---
title: "Reconstructed Slides: From Text to Vision to Voice Exploring Multimodality with Open AI: Romain Huet"
category: "slides"
video_id: "yJHw33cVeHo"
sourceLabels: ["Cropped public YouTube video frames", "Local OpenCV slide-region detection", "Local RapidOCR"]
---

# Reconstructed Slides: From Text to Vision to Voice Exploring Multimodality with Open AI: Romain Huet

## Source Video
[From Text to Vision to Voice Exploring Multimodality with Open AI: Romain Huet](https://www.youtube.com/watch?v=yJHw33cVeHo)

## 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/yJHw33cVeHo/slide-001.jpg]]

- Source frame: `slide-001.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `158.44`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-002.jpg]]

- Source frame: `slide-002.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `161.72`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-003.jpg]]

- Source frame: `slide-003.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `152.12`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-004.jpg]]

- Source frame: `slide-004.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.29`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-005.jpg]]

- Source frame: `slide-005.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `155.11`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-006.jpg]]

- Source frame: `slide-006.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `152.38`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-007.jpg]]

- Source frame: `slide-007.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `155.72`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-008.jpg]]

- Source frame: `slide-008.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `159.89`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-009.jpg]]

- Source frame: `slide-009.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `157.09`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-010.jpg]]

- Source frame: `slide-010.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `159.34`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-011.jpg]]

- Source frame: `slide-011.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `172.85`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-012.jpg]]

- Source frame: `slide-012.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `175.92`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-013.jpg]]

- Source frame: `slide-013.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `159.76`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-014.jpg]]

- Source frame: `slide-014.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `175.88`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-015.jpg]]

- Source frame: `slide-015.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.15`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-016.jpg]]

- Source frame: `slide-016.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `160.13`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-017.jpg]]

- Source frame: `slide-017.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `159.79`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-018.jpg]]

- Source frame: `slide-019.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `151.51`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-019.jpg]]

- Source frame: `slide-020.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `158.76`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-020.jpg]]

- Source frame: `slide-021.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `156.27`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-021.jpg]]

- Source frame: `slide-022.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `158.35`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-022.jpg]]

- Source frame: `slide-023.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `157.05`
![[assets/reconstructed-slides/yJHw33cVeHo/slide-023.jpg]]

- Source frame: `slide-024.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `153.21`
## Dense Scene-Detected Slide Candidates
- [[youtube-yJHw33cVeHo-dense-slides]]