Image Processor

Code example

This code uses the zendarAI.img() method to analyze images for objects, faces, text, trees, and animals. It enhances the image, detects specified elements, and handles errors. Detected results are logged, and a function simulates visualizing the analysis. The code processes multiple images and logs the findings.

const zendarAI = require('zendarai')

const imgprocessor = new zendarAI.img()

// Function to analyze the image and detect various elements
async function analyzeImage(image) {
  try {
    // Perform image analysis with object, face, text, tree, and animal detection
    const result = await imgprocessor.analyze(image, {
      detect: ['objects', 'faces', 'text', 'trees', 'animals'], // Elements to detect
      enhance: true // Enhance image quality before analysis
    })

    // If no result is found, handle the case
    if (!result) {
      console.log('No analysis result found. Please check the image.')
      return
    }

    // Output the detected elements
    console.log('Analysis complete:')
    console.log('Detected Objects:', result.objects || 'None detected')
    console.log('Detected Faces:', result.faces || 'None detected')
    console.log('Detected Text:', result.text || 'No text detected')
    console.log('Detected Trees:', result.trees || 'None detected')
    console.log('Detected Animals:', result.animals || 'None detected')

    // Further handling of the analysis results
    handleDetectedElements(result)

    return result
  } catch (error) {
    console.error('Error processing the image:', error)
    return 'Sorry, there was an error with the image analysis.'
  }
}

// Function to handle detected elements and take actions
function handleDetectedElements(result) {
  if (result.objects && result.objects.length > 0) {
    console.log('Objects detected:', result.objects)
  }
  
  if (result.faces && result.faces.length > 0) {
    console.log('Faces detected:', result.faces)
  }

  if (result.text && result.text.length > 0) {
    console.log('Text detected:', result.text)
  }

  if (result.trees && result.trees.length > 0) {
    console.log('Trees detected:', result.trees)
  }

  if (result.animals && result.animals.length > 0) {
    console.log('Animals detected:', result.animals)
  }
}

// Simulate image analysis with a sample image
const sampleImage = 'path/to/your/image.jpg' // Path to an example image
console.log('Starting image analysis...')
analyzeImage(sampleImage).then((result) => {
  console.log('Image analysis completed:', result)
}).catch((error) => {
  console.log('An error occurred during image analysis:', error)
})

// Simulate another image for additional analysis
const anotherImage = 'path/to/another/image.jpg' // Another example image
console.log('Starting second image analysis...')
analyzeImage(anotherImage).then((result) => {
  console.log('Second image analysis completed:', result)
}).catch((error) => {
  console.log('An error occurred during second image analysis:', error)
})

// Example function to visualize the results (pseudo-implementation for the demo)
function visualizeAnalysisResults(result) {
  // Example visualization, just a simulation of how results could be visualized
  console.log('Visualizing analysis results...')
  if (result.objects) {
    console.log('Drawing bounding boxes for objects...')
  }
  if (result.faces) {
    console.log('Drawing bounding boxes around faces...')
  }
  if (result.text) {
    console.log('Displaying detected text on image...')
  }
  // Other visualizations would go here, such as drawing trees or animals on the image
}

// Simulating visualization of analysis results
visualizeAnalysisResults({
  objects: ['Car', 'Building'],
  faces: ['Person1', 'Person2'],
  text: ['Welcome', 'to the Zoo']
})