I'm playing around with Google Vision autoML in react and I'm trying to figure out a way to change fs.readFileSync to an online url. I've used https, request and even url in node.js but I still can't figure out a way to make it read from a url source. Any help is appreciated, thank you
const projectId = "abc"
const location = "abc"
const modelId = "abc"
const filePath = "./test-pics/7.jpg"
const { PredictionServiceClient } = require("#google-cloud/automl").v1
const https = require("https")
const request = require("request")
const url = require("node:url")
const fs = require("fs")
const client = new PredictionServiceClient({
keyFilename: "./vision-private-key.json",
})
const imageURL = "https://cdn.filestackcontent.com/IJ0kViHQQyiwQTVaFH66"
// Read the file content for translation.
const content = fs.readFileSync(filePath)
const content1 = https.get(imageURL)
const content2 = request.get(
"https://cdn.filestackcontent.com/IJ0kViHQQyiwQTVaFH66"
)
async function predict() {
const request = {
name: client.modelPath(projectId, location, modelId),
payload: {
image: {
imageBytes: content,
},
},
}
const [response] = await client.predict(request)
for (const annotationPayload of response.payload) {
console.log(`type of vehicle: ${annotationPayload.displayName}`)
const carType = annotationPayload.displayName
console.log(carType)
}
}
predict()
Related
const IgApiClient = require('instagram-private-api').IgApiClient;
const fs = require('fs');
const config = require('./config.json');
const ig = new IgApiClient();
ig.state.generateDevice(config.instagramUsername);
ig.state.proxyUrl = config.igProxy;
async function uploadImage(imageBuffer) {
const imageUrl = await ig.upload.photo(
{
file: imageBuffer
}
);
console.log(`URL: ${imageUrl}`);
}
(async () => {
await ig.simulate.preLoginFlow();
const loggedInUser = await ig.account.login(config.instagramUsername, config.instagramPassword);
process.nextTick(async () => await ig.simulate.postLoginFlow());
const imageBuffer = fs.readFileSync('output.png');
uploadImage(imageBuffer);
})();
Error:
C:\Users\PC\Desktop\spotted\node_modules\instagram-private-api\dist\core\request.js:126
return new errors_1.IgResponseError(response);
^
IgResponseError: POST /rupload_igphoto/1672943340753_0_8268117741 - 400 Bad Request;
at Request.handleResponseError (C:\Users\PC\Desktop\spotted\node_modules\instagram-private-api\dist\core\request.js:126:16)
at Request.send (C:\Users\PC\Desktop\spotted\node_modules\instagram-private-api\dist\core\request.js:54:28)
at async UploadRepository.photo (C:\Users\PC\Desktop\spotted\node_modules\instagram-private-api\dist\repositories\upload.repository.js:18:26)
at async uploadImage (C:\Users\PC\Desktop\spotted\bomba.js:10:20)
Node.js v19.2.0
Hello, I've been trying to create an app, which will automatically post generated images on instagram, but there's a problem, it doesn't work even if i do it as it is intended in documentation (probably). Does anyone have any ideas?
I´m a Java Dev so I need help from NodeJS guys!
Task: create a script that retrieves '_id', 'document', and 'corporateName' from MongoDB, then take the retrieved '_id', and pass it as a parameter to an API request. The last part should be taking 'document', 'corporateName' + 'client_id', 'client_secret' and export it into a single csv file.
It might be a very simple script! Therefore I´ve done this till now:
const {MongoClient} = require('mongodb');
const uri = "mongodb+srv://<privateInfo>/";
const client = new MongoClient(uri);
async function run() {
try {
const database = client.db("merchant-profile");
const ecs = database.collection("merchant_wallet");
const api = `https://<prodAPI>/v1/merchant/wallet/${id}/oauth2`;
const ecOpt = {_id: 1, document: 1, corporateName: 1};
const credOpt = {client_id: 1, client_secret: 1};
const ec = ecs.find({}).project(ecOpt);
let id = ec.forEach(id => cred._id);
const cred = api.find({}).project(credOpt);
await cred.forEach(console.dir);
} finally {
await client.close();
}
}
run().catch(console.dir);
I´m trying to understand how can I take '_id' fetched in 'ec' and pass it as a param to the 'cred' call.
This would already be awesome!
