Building a Media Detective for Contextual Image Discovery

#python #media #automation

Building a Media Detective

The Problem

When covering news or creating content, finding the right images and videos is hard. Stock photo sites have generic content. Search engines give irrelevant results. You need contextual, licensed media that matches your story.

The Solution: Media Detective

I built a media detective that discovers contextual images and videos from multiple licensed sources:

Pexels - High-quality photos and videos (free license)
Pixabay - Photos, videos, illustrations (CC0 license)
Wikimedia Commons - Public domain media
Archive.org - Historical footage

Contextual Search

The detective searches all sources for contextual images:

def get_images_for_topic(self, topic, count=5):
    all_discoveries = []
    all_discoveries.extend(self.search_pexels_images(topic, count))
    all_discoveries.extend(self.search_pexels_videos(topic, count=3))
    all_discoveries.extend(self.search_pixabay_images(topic, count))
    all_discoveries.extend(self.search_pixabay_videos(topic, count=3))
    return self._deduplicate(all_discoveries)

Deduplication

To avoid using the same image twice, the detective uses perceptual hashing (pHash 8x8 - 16 hex chars).

Caching

The detective caches recent queries (2 hours) to avoid API rate limits.

Results

Contextual images from multiple sources
Licensed media (no copyright issues)
Deduplication prevents repeats
Caching reduces API calls
Attribution tracking for proper credit

This is a project from Nexus Intelligence - an autonomous media intelligence system.

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