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--- |
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license: openrail |
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tags: |
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- object-detection |
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- ultralytics |
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--- |
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# NTU CZ3004/SC2079 Image Recognition/Symbol Detection - Week 9 - YOLOv5 |
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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. |
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Part of the assessment is to go to obstacles and detect alphanumeric symbols pasted on them. |
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## Training Data |
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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. |
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## Training Procedure |
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The notebook from Ultralytics was used for training. Training was done on Google Colab for 20 epochs. |
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## Other Models |
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There is also a [Week 8 model available](https://huggingface.co/pyesonekyaw/MDP_ImageRecognition_YOLOv5_Week_8_AY22-23_NTU-SG) |
