Use Cases

// n8n Workflow Example
// Trigger: New file in Google Drive
// Action 1: HTTP Request to ClipToFrame
{
  "videoUrl": "{{$json.webViewLink}}",
  "time": 30,  // Extract frame at 30 seconds
  "outputFormat": "jpg",
  "quality": 90,
  "maxWidth": 1280,
  "maxHeight": 720
}

// Action 2: Upload thumbnail to S3/CDN
// Action 3: Update database with thumbnail URL

// Python Example: Batch frame extraction + AI analysis
import requests
import openai

# Step 1: Extract frames using batch endpoint
batch_response = requests.post(
    'https://video-capture-api.onrender.com/capture/batch',
    headers={'x-api-key': 'YOUR_API_KEY'},
    json={
        'requests': [
            {'videoUrl': video_url, 'time': 10, 'outputFormat': 'png'},
            {'videoUrl': video_url, 'time': 30, 'outputFormat': 'png'},
            {'videoUrl': video_url, 'time': 60, 'outputFormat': 'png'},
        ]
    }
)

# Step 2: Analyze each frame with OpenAI Vision
for result in batch_response.json()['results']:
    if result['status'] == 'success':
        # Send frame to OpenAI Vision
        vision_response = openai.ChatCompletion.create(
            model="gpt-4-vision-preview",
            messages=[{
                "role": "user",
                "content": [
                    {"type": "text", "text": "Describe this video frame and identify any objects, people, or text."},
                    {"type": "image_url", "image_url": {"url": result['imageUrl']}}
                ]
            }]
        )
        print(f"Frame at {result['index']}: {vision_response.choices[0].message.content}")

// Node.js Example: Video monitoring with change detection
const axios = require('axios');
const sharp = require('sharp');

async function monitorVideo(videoUrl, timestamp) {
  // Extract current frame
  const response = await axios.post(
    'https://video-capture-api.onrender.com/capture',
    {
      videoUrl: videoUrl,
      time: timestamp,
      outputFormat: 'png'
    },
    { headers: { 'x-api-key': process.env.API_KEY } }
  );

  const currentFrame = await axios.get(response.data.imageUrl, { responseType: 'arraybuffer' });
  const currentImage = await sharp(currentFrame.data);

  // Load baseline frame (from previous check)
  const baselineImage = await sharp('baseline_frame.png');

  // Compare images
  const { data: currentData } = await currentImage.raw().toBuffer({ resolveWithObject: true });
  const { data: baselineData } = await baselineImage.raw().toBuffer({ resolveWithObject: true });

  // Simple pixel difference check
  let differences = 0;
  for (let i = 0; i < currentData.length; i += 4) {
    const diff = Math.abs(currentData[i] - baselineData[i]);
    if (diff > 10) differences++; // Threshold for change detection
  }

  const changePercent = (differences / (currentData.length / 4)) * 100;

  if (changePercent > 5) {
    // Significant change detected
    console.log(`Change detected: ${changePercent.toFixed(2)}% difference`);
    // Send alert, update baseline, etc.
  }

  // Update baseline
  await currentImage.toFile('baseline_frame.png');
}