REVERSE SEARCH 2 ORB EDITION

This commit is contained in:
qwertyforce 2020-11-05 22:17:21 +03:00
parent 782e1f4d9e
commit 5ce3eb0990
7 changed files with 170 additions and 54 deletions

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@ -22,30 +22,33 @@ export default function ReverseSearch() {
const router = useRouter() const router = useRouter()
const [Files, setFiles] = useState([]); const [Files, setFiles] = useState([]);
const [open, setOpen] = useState(false); const [open, setOpen] = useState(false);
const send_image = (token: string) => { const send_image = (token: string,mode:string) => {
setOpen(true) setOpen(true)
const formData = new FormData(); const formData = new FormData();
formData.append("image", Files[0]); formData.append("image", Files[0]);
formData.append("g-recaptcha-response", token); formData.append("g-recaptcha-response", token);
formData.append("mode", mode);
axios(`/reverse_search`, { axios(`/reverse_search`, {
method: "post", method: "post",
data: formData, data: formData,
headers: { headers: {
'Content-Type': 'multipart/form-data' 'Content-Type': 'multipart/form-data'
} },
timeout:120000 //2min
}).then((resp) => { }).then((resp) => {
setOpen(false) setOpen(false)
console.log(resp.data.ids)
router.push("/show?ids=" + resp.data.ids) router.push("/show?ids=" + resp.data.ids)
}).catch((err) => { }).catch((err) => {
setOpen(false) setOpen(false)
console.log(err) console.log(err)
}) })
} }
const _send_image = () => { const _send_image = (mode:string) => {
/*global grecaptcha*/ // defined in pages/_document.tsx /*global grecaptcha*/ // defined in pages/_document.tsx
grecaptcha.ready(function () { grecaptcha.ready(function () {
grecaptcha.execute(config.recaptcha_site_key, { action: 'login' }).then(function (token) { grecaptcha.execute(config.recaptcha_site_key, { action: 'login' }).then(function (token) {
send_image(token) send_image(token,mode)
}); });
}) })
} }
@ -64,7 +67,9 @@ export default function ReverseSearch() {
onChange={(files) => setFiles((files as never))} onChange={(files) => setFiles((files as never))}
/> />
</Box> </Box>
<Button onClick={() => { _send_image() }} variant="contained" color="primary" >Reverse Search</Button> <Button onClick={() => { _send_image("1") }} variant="contained" color="primary" >Reverse Search (fast, less accureate)</Button>
<div style={{marginTop:"10px"}}><Button onClick={() => { _send_image("2") }} variant="contained" color="primary" >Reverse Search (slow, more accurate)</Button></div>
</div> </div>
); );
} }

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@ -0,0 +1,36 @@
import * as cv from 'opencv4nodejs'
import path from 'path';
import db_ops from '../helpers/db_ops'
import config from '../../config/config'
const detector=new cv.ORBDetector()
const PATH_TO_IMAGES = path.join(config.root_path, 'public', 'images')
async function calculate_orb_features(){
const images = await db_ops.image_ops.get_all_images()
for(const image of images){
const check_if_already_calculated= await db_ops.image_search.get_orb_features_by_id(image.id)
if(check_if_already_calculated.length!==0){
continue
}
console.log(image.id)
try{
const img = await cv.imreadAsync(`${PATH_TO_IMAGES}/${image.id}.${image.file_ext}`);
const keyPoints = await detector.detectAsync(img);
const descriptors = await detector.computeAsync(img, keyPoints);
const descriptors_as_array=descriptors.getDataAsArray()
descriptors.release()
img.release()
await db_ops.image_search.add_orb_features_by_id(image.id,descriptors_as_array)
}catch(err){
console.log(err)
console.log(image.id)
}
}
}
async function run() {
await calculate_orb_features()
process.exit()
}
run()

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@ -0,0 +1,11 @@
import db_ops from '../helpers/db_ops'
async function delete_orb_feature_by_id() {
// const color_hist_image_ids=[]
const similarities_image_ids=[-1]
for (const id of similarities_image_ids){
await db_ops.image_search.delete_orb_feature_by_id(id)
}
process.exit()
}
delete_orb_feature_by_id()

