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---
license: openrail
tags:
- object-detection
- ultralytics
---
# NTU CZ3004/SC2079 Image Recognition/Symbol Detection - Week 9 - YOLOv5
CZ3004 is a module in Nanyang Technological University's Computer Science curriculum that involves creating a robot car that can navigate within an arena and around obstacles.
Part of the assessment is to go to obstacles and detect alphanumeric symbols pasted on them.
## Training Data
The training dataset had 20,000 images across 3 classes, with each class having roughly the same number of images. The images were either downloaded from RoboFlow Universe or obtained by ourselves in real life.
## Training Procedure
The notebook from Ultralytics was used for training. Training was done on Google Colab for 20 epochs.
## Other Models
There is also a [Week 8 model available](https://huggingface.co/pyesonekyaw/MDP_ImageRecognition_YOLOv5_Week_8_AY22-23_NTU-SG) |