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video-ad-analyzer

Extract and analyze content from video ads using Gemini Vision AI. Supports frame extraction, OCR text detection, audio transcription, and AI-powered scene analysis. Use when analyzing video creative content, extracting text overlays, or generating scene-by-scene descriptions.

fortytwode0 source installs☆ 0 Repository starsv1.0.0

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

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skillhub install fortytwode/meta-video-ad-analyzer

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Skill instructions

Video Ad Analyzer

AI-powered video content extraction using Google Gemini Vision.

What This Skill Does

  • Frame Extraction: Smart sampling with scene change detection
  • OCR Text Detection: Extract text overlays using EasyOCR
  • Audio Transcription: Convert speech to text with Google Cloud Speech
  • AI Scene Analysis: Describe each scene using Gemini Vision
  • Native Video Analysis: Direct video understanding for longer content
  • Thumbnail Generation: Auto-generate thumbnails from first frame

Setup

1. Environment Variables
# Required for Gemini Vision
GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json

# Required for audio transcription
# (same service account needs Speech-to-Text API enabled)
2. Dependencies
pip install opencv-python pillow easyocr ffmpeg-python google-cloud-speech vertexai google-api-python-client

Also requires ffmpeg and ffprobe installed on system.

Usage

Basic Video Analysis
from scripts.video_extractor import VideoExtractor
from scripts.models import ExtractedVideoContent
import vertexai
from vertexai.generative_models import GenerativeModel

# Initialize Vertex AI
vertexai.init(project="your-project-id", location="us-central1")
gemini_model = GenerativeModel("gemini-1.5-flash")

# Create extractor
extractor = VideoExtractor(gemini_model=gemini_model)

# Analyze video
result = extractor.extract_content("/path/to/video.mp4")

print(f"Duration: {result.duration}s")
print(f"Scenes: {len(result.scene_timeline)}")
print(f"Text overlays: {len(result.text_timeline)}")
print(f"Transcript: {result.transcript[:200]}...")
Extract Only Frames
frames, timestamps, text_timeline, scene_timeline, thumbnail = extractor.extract_smart_frames(
    "/path/to/video.mp4",
    scene_interval=2,    # Check for scene changes every 2s
    text_interval=0.5    # Check for text every 0.5s
)
Analyze Images
# Works with images too
resu...

Source information

Source
github
Repository
openclaw/skills
Path
skills/fortytwode/meta-video-ad-analyzer
Version
1.0.0
Commit
40b8c349b7de4c985d627f217e05392ac536bde6
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# Video Ad Analyzer

AI-powered video content extraction using Google Gemini Vision.

## What This Skill Does

- **Frame Extraction**: Smart sampling with scene change detection
- **OCR Text Detection**: Extract text overlays using EasyOCR
- **Audio Transcription**: Convert speech to text with Google Cloud Speech
- **AI Scene Analysis**: Describe each scene using Gemini Vision
- **Native Video Analysis**: Direct video understanding for longer content
- **Thumbnail Generation**: Auto-generate thumbnails from first frame

## Setup

### 1. Environment Variables

```bash
# Required for Gemini Vision
GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json

# Required for audio transcription
# (same service account needs Speech-to-Text API enabled)
```

### 2. Dependencies

```bash
pip install opencv-python pillow easyocr ffmpeg-python google-cloud-speech vertexai google-api-python-client
```

Also requires `ffmpeg` and `ffprobe` installed on system.

## Usage

### Basic Video Analysis

```python
from scripts.video_extractor import VideoExtractor
from scripts.models import ExtractedVideoContent
import vertexai
from vertexai.generative_models import GenerativeModel

# Initialize Vertex AI
vertexai.init(project="your-project-id", location="us-central1")
gemini_model = GenerativeModel("gemini-1.5-flash")

# Create extractor
extractor = VideoExtractor(gemini_model=gemini_model)

# Analyze video
result = extractor.extract_content("/path/to/video.mp4")

print(f"Duration: {result.duration}s")
print(f"Scenes: {len(result.scene_timeline)}")
print(f"Text overlays: {len(result.text_timeline)}")
print(f"Transcript: {result.transcript[:200]}...")
```

### Extract Only Frames

```python
frames, timestamps, text_timeline, scene_timeline, thumbnail = extractor.extract_smart_frames(
    "/path/to/video.mp4",
    scene_interval=2,    # Check for scene changes every 2s
    text_interval=0.5    # Check for text every 0.5s
)
```

### Analyze Images

```python
# Works with images too
resu...

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