---
title: "Reconstructed Slides: Can LLMs generate Enterprise Quality Code? — Prasenjit Sarkar, Sonar"
category: "slides"
video_id: "NuePCNMpWGc"
sourceLabels: ["Cropped public YouTube video frames", "Local OpenCV slide-region detection", "Local RapidOCR"]
---

# Reconstructed Slides: Can LLMs generate Enterprise Quality Code? — Prasenjit Sarkar, Sonar

## Source Video
[Can LLMs generate Enterprise Quality Code? — Prasenjit Sarkar, Sonar](https://www.youtube.com/watch?v=NuePCNMpWGc)

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

- Source frame: `slide-001.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `157.8`
![[assets/reconstructed-slides/NuePCNMpWGc/slide-002.jpg]]

- Source frame: `slide-002.jpg`
- Crop: `contour` `[0, 0, 960, 540]` score `177.11`
![[assets/reconstructed-slides/NuePCNMpWGc/slide-003.jpg]]

- Source frame: `slide-003.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.03`
![[assets/reconstructed-slides/NuePCNMpWGc/slide-004.jpg]]

- Source frame: `slide-004.jpg`
- Crop: `full` `[0, 0, 960, 540]` score `176.08`
## Dense Scene-Detected Slide Candidates
- [[youtube-NuePCNMpWGc-dense-slides]]