The Code Wizards - AI FACE DETECTION

Backend/.env.sample

@@ -0,0 +1,17 @@
+#JWT
+APP_PORT=9000
+
+#PREFIX app path
+APP_PRIFIX_PATH=/APP_PRIFIX_PATH
+
+#JWT
+JWT_SECRET=APLHABETAGAMA
+
+JWT_EXPIRE=1y
+
+# Database config
+
+# If you want to use database URI with DB_URI
+DB_URI=
+DB_USERNAME=admin
+DB_PASSWORD=admin

Backend/.gitignore

@@ -0,0 +1,104 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+lerna-debug.log*
+
+# Diagnostic reports (https://nodejs.org/api/report.html)
+report.[0-9]*.[0-9]*.[0-9]*.[0-9]*.json
+
+# Runtime data
+pids
+*.pid
+*.seed
+*.pid.lock
+
+# Directory for instrumented libs generated by jscoverage/JSCover
+lib-cov
+
+# Coverage directory used by tools like istanbul
+coverage
+*.lcov
+
+# nyc test coverage
+.nyc_output
+
+# Grunt intermediate storage (https://gruntjs.com/creating-plugins#storing-task-files)
+.grunt
+
+# Bower dependency directory (https://bower.io/)
+bower_components
+
+# node-waf configuration
+.lock-wscript
+
+# Compiled binary addons (https://nodejs.org/api/addons.html)
+build/Release
+
+# Dependency directories
+node_modules/
+jspm_packages/
+
+# TypeScript v1 declaration files
+typings/
+
+# TypeScript cache
+*.tsbuildinfo
+
+# Optional npm cache directory
+.npm
+
+# Optional eslint cache
+.eslintcache
+
+# Microbundle cache
+.rpt2_cache/
+.rts2_cache_cjs/
+.rts2_cache_es/
+.rts2_cache_umd/
+
+# Optional REPL history
+.node_repl_history
+
+# Output of 'npm pack'
+*.tgz
+
+# Yarn Integrity file
+.yarn-integrity
+
+# dotenv environment variables file
+.env
+.env.test
+
+# parcel-bundler cache (https://parceljs.org/)
+.cache
+
+# Next.js build output
+.next
+
+# Nuxt.js build / generate output
+.nuxt
+dist
+
+# Gatsby files
+.cache/
+# Comment in the public line in if your project uses Gatsby and *not* Next.js
+# https://nextjs.org/blog/next-9-1#public-directory-support
+# public
+
+# vuepress build output
+.vuepress/dist
+
+# Serverless directories
+.serverless/
+
+# FuseBox cache
+.fusebox/
+
+# DynamoDB Local files
+.dynamodb/
+
+# TernJS port file
+.tern-port

Backend/.vscode/c_cpp_properties.json

@@ -0,0 +1,21 @@
+{
+    "configurations": [
+        {
+            "name": "Win32",
+            "includePath": [
+                "${workspaceFolder}/**"
+            ],
+            "defines": [
+                "_DEBUG",
+                "UNICODE",
+                "_UNICODE"
+            ],
+            "windowsSdkVersion": "10.0.22000.0",
+            "compilerPath": "C:/Program Files (x86)/Microsoft Visual Studio/2019/BuildTools/VC/Tools/MSVC/14.29.30133/bin/Hostx64/x64/cl.exe",
+            "cStandard": "c17",
+            "cppStandard": "c++17",
+            "intelliSenseMode": "windows-msvc-x64"
+        }
+    ],
+    "version": 4
+}

