Downloads · 30 days
7
3% of all-time downloads
MDP_ImageRecognition_YOLOv5_Week_9_AY22-23_NTU-SG
pyesonekyaw/MDP_ImageRecognition_YOLOv5_Week_9_AY22-23_NTU-SG
MDP_ImageRecognition_YOLOv5_Week_9_AY22-23_NTU-SG is a object detection model from pyesonekyaw. Use it when you need objects located in an image. It is set up for ultralytics. The card lists the license as openrail.
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 obstac…
All-time downloads
259
Public
Repo size
14.3 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.pt14.3 MB · 100%
At a glance
- Task
- Object Detection
- Library
- ultralytics
- License
- openrail
- Access
- Public
- Created
- Apr 24, 2023
- Updated
- Apr 24, 2023
- SHA
- 91b14e10
Model card
From the Hugging Face model README
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
- Task
- Object Detection
- Library
- ultralytics
- License
- openrail
- Created
- Apr 24, 2023
- Updated
- Apr 24, 2023