<commit_before># Traffic Sign Recognition

**Table of Content**

<!-- TOC depthFrom:2 depthTo:6 withLinks:1 updateOnSave:1 orderedList:0 -->

	- [Data Set Summary & Exploration](#data-set-summary-exploration)
		- [Data Structure](#data-structure)
		- [Dataset sample](#dataset-sample)
	- [Design and Test a Model Architecture](#design-and-test-a-model-architecture)
		- [Data Preprocessing](#data-preprocessing)
		- [Training](#training)
		- [Final Architecture](#final-architecture)
		- [Details for training the model](#details-for-training-the-model)
		- [Results](#results)
	- [Test a Model on New Images](#test-a-model-on-new-images)
		- [Images used](#images-used)
		- [Prediction](#prediction)
		- [Softmax probabilities](#softmax-probabilities)
- [Reference](#reference)

<!-- /TOC -->

This project involves in detecting the German traffic signs using the principals of Convolutional Neural network (CNN).

Before I go in the details of how the algorithm works, lets look at the images used to classify the trained model.

---<commit_msg>toc updated<commit_after># Traffic Sign Recognition

**Table of Content**

- [Data Set Summary & Exploration](#data-set-summary-exploration)
	- [Data Structure](#data-structure)
	- [Dataset sample](#dataset-sample)
- [Design and Test a Model Architecture](#design-and-test-a-model-architecture)
	- [Data Preprocessing](#data-preprocessing)
	- [Training](#training)
	- [Final Architecture](#final-architecture)
	- [Details for training the model](#details-for-training-the-model)
	- [Results](#results)
- [Test a Model on New Images](#test-a-model-on-new-images)
	- [Images used](#images-used)
	- [Prediction](#prediction)
	- [Softmax probabilities](#softmax-probabilities)
- [Reference](#reference)

This project involves in detecting the German traffic signs using the principals of Convolutional Neural network (CNN).

Before I go in the details of how the algorithm works, lets look at the images used to classify the trained model.

---
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{'dir': 'git-commits-cleaned', 'id': '4396877', 'n_tokens_mistral': 632, 'n_tokens_neox': 565, 'n_words': 174}