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@ -1,29 +0,0 @@
import * as cv from 'opencv4nodejs'
import path from 'path';
import db_ops from '../helpers/db_ops'
import config from '../../config/config'
const detector=new cv.SIFTDetector({ nFeatures: 400 })
const PATH_TO_IMAGES = path.join(config.root_path, 'public', 'images')
async function calculate_color_hist(){
const images = await db_ops.image_ops.get_all_images()
for(const image of images){
const check_if_already_calculated= await db_ops.image_search.get_sift_features_by_id(image.id)
if(check_if_already_calculated.length!==0){
continue
}
console.log(image.id)
const img = await cv.imreadAsync(`${PATH_TO_IMAGES}/${image.id}.${image.file_ext}`);
const keyPoints = await detector.detectAsync(img);
const descriptors = await detector.computeAsync(img, keyPoints);
descriptors.release()
img.release()
const descriptors_as_array=descriptors.getDataAsArray()
await db_ops.image_search.add_sift_features_by_id(image.id,descriptors_as_array)
}
}
async function run() {
await calculate_color_hist()
}
run()

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@ -91,6 +91,36 @@ async function generate_id() {
} }
/////////////////////////////////////////////////IMAGE SEARCH OPS /////////////////////////////////////////////////IMAGE SEARCH OPS
async function delete_orb_feature_by_id(id:number){
removeDocument("orb_reverse_search",{id:id})
}
async function add_orb_features_by_id(id:number,orb_features:Array<any>){
insertDocuments("orb_reverse_search", [{
id:id,
orb_features:orb_features
}])
}
async function get_orb_features_batch(skip:number,limit:number){
const collection = client.db(db_main).collection("orb_reverse_search");
const similarities = collection.find().skip(skip).limit(limit).project({_id:0}).toArray()
return similarities
}
async function get_orb_features_by_id(id:number){
const collection = client.db(db_main).collection("orb_reverse_search");
const similarities = collection.find({id:id}).project({_id:0,id:0}).toArray()
return similarities
}
async function get_number_of_images_orb_reverse_search(){
const collection = client.db(db_main).collection("orb_reverse_search");
const number_of_images_in_collection = collection.countDocuments()
return number_of_images_in_collection
}
async function get_color_similarities_by_id(id:number){ async function get_color_similarities_by_id(id:number){
const collection = client.db(db_main).collection("color_similarities"); const collection = client.db(db_main).collection("color_similarities");
// collection.find(selector).project({_id:0}).explain((_err,exp)=>console.log(exp)) // collection.find(selector).project({_id:0}).explain((_err,exp)=>console.log(exp))
@ -364,6 +394,11 @@ export default {
add_tags_to_image_by_id add_tags_to_image_by_id
}, },
image_search:{ image_search:{
delete_orb_feature_by_id,
add_orb_features_by_id,
get_orb_features_batch,
get_orb_features_by_id,
get_number_of_images_orb_reverse_search,
get_all_color_hists, get_all_color_hists,
get_color_hist_by_id, get_color_hist_by_id,
add_color_hist_by_id, add_color_hist_by_id,

