---
title: "Reconstructed Slides: Building Agents at Cloud Scale — Antje Barth, AWS"
category: "slides"
video_id: "WJjInLeaJjo"
sourceLabels: ["Cropped public YouTube video frames", "Local OpenCV slide-region detection", "Local RapidOCR"]
---

# Reconstructed Slides: Building Agents at Cloud Scale — Antje Barth, AWS

## Source Video
[Building Agents at Cloud Scale — Antje Barth, AWS](https://www.youtube.com/watch?v=WJjInLeaJjo)

## 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
![[assets/reconstructed-slides/WJjInLeaJjo/slide-001.jpg]]

- Source frame: `slide-001.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `160.13`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-002.jpg]]

- Source frame: `slide-002.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `166.28`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-003.jpg]]

- Source frame: `slide-003.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `166.17`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-004.jpg]]

- Source frame: `slide-004.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `167.53`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-005.jpg]]

- Source frame: `slide-005.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `160.75`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-006.jpg]]

- Source frame: `slide-006.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `175.44`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-007.jpg]]

- Source frame: `slide-007.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `160.71`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-008.jpg]]

- Source frame: `slide-008.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `160.39`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-009.jpg]]

- Source frame: `slide-009.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `161.3`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-010.jpg]]

- Source frame: `slide-010.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `158.72`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-011.jpg]]

- Source frame: `slide-011.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `159.76`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-012.jpg]]

- Source frame: `slide-012.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `157.2`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-013.jpg]]

- Source frame: `slide-013.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `157.92`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-014.jpg]]

- Source frame: `slide-014.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `166.91`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-015.jpg]]

- Source frame: `slide-015.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.56`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-016.jpg]]

- Source frame: `slide-017.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `159.68`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-017.jpg]]

- Source frame: `slide-018.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `177.41`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-018.jpg]]

- Source frame: `slide-019.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.91`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-019.jpg]]

- Source frame: `slide-020.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `158.82`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-020.jpg]]

- Source frame: `slide-021.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `159.12`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-021.jpg]]

- Source frame: `slide-022.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `162.58`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-022.jpg]]

- Source frame: `slide-023.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `177.78`
![[assets/reconstructed-slides/WJjInLeaJjo/slide-023.jpg]]

- Source frame: `slide-024.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.98`
## Dense Scene-Detected Slide Candidates
- [[youtube-WJjInLeaJjo-dense-slides]]