Reconstructed Slides: MCP is all you need — Samuel Colvin, Pydantic

Source Video

MCP is all you need — Samuel Colvin, Pydantic

Method

This deck is reconstructed from the existing video frame captures by detecting likely slide regions with OpenCV, cropping/upscaling those regions, deduplicating similar crops, and OCRing the cropped slide images locally. It is a cleaner companion to the full-stage frame deck.

Reconstructed Slides

• Source frame: slide-001.jpg
• Crop: full [0, 0, 960, 540] score 160.12

• Source frame: slide-002.jpg
• Crop: full [0, 0, 960, 540] score 163.02

• Source frame: slide-003.jpg
• Crop: full [0, 0, 960, 540] score 161.15

• Source frame: slide-004.jpg
• Crop: full [0, 0, 960, 540] score 156.9

• Source frame: slide-005.jpg
• Crop: full [0, 0, 960, 540] score 157.42

• Source frame: slide-006.jpg
• Crop: full [0, 0, 960, 540] score 157.56

• Source frame: slide-007.jpg
• Crop: full [0, 0, 960, 540] score 153.68

• Source frame: slide-008.jpg
• Crop: full [0, 0, 960, 540] score 151.22

• Source frame: slide-009.jpg
• Crop: full [0, 0, 960, 540] score 158.41

• Source frame: slide-010.jpg
• Crop: full [0, 0, 960, 540] score 158.14

• Source frame: slide-011.jpg
• Crop: full [0, 0, 960, 540] score 158.92

• Source frame: slide-012.jpg
• Crop: full [0, 0, 960, 540] score 159.48

• Source frame: slide-013.jpg
• Crop: full [0, 0, 960, 540] score 158.94

• Source frame: slide-014.jpg
• Crop: full [0, 0, 960, 540] score 158.74

• Source frame: slide-015.jpg
• Crop: full [0, 0, 960, 540] score 160.77

• Source frame: slide-016.jpg
• Crop: full [0, 0, 960, 540] score 158.62

• Source frame: slide-017.jpg
• Crop: full [0, 0, 960, 540] score 177.44

• Source frame: slide-018.jpg
• Crop: full [0, 0, 960, 540] score 159.94

Dense Scene-Detected Slide Candidates

• youtube bmWZk9vTze0 dense slides