointer(nCfg))
 	wFile := C.CString(n.WeightsFile)
 	defer C.free(unsafe.Pointer(wFile))
-
 	// GPU device ID must be set before `load_network()` is invoked.
 	C.cuda_set_device(C.int(n.GPUDeviceIndex))
 	n.cNet = C.load_network(nCfg, wFile, 0)
-
 	if n.cNet == nil {
 		return errUnableToInitNetwork
 	}
-
-	C.set_batch_network(n.cNet, 1)
 	C.srand(2222222)
-
+	n.hierarchalThreshold = 0.5
-	// Currently, hierarchal threshold is always 0.5.
+	n.nms = 0.45
-	n.hierarchalThreshold = .5
+	metadata := C.get_metadata(nCfg)
-
+	n.Classes = int(metadata.classes)
-	// Currently NMS is always 0.4.
+	n.ClassNames = makeClassNames(metadata.names, n.Classes)
-	n.nms = .4
-
-	n.Classes = int(C.get_network_layer_classes(n.cNet, n.cNet.n-1))
-	cClassNames := loadClassNames(n.DataConfigurationFile)
-	defer freeClassNames(cClassNames)
-	n.ClassNames = makeClassNames(cClassNames, n.Classes)
-
 	return nil
 }
 
@@ -70,34 +58,26 @@ func (n *YOLONetwork) Close() error {
 	if n.cNet == nil {
 		return errNetworkNotInit
 	}
-
+	C.free_network(*n.cNet)
-	C.free_network(n.cNet)
 	n.cNet = nil
 	return nil
 }
 
-// Detect specified image.
+// Detect specified image
-func (n *YOLONetwork) Detect(img *Image) (*DetectionResult, error) {
+func (n *YOLONetwork) Detect(img *DarknetImage) (*DetectionResult, error) {
 	if n.cNet == nil {
 		return nil, errNetworkNotInit
 	}
-
 	startTime := time.Now()
-	result := C.perform_network_detect(n.cNet, &img.image, C.int(n.Classes),
+	result := C.perform_network_detect(n.cNet, &img.image, C.int(n.Classes), C.float(n.Threshold), C.float(n.hierarchalThreshold), C.float(n.nms), C.int(0))
-		C.float(n.Threshold), C.float(n.hierarchalThreshold), C.float(n.nms))
 	endTime := time.Now()
-	defer C.free_detections(result.detections, result.detections_len)
+	ds := makeDetections(img, result.detections, int(result.detections_len), n.Threshold, n.Classes, n.ClassNames)
-
+	C.free_detections(result.detections, result.detections_len)
-	ds := makeDetections(img, result.detections, int(result.detections_len),
-		n.Threshold, n.Classes, n.ClassNames)
-
 	endTimeOverall := time.Now()
-
 	out := DetectionResult{
 		Detections:           ds,
 		NetworkOnlyTimeTaken: endTime.Sub(startTime),
 		OverallTimeTaken:     endTimeOverall.Sub(startTime),
 	}
-
 	return &out, nil
 }

network.h

@@ -8,4 +8,4 @@ struct network_box_result {
 };
 
 extern int get_network_layer_classes(network *n, int index);
-extern struct network_box_result perform_network_detect(network *n, image *img, int classes, float thresh, float hier_thresh, float nms);
+extern struct network_box_result perform_network_detect(network *n, image *img, int classes, float thresh, float hier_thresh, float nms, int letter_box);