---
title: "Reconstructed Slides: Trust, but Verify: Shreya Rajpal"
category: "slides"
video_id: "9-vGxMoUM9Y"
sourceLabels: ["Cropped public YouTube video frames", "Local OpenCV slide-region detection", "Local RapidOCR"]
---

# Reconstructed Slides: Trust, but Verify: Shreya Rajpal

## Source Video
[Trust, but Verify: Shreya Rajpal](https://www.youtube.com/watch?v=9-vGxMoUM9Y)

## 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/9-vGxMoUM9Y/slide-001.jpg]]

- Source frame: `slide-001.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.51`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-002.jpg]]

- Source frame: `slide-002.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `168.11`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-003.jpg]]

- Source frame: `slide-003.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `175.62`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-004.jpg]]

- Source frame: `slide-004.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `171.31`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-005.jpg]]

- Source frame: `slide-005.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `154.03`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-006.jpg]]

- Source frame: `slide-006.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `162.97`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-007.jpg]]

- Source frame: `slide-007.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `165.85`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-008.jpg]]

- Source frame: `slide-008.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `160.78`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-009.jpg]]

- Source frame: `slide-009.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `167.19`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-010.jpg]]

- Source frame: `slide-010.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `170.15`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-011.jpg]]

- Source frame: `slide-011.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `154.23`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-012.jpg]]

- Source frame: `slide-012.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `164.45`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-013.jpg]]

- Source frame: `slide-013.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `165.71`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-014.jpg]]

- Source frame: `slide-014.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.3`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-015.jpg]]

- Source frame: `slide-016.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `157.88`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-016.jpg]]

- Source frame: `slide-017.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `163.92`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-017.jpg]]

- Source frame: `slide-018.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `154.9`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-018.jpg]]

- Source frame: `slide-019.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `163.41`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-019.jpg]]

- Source frame: `slide-020.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `171.65`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-020.jpg]]

- Source frame: `slide-021.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `167.36`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-021.jpg]]

- Source frame: `slide-022.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `168.08`
![[assets/reconstructed-slides/9-vGxMoUM9Y/slide-022.jpg]]

- Source frame: `slide-023.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `169.91`
## Dense Scene-Detected Slide Candidates
- [[youtube-9-vGxMoUM9Y-dense-slides]]