Merge pull request #4 from terorie/refactor

Refactor of the project + output feature

Author: CorentinB

.gitignore

@@ -0,0 +1,8 @@
+# Executable builds
+/deepsort
+/cmd/deepsort/deepsort
+deepsort.exe
+
+# OS files
+desktop.ini
+.DS_Store

.travis.yml

@@ -1,5 +1,3 @@
 language: go
 go:
-- "1.10.2"
-
-before_script: cd cmd/deepsort/
+- "1.10.2"

README.md

@@ -21,9 +21,9 @@ Right now, the only supported installation of DeepDetect that works with DeepSor
 
 Then, download the latest DeepSort release from https://github.com/CorentinB/DeepSort/releases
 
-Unzip your release, rename it `deepsort` and make it executable with:
+Unzip your release, rename it `DeepSort` and make it executable with:
 ```
-chmod +x deepsort
+chmod +x DeepSort
 ```
 
 # Usage
@@ -34,10 +34,10 @@ DeepSort support few different parameters, you're obliged to fill two of them:
 
 For more informations, refeer to the helper:
 ```
-./deepsort --help
+./DeepSort --help
 
 [-u|--url] is required
-usage: deepsort [-h|--help] -u|--url "<value>" -i|--input "<value>"
+usage: DeepSort [-h|--help] -u|--url "<value>" -i|--input "<value>"
                 [-n|--network (resnet-50|googlenet)] [-R|--recursive]
                 [-j|--jobs <integer>] [-d|--dry-run]
 

arguments.go

@@ -0,0 +1,86 @@
+package main
+
+import (
+	"fmt"
+	"os"
+	"path/filepath"
+
+	"github.com/akamensky/argparse"
+)
+
+var arguments = struct {
+	Input        string
+	Output       string
+	URL          string
+	DryRun       bool
+	Recursive    bool
+	Jobs         int
+	Network      string
+}{
+	// Default arguments
+	Jobs: 1,
+}
+
+func argumentParsing(args []string) {
+	// Create new parser object
+	parser := argparse.NewParser("deepsort", "AI powered image tagger backed by DeepDetect")
+
+	// Create flags
+	URL := parser.String("u", "url", &argparse.Options{
+		Required: true,
+		Help: "URL of your DeepDetect instance (i.e: http://localhost:8080)"})
+
+	input := parser.String("i", "input", &argparse.Options{
+		Required: true,
+		Help: "Your input folder."})
+
+	output := parser.String("o", "output", &argparse.Options{
+		Required: false,
+		Help: "Your output folder, if output is set, " +
+			"original files will not be renamed, " +
+			"but the renamed version will be copied in the output folder."})
+
+	network := parser.Selector("n", "network", []string{"resnet-50", "googlenet"}, &argparse.Options{
+		Required: false,
+		Help: "The pre-trained deep neural network you want to use, " +
+			"can be resnet-50 or googlenet",
+		Default: "resnet-50"})
+
+	recursive := parser.Flag("R", "recursive", &argparse.Options{
+		Required: false,
+		Help: "Process files recursively."})
+
+	jobs := parser.Int("j", "jobs", &argparse.Options{
+		Required: false,
+		Help: "Number of parallel jobs",
+		Default: 1})
+
+	dryRun := parser.Flag("d", "dry-run", &argparse.Options{
+		Required: false,
+		Help: "Just classify images and return results, do not apply."})
+
+	// Parse input
+	err := parser.Parse(args)
+	if err != nil {
+		// In case of error print error and print usage
+		// This can also be done by passing -h or --help flags
+		fmt.Print(parser.Usage(err))
+		os.Exit(0)
+	}
+
+	// Convert path parameters to absolute paths
+	inputFolder, _ := filepath.Abs(*input)
+	var outputFolder string
+	if *output != "" {
+		outputFolder, _ = filepath.Abs(*output)
+	}
+
+	// Finally save the collected flags
+	arguments.Network = *network
+	arguments.Jobs = *jobs
+	arguments.DryRun = *dryRun
+	arguments.Recursive = *recursive
+	arguments.Input = inputFolder
+	arguments.Output = outputFolder
+	arguments.URL = *URL
+}

classify.go

@@ -0,0 +1,44 @@
+package main
+
+import (
+	"encoding/base64"
+	"net/http"
+	"strings"
+	"io/ioutil"
+	"github.com/savaki/jq"
+)
+
+// Classify runs the image through the classification engine and
+// returns a slice of tags
+func (c *ClassificationService) Classify(image []byte) ([]string, error) {
+	url := c.URL + "/predict"
+
+	// Send image over as base64
+	dataStr := base64.StdEncoding.EncodeToString(image)
+
+	req, err := http.NewRequest("POST", url, strings.NewReader(`{
+		"service": "` + c.ID+ `",
+		"parameters": {
+			"input": {
+				"width":224,
+				"height":224
+			},
+			"output": { "best":1 },
+			"mllib": { "gpu":false }
+		},
+		"data":["` + dataStr + `"]
+	}`))
+
+	resp, err := c.Conn.Do(req)
+	if err != nil { return nil, err }
+	defer resp.Body.Close()
+
+	body, _ := ioutil.ReadAll(resp.Body)
+
+	tagsJSON, _ := jq.Parse(".body.predictions.[0].classes.[0].cat")
+	value, _ := tagsJSON.Apply(body)
+	class := strings.Split(string(value), " ")
+	class = class[1:]
+
+	return class, nil
+}