If you could help me out with the CSV issue as well it would be perfect.
So I don´t want just the answer, but understand how to do this.
Thank you all in advance!
This is the way I found to do it:
const { default: axios } = require("axios");
const { MongoClient } = require("mongodb");
const uri = "mongodb+srv://admin:sLKJdsdRp4LrsVtLsnkR#pp-core-prd.fy3aq.mongodb.net/";
const client = new MongoClient(uri);
async function run() {
try {
const database = client.db("merchant-profile");
const ecs = database.collection("merchant_wallet");
const data = [];
await ecs.find({}).forEach(async function teste(response) {
const id = response._id;
const api = `https://api.pedepronto.com.br/v1/merchant/wallet/${id}/oauth2`;
try{
const res = await axios.get(api);
data.push({client_secret: res.data[0].client_secret, client_id: res.data[0].client_id})
}catch(e){
console.log(e);
}
})
} finally {
await client.close();
}
}
run().catch(console.dir);
It iterates over the find method and appends the fetched id to the uri.
I have created a nft and is listed in OpenSea. Now I am trying to create sell order of my item through opensea-js sdk. Unfortunately it is not working. Do not know where I am making a mistake. Also I am not sure on base derivation path. Below is my code to create sell order. Pls help me resolving this.
const opensea = require("opensea-js");
const OpenSeaPort = opensea.OpenSeaPort;
const Network = opensea.Network;
const MnemonicWalletSubprovider = require("#0x/subproviders")
.MnemonicWalletSubprovider;
const RPCSubprovider = require("web3-provider-engine/subproviders/rpc");
const Web3ProviderEngine = require("web3-provider-engine");
const MNEMONIC = "accuse never ....";
const NFT_CONTRACT_ADDRESS = "0x6C317E7dE3e8823BBc308a2912Ba6F24587fc167";
const OWNER_ADDRESS = "0x589a1532AAaE84e38345b58C11CF4697Ea89A866";
API_KEY = "";
const infuraRpcSubprovider = new RPCSubprovider({
rpcUrl: "https://rinkeby.infura.io/v3/c0e4482bdf9e4f539692666cd56ef6e4"
});
const BASE_DERIVATION_PATH = `44'/60'/0'/0`;
const mnemonicWalletSubprovider = new MnemonicWalletSubprovider({
mnemonic: MNEMONIC,
baseDerivationPath: BASE_DERIVATION_PATH,
chainId: 4
});
const providerEngine = new Web3ProviderEngine();
providerEngine.addProvider(mnemonicWalletSubprovider);
providerEngine.addProvider(infuraRpcSubprovider);
providerEngine.start();
const seaport = new OpenSeaPort(
providerEngine,
{
networkName: Network.Rinkeby,
apiKey: API_KEY,
},
(arg) => console.log(arg)
);
async function main() {
console.log("Auctioning an item for a fixed price...");
const fixedPriceSellOrder = await seaport.createSellOrder({
asset: {
tokenId: "3",
tokenAddress: NFT_CONTRACT_ADDRESS,
},
startAmount: 0.0001,
expirationTime: 0,
accountAddress: OWNER_ADDRESS,
}) ;
console.log("fixedPriceSellOrder") ;
}
main();
This has been resolved. I have changed the HDProvider to #truffle/hdwallet-provider. Now I could see the listing in opensea after createSellOrder through opensea-js.
This link helped me to get this resolved
Background
Using Google Vision API (with Node) to recognize Vietnamese text, the result is lacking quality. There are some (not all but some) tone markers as well as vowel signifies missing.
Compared to their online demo, which returns a decent result (scroll down for live demo):
https://cloud.google.com/vision/
(As I do not have a company account with them, I cannot ask Google directly.)
Question
Can I tweak my request to get better results?
I already set the language hint to "vi" and tried to combine it with "en". I also tried the more specific "vi-VN".