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@ -1,6 +1,12 @@
/* eslint-disable @typescript-eslint/no-var-requires */
import * as cv from 'opencv4nodejs' import * as cv from 'opencv4nodejs'
import { HistAxes } from 'opencv4nodejs'; import { HistAxes } from 'opencv4nodejs';
import db_ops from './db_ops'; import db_ops from './db_ops';
const detector=new cv.ORBDetector()
const matchFunc=cv.matchBruteForceHammingAsync
const imghash = require('imghash');
const BIN_SIZE=16 const BIN_SIZE=16
const histAxes:HistAxes[]= [ const histAxes:HistAxes[]= [
new HistAxes({ new HistAxes({
@ -19,6 +25,7 @@ const histAxes:HistAxes[]= [
ranges: [0, 255] ranges: [0, 255]
}), }),
] ]
async function calculate_color_hist_and_similarities(new_image_id:number,image:Buffer){ async function calculate_color_hist_and_similarities(new_image_id:number,image:Buffer){
const img_mat = await cv.imdecodeAsync(image) const img_mat = await cv.imdecodeAsync(image)
let rgb_hist = await cv.calcHistAsync(img_mat, histAxes) let rgb_hist = await cv.calcHistAsync(img_mat, histAxes)
@ -39,4 +46,58 @@ const histAxes:HistAxes[]= [
} }
await db_ops.image_search.add_color_similarities_by_id(new_image_id,similarities) await db_ops.image_search.add_color_similarities_by_id(new_image_id,similarities)
} }
export default {calculate_color_hist_and_similarities} async function get_similar_images_by_orb(image:Buffer) {
const img_mat = await cv.imdecodeAsync(image)
const keyPoints = await detector.detectAsync(img_mat);
const img_descriptors = await detector.computeAsync(img_mat, keyPoints);
const number_of_images = await db_ops.image_search.get_number_of_images_orb_reverse_search()
const batch = 500;
const similar_images=[]
console.time()
for (let i = 0; i < number_of_images; i += batch) {
const descriptors = await db_ops.image_search.get_orb_features_batch(i, batch)
for (const img of descriptors) {
const descriptors2 = new cv.Mat(img.orb_features, cv.CV_8UC1)
const matches = await matchFunc(img_descriptors, descriptors2);
descriptors2.release()
let sum = 0
for (const x of matches) {
sum += x.distance
}
if (sum===0){
return [img.id]
}
similar_images.push({id:img.id,avg_distance:sum / matches.length})
}
}
console.timeEnd()
similar_images.sort((a,b)=>a.avg_distance-b.avg_distance)
similar_images.length=30
const ids=similar_images.map((el)=>el.id)
return ids
}
function hamming_distance(str1: string, str2: string) {
let distance = 0;
for (let i = 0; i < str1.length; i += 1) {
if (str1[i] !== str2[i]) {
distance += 1;
}
}
return distance;
}
async function get_similar_images_by_phash(image:Buffer){
const phash= await imghash.hash(image,16)
const images=await db_ops.image_ops.get_ids_and_phashes()
for(let i=0;i<images.length;i++){
images[i].dist=hamming_distance(phash,images[i].phash)
if(images[i].dist===0){
return [images[i].id]
}
}
images.sort((a,b)=>a.dist-b.dist)
images.length=30
const ids=images.map((el)=>el.id)
return ids
}
export default {calculate_color_hist_and_similarities,get_similar_images_by_orb,get_similar_images_by_phash}

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@ -3,17 +3,8 @@
// import db_ops from './../helpers/db_ops' // import db_ops from './../helpers/db_ops'
import { Request, Response } from 'express'; import { Request, Response } from 'express';
import { RecaptchaResponseV3 } from 'express-recaptcha/dist/interfaces'; import { RecaptchaResponseV3 } from 'express-recaptcha/dist/interfaces';
import db_ops from '../helpers/db_ops' import image_ops from '../helpers/image_ops'
const imghash: any = require('imghash');
function hamming_distance(str1: string, str2: string) {
let distance = 0;
for (let i = 0; i < str1.length; i += 1) {
if (str1[i] !== str2[i]) {
distance += 1;
}
}
return distance;
}
async function reverse_search(req: Request, res: Response) { async function reverse_search(req: Request, res: Response) {
const recaptcha_score=(req.recaptcha as RecaptchaResponseV3)?.data?.score const recaptcha_score=(req.recaptcha as RecaptchaResponseV3)?.data?.score
if (req.recaptcha?.error|| (typeof recaptcha_score==="number" && recaptcha_score<0.5)) { if (req.recaptcha?.error|| (typeof recaptcha_score==="number" && recaptcha_score<0.5)) {
@ -21,15 +12,21 @@ async function reverse_search(req: Request, res: Response) {
message: "Captcha error" message: "Captcha error"
}); });
} }
const phash= await imghash.hash(req.file.buffer,16)
const images=await db_ops.image_ops.get_ids_and_phashes() if(req.file){
for(let i=0;i<images.length;i++){ const Mode=parseInt(req.body.mode)
images[i].dist=hamming_distance(phash,images[i].phash) req.setTimeout(120000)//2min
if(Mode===1){
const ids=await image_ops.get_similar_images_by_phash(req.file.buffer)
console.log(ids)
res.json({ids:ids.join(',')})
}else if(Mode===2){
const ids=await image_ops.get_similar_images_by_orb(req.file.buffer)
console.log(ids)
res.json({ids:ids.join(',')})
}
} }
images.sort((a,b)=>a.dist-b.dist)
images.length=30
const ids=images.map((el)=>el.id)
res.json({ids:ids.join(',')})
} }
export default reverse_search; export default reverse_search;