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.
- License 许可
- MIT
- 最近更新
- 2026-08-23
- Stars
- ★ 1
- Forks
- 0
01 前言 Front Matter
- name
- video-ad-analyzer
- version
- 1.0.0
- description
- 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.
02 资源文件 6
- 参考文档_meta.json300 B
- 参考文档prompts/scene_analysis.md3.3 KB
- 参考文档prompts/scene_reconciliation.md3.6 KB
- 脚本scripts/models.py548 B
- 脚本scripts/prompt_manager.py4.9 KB
- 脚本scripts/video_extractor.py28.0 KB
03 SKILL.md 正文
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
result = extractor.extract_content("/path/to/image.jpg")
print(result.scene_timeline[0]['description'])
Output Structure
ExtractedVideoContent(
video_path="/path/to/video.mp4",
duration=30.5,
transcript="Here's what we found...",
text_timeline=[
{"at": 0.0, "text": ["Download Now"]},
{"at": 5.5, "text": ["50% Off Today"]}
],
scene_timeline=[
{"timestamp": 0.0, "description": "Woman using phone app..."},
{"timestamp": 2.0, "description": "Product showcase with features..."}
],
thumbnail_url="/static/thumbnails/video_thumb.jpg",
extraction_complete=True
)
Key Features
| Feature | Description |
|---|---|
| Scene Detection | Histogram-based change detection (threshold=65) |
| OCR Confidence | Tiered thresholds (0.5 high, 0.3 low) |
| AI Proofreading | Gemini cleans up OCR errors |
| Source Reconciliation | Merges OCR + Vision text intelligently |
| Native Video | Direct Gemini analysis for <20MB files |
Prompts
Customize AI behavior by editing prompts in the prompts/ folder:
scene_analysis.md- Frame analysis promptsscene_reconciliation.md- Scene enrichment prompts
Common Questions This Answers
- "What text appears in this video ad?"
- "Describe each scene in this creative"
- "What does the narrator say?"
- "Extract the call-to-action from this ad"
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