Backend/abhi.py

@@ -0,0 +1,206 @@
+import cv2
+import matplotlib.pyplot as plt
+from deepface import DeepFace
+import numpy as np
+import os
+from moviepy.editor import VideoFileClip
+import pandas as pd
+from keras.preprocessing.image import ImageDataGenerator
+from keras.utils import load_img,img_to_array
+
+path = r"Backend\\uploads"
+path1= r"Backend\\thief"
+storepath=r"Frontend\\src\\Components\\Images"
+storepath1=r"Frontend\\src\\Components\\imagesThief"
+dbpath=r"Backend\\intermediate"
+dbpath1=r"Backend\\thief_data"
+aug_in=r"Backend\\augmentation"
+aug_out=r"Frontend\\src\\Components\\augmented"
+
+def prediction_and_write(imgpath1):
+    fps=imagegenerator()
+    imgpath= r"Backend\\uploads\\" + imgpath1[0]
+    dbpath2=dbpath
+    storepath=r"Frontend\\src\\Components\\Images"
+    remove(storepath)
+
+    recognition = DeepFace.find(
+        img_path=imgpath, db_path=r"Backend\\intermediate", enforce_detection=False)
+    print(recognition)
+    n = 1
+    arr=[]
+    for i in recognition[0].identity:
+        print(i)
+        pred_img = cv2.imread(i)
+        x=i.replace(dbpath,'')
+        x=x.replace(r".jpg",'')
+        x=x.replace(r'/','')
+        x=x.replace(r'\\','')
+
+        num=0 #this will store the frame number , after extracting from name of file
+
+        file_name_len=len(x)
+        j=file_name_len-1
+
+        while j>=0:
+            if x[j]>='0' and x[j]<='9':
+                num=(num*10)+int(x[j])
+            j-=1
+
+        #reversing the number
+
+        x=int(str(num)[::-1])
+
+        x=int(x/fps)
+
+        arr.append(x)
+        grayf = cv2.cvtColor(pred_img, cv2.COLOR_BGR2RGB)
+        resizedf = cv2.resize(grayf, (100, 100))
+        normalized = resizedf/255
+        reshapedf = np.reshape(normalized, (100, 100, 3))
+        img=imgpath1[0].replace(".jpg",'')
+        name = storepath+"\\"+ img +"_"+str(x)+".jpg"
+        plt.imsave(name, reshapedf)
+    os.remove(imgpath)
+    os.chdir(r"Frontend\\src\\Components\\Images")
+    lst=os.listdir()
+    i=0
+    while i<len(lst)-5:
+        os.remove(lst[i])
+        i=i+1
+    os.chdir(r"..\\..\\..\\..")
+    remove(dbpath2)
+
+def infinite_run():
+    while (1):
+        path = r"Backend\\uploads"
+        if (len(os.listdir(path)) == 0 and len(os.listdir(path1))==0 and len(os.listdir(aug_in))==0):
+            count=1
+        elif (len(os.listdir(path)) != 0):
+            r=os.listdir(path)
+            remove(storepath)
+            prediction_and_write(r)
+        elif(len(os.listdir(path1))!=0):
+            r=os.listdir(path1)
+            remove(storepath1)
+            prediction_and_write_thief(r)
+        elif(len(os.listdir(aug_in))!=0):
+            r=os.listdir(aug_in)
+            remove(aug_out)
+            # print(r)
+            augmentation(r)
+
+def remove(path):
+    matter=os.listdir(path)
+    for i in matter:
+        if(i=="representations_vgg_face.pkl"):
+            continue
+        i=path+"\\"+i
+        os.remove(i)
+
+
+def imagegenerator():
+    cam=VideoFileClip(r"Backend\\Video\\WhatsApp Video 2023-02-04 at 6.23.15 PM.mp4")
+    dur=int(cam.duration)
+    cam = cv2.VideoCapture(r"Backend\\Video\\WhatsApp Video 2023-02-04 at 6.23.15 PM.mp4")
+    currentframe = 1
+    while (True):
+        ret, frame = cam.read()
+        if ret:
+            name = r"Backend\\intermediate\\" + str(currentframe) + '.jpg'
+            plt.imsave(name, frame)
+            currentframe += 1
+        else:
+            break
