Reconstructed Slides: Agents need more than a chat - Jacob Lauritzen, CTO Legora

Source Video

Agents need more than a chat - Jacob Lauritzen, CTO Legora

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 157.8

• Source frame: slide-002.jpg
• Crop: contour [0, 0, 960, 540] score 175.97

• Source frame: slide-003.jpg
• Crop: full [0, 0, 960, 540] score 164.76

• Source frame: slide-004.jpg
• Crop: contour [0, 0, 960, 540] score 176.29

• Source frame: slide-005.jpg
• Crop: full [0, 0, 960, 540] score 176.06

• Source frame: slide-006.jpg
• Crop: contour [0, 0, 960, 540] score 176.38

• Source frame: slide-007.jpg
• Crop: full [0, 0, 960, 540] score 176.22

• Source frame: slide-008.jpg
• Crop: full [0, 0, 960, 540] score 175.84

• Source frame: slide-009.jpg
• Crop: full [0, 0, 960, 540] score 165.22

• Source frame: slide-010.jpg
• Crop: full [0, 0, 960, 540] score 165.93

Dense Scene-Detected Slide Candidates

• youtube XNtkiQJ49Ps dense slides