Example Image
https://www.tecc.org/Slatwall/custom/assets/images/product/default/cache/j056vt-_800w_800h_sb.jpg
Example Code
const fs = require("fs");
const path = require("path");
const vision = require("#google-cloud/vision");
async function quickstart() {
let text;
const fileName = "j056vt-_800w_800h_sb.jpg";
const imageFile = fs.readFileSync(fileName);
const image = Buffer.from(imageFile).toString("base64");
const client = new vision.ImageAnnotatorClient();
const request = {
image: {
content: image
},
imageContext: {
languageHints: ["vi", 'en']
}
};
const [result] = await client.textDetection(request);
for (const tmp of result.textAnnotations) {
text += tmp.description + '\n';
}
const out = path.basename(fileName, path.extname(fileName)) + ".txt";
fs.writeFileSync(out, text);
}
quickstart();
Solution
// $env:GOOGLE_APPLICATION_CREDENTIALS="[PATH]"
const fs = require("fs");
const path = require("path");
const vision = require("#google-cloud/vision");
async function quickstart() {
let text = '';
const fileName = "j056vt-_800w_800h_sb.jpg";
const imageFile = fs.readFileSync(fileName);
const image = Buffer.from(imageFile).toString("base64");
const client = new vision.ImageAnnotatorClient();
const request = {
image: {
content: image
},
imageContext: {
languageHints: ["vi-VN"]
}
};
const [result] = await client.documentTextDetection(request);
// OUTPUT METHOD A
for (const tmp of result.textAnnotations) {
text += tmp.description + "\n";
}
console.log(text);
const out = path.basename(fileName, path.extname(fileName)) + ".txt";
fs.writeFileSync(out, text);
// OUTPUT METHOD B
const fullTextAnnotation = result.fullTextAnnotation;
console.log(`Full text: ${fullTextAnnotation.text}`);
fullTextAnnotation.pages.forEach(page => {
page.blocks.forEach(block => {
console.log(`Block confidence: ${block.confidence}`);
block.paragraphs.forEach(paragraph => {
console.log(`Paragraph confidence: ${paragraph.confidence}`);
paragraph.words.forEach(word => {
const wordText = word.symbols.map(s => s.text).join("");
console.log(`Word text: ${wordText}`);
console.log(`Word confidence: ${word.confidence}`);
word.symbols.forEach(symbol => {
console.log(`Symbol text: ${symbol.text}`);
console.log(`Symbol confidence: ${symbol.confidence}`);
});
});
});
});
});
}
quickstart();
This question is already answered in this one.
In summary, the Demo is in this case probably using the DOCUMENT_TEXT_DETECTION, which can sometimes make a more thorough strings extraction, while you are using TEXT_DETECTION.
You can try to make a client.document_text_detection request instead of client.textDetection and you will probably get results closer to the Demo.
If you want to read to the related documentation you can find it here.
I hope this resolves your question!
I'm following a web scraping course that uses Cheerio. I practice on a different website then they use in the course and now I run into the problem that all my scraped text end up in one big object. But every title should end up in it's own object. Can someone see what I did wrong? I already bumbed my head 2 hours on this problem.
const request = require('request-promise');
const cheerio = require('cheerio');
const url = "https://huurgoed.nl/gehele-aanbod";
const scrapeResults = [];
async function scrapeHuurgoed() {
try {
const htmlResult = await request.get(url);
const $ = await cheerio.load(htmlResult);
$("div.aanbod").each((index, element) => {
const result = $(element).children(".item");
const title = result.find("h2").text().trim();
const characteristics = result.find("h4").text();
const scrapeResult = {title, characteristics};
scrapeResults.push(scrapeResult);
});
console.log(scrapeResults);
} catch(err) {
console.error(err);
}
}
scrapeHuurgoed();
This is the link to the repo: https://github.com/danielkroon/huurgoed-scraper/blob/master/index.js
Thanks!
That is because of the way you used selectors. I've modified your script to fetch the content as you expected. Currently the script is collecting titles and characteristics. Feel free to add the rest within your script.
This is how you can get the required output:
const request = require('request-promise');
const cheerio = require('cheerio');
const url = "https://huurgoed.nl/gehele-aanbod";
const scrapeResults = [];
async function scrapeHuurgoed() {
try {
const htmlResult = await request.get(url);
const $ = await cheerio.load(htmlResult);
$("div.item").each((index, element) => {
const title = $(element).find(".kenmerken > h2").text().trim();
const characteristics = $(element).find("h4").text().trim();
scrapeResults.push({title,characteristics});
});
console.log(scrapeResults);
} catch(err) {
console.error(err);
}
}
scrapeHuurgoed();