aiom_pack/src/controllers/addon/dataUpload.js

Framework for interdependent (mcmc-like) behavioral experiments

// come into effect when the user set production to true in .env file
const { pool } = require('../../core/database');
const sharp = require('sharp');

exports.upload_files = async (req, res, next) => {
    try {
      const consentPublications = req.header('Consent-Publications');
      const pid = req.header('pid');
      if (consentPublications === 'false') {
        await pool.query(
          `UPDATE participants SET face_authorization = false WHERE participant = $1`,
          [pid]
        );
      }
      
      // Create images table if it doesn't exist
      await pool.query(`
        CREATE TABLE IF NOT EXISTS production (
          id SERIAL PRIMARY KEY,
          participant_id TEXT NOT NULL,
          image_name TEXT NOT NULL,
          image_data BYTEA NOT NULL,
          upload_date TIMESTAMP DEFAULT CURRENT_TIMESTAMP
        )
      `);
      const files = req.files.files;
      const filesArray = Array.isArray(files) ? files : [files];
      const MAX_SIZE_MB = 1; // Define max size in MB
      const MAX_SIZE_BYTES = MAX_SIZE_MB * 1024 * 1024;
      
      for (let i = 0; i < filesArray.length; i++) {
        const file = filesArray[i];
        let imageData = file.data;
        
        if (imageData.length > MAX_SIZE_BYTES) {
          let quality = 90;
          while (quality >= 40 && imageData.length > MAX_SIZE_BYTES) {
            try {
              imageData = await sharp(file.data)
                .jpeg({ quality })
                .toBuffer();
              quality -= 10;
            } catch (err) {
              console.error(`Error compressing ${file.name}:`, err);
              imageData = file.data; 
              break;
            }
          }
        }
        // Insert image into database
        const result = await pool.query(
          `INSERT INTO production (participant_id, image_name, image_data) 
          VALUES ($1, $2, $3) 
          RETURNING id`,
          [pid, file.name.split('.')[0], imageData]
        );
      }

      console.log(`Files uploaded successfully for participant ${pid}`);

      res.status(200).json({
        progress: 100,
        message: "Files uploaded successfully -- thank you!",
      });
    } catch (error) {
      next(error);
    }
  }