+    cam.release()
+    fps=int(currentframe/dur)
+    cv2.destroyAllWindows()
+    # print(dur)
+    # print(currentframe)
+    # print(fps)
+    return fps
+
+def textfilegen(recognition):
+    df=pd.DataFrame(recognition[0])
+    no=df.shape[0]
+    text_file = open(r"Backend\\test.txt", "w")
+    lis=[]
+    for k in range(no):
+        y=df['identity'][k]
+        new_str = ""
+        i=1
+
+        for c in reversed(y):
+            if c == '/':
+                break
+                i=i+1
+            elif i>4:
+                new_str= new_str+c
+                i=i+1
+            else:
+                i=i+1
+        txt = new_str[::-1]
+        lis.append(txt)
+
+    print(lis)
+    lis1=[]
+    for j in lis:
+        res = ''.join([i for i in j if not i.isdigit()])
+        lis1.append(res)
+
+    indexes = np.unique(lis1, return_index=True)[1]
+    lis1=[lis1[index] for index in sorted(indexes)]
+
+    file1 = open(r"Backend\\test.txt","w")
+    for i in lis1:
+        file1.write(i +"\n")
+
+
+
+    file1.close()
+
+def prediction_and_write_thief(imagepath1):
+    imgpath=path1 + "\\" + imagepath1[0]
+    print(imgpath)
+    dbpath=dbpath1
+    print(dbpath)
+    strpath=storepath1
+    recognition = DeepFace.find(
+        img_path= imgpath, db_path=dbpath, enforce_detection=False)
+    print(recognition)
+    n = 1
+    for i in recognition[0].identity:
+        pred_img = cv2.imread(i)
+        grayf = cv2.cvtColor(pred_img, cv2.COLOR_BGR2RGB)
+        resizedf = cv2.resize(grayf, (100, 100))
+        normalized = resizedf/255
+        reshapedf = np.reshape(normalized, (100, 100, 3))
+        name = strpath+"\\" + str(n)+ ".jpg"
+        n=n+1
+        plt.imsave(name, reshapedf)
+    os.remove(imgpath)
+    textfilegen(recognition)
+
+
+def augmentation(imgp):
+    datagen=ImageDataGenerator(rotation_range=30,width_shift_range=0.2,height_shift_range=0.2,rescale=1./255,shear_range=0.2,zoom_range=0.2,horizontal_flip=True,fill_mode='nearest')
+    img_path=aug_in + "\\" + imgp[0]
+    # i=os.listdir(img_path)
+    pic=load_img(img_path)
+    data_path=aug_out
+    pic.getpixel
+    pic_array=img_to_array(pic)
+    pic_array=cv2.resize(pic_array,(200,200))
+    print(pic_array.shape)
+    pic_array= pic_array.reshape(1,*pic_array.shape)
+    count=0
+    for batch in datagen.flow(pic_array,batch_size=5,save_to_dir=data_path,save_prefix='shas'): 
+        count+=1
+        if(count==10):
+            break
+    os.remove(img_path)
+
+
+infinite_run()
+
+

Backend/app.js

@@ -0,0 +1,33 @@
+import express, { application }  from "express"
+import  dotenv  from "dotenv"
+import bodyParser from 'body-parser'
+import connectDB from "./config/db.js"
+import cors from 'cors'
+dotenv.config();
+const app=express()
+app.use(cors());
+import cookieParser from "cookie-parser"
+
+//cookies and filemiddleware
+app.use(cookieParser())
+
+// morgan middlewares
+import morgan from "morgan"
+app.use(morgan("tiny"))
+app.use(bodyParser.raw({ type: 'application/octet-stream' }));
+
+// regular middlewares
+app.use(express.json())
+app.use(express.urlencoded({extended:true}));
+
+app.use(bodyParser.json());
+app.use(express.static('public')); 
+app.use('/images', express.static('images'));
+app.use(bodyParser.urlencoded());
+// import all routes here
+import userRoutes from "./routes/userRoutes.js"
+import eventRoutes from "./routes/eventRoutes.js"
+// router middleware
+app.use("/api/user",userRoutes);
+app.use("/api/upload",eventRoutes);
+export default app;