---
title: "Reconstructed Slides: Ship Real Agents: Hands-On Evals for Agentic Applications — Laurie Voss, Arize"
category: "slides"
video_id: "Xfl50508LZM"
sourceLabels: ["Cropped public YouTube video frames", "Local OpenCV slide-region detection", "Local RapidOCR"]
---

# Reconstructed Slides: Ship Real Agents: Hands-On Evals for Agentic Applications — Laurie Voss, Arize

## Source Video
[Ship Real Agents: Hands-On Evals for Agentic Applications — Laurie Voss, Arize](https://www.youtube.com/watch?v=Xfl50508LZM)

## 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/Xfl50508LZM/slide-001.jpg]]

- Source frame: `slide-001.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `157.81`
![[assets/reconstructed-slides/Xfl50508LZM/slide-002.jpg]]

- Source frame: `slide-002.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `175.75`
![[assets/reconstructed-slides/Xfl50508LZM/slide-003.jpg]]

- Source frame: `slide-003.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.23`
![[assets/reconstructed-slides/Xfl50508LZM/slide-004.jpg]]

- Source frame: `slide-004.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `177.45`
![[assets/reconstructed-slides/Xfl50508LZM/slide-005.jpg]]

- Source frame: `slide-005.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `175.48`
![[assets/reconstructed-slides/Xfl50508LZM/slide-006.jpg]]

- Source frame: `slide-006.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.22`
![[assets/reconstructed-slides/Xfl50508LZM/slide-007.jpg]]

- Source frame: `slide-007.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.6`
## Dense Scene-Detected Slide Candidates
- [[youtube-Xfl50508LZM-dense-slides]]