Object Detection
Collection
7 items
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Updated
This model is a fine-tuned version of hustvl/yolos-tiny on the hard-hat-detection dataset.
For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Computer%20Vision/Object%20Detection/Hard%20Hat%20Detection/Hard_Hat_Object_Detection_YOLOS.ipynb
This model is intended to demonstrate my ability to solve a complex problem using technology.
Dataset Source: https://huggingface.co/datasets/keremberke/hard-hat-detection
The following hyperparameters were used during training:
Metric Name | IoU | Area | maxDets | Metric Value |
---|---|---|---|---|
Average Precision (AP) | IoU=0.50:0.95 | all | maxDets=100 | 0.346 |
Average Precision (AP) | IoU=0.50 | all | maxDets=100 | 0.747 |
Average Precision (AP) | IoU=0.75 | all | maxDets=100 | 0.275 |
Average Precision (AP) | IoU=0.50:0.95 | small | maxDets=100 | 0.128 |
Average Precision (AP) | IoU=0.50:0.95 | medium | maxDets=100 | 0.343 |
Average Precision (AP) | IoU=0.50:0.95 | large | maxDets=100 | 0.521 |
Average Recall (AR) | IoU=0.50:0.95 | all | maxDets=1 | 0.188 |
Average Recall (AR) | IoU=0.50:0.95 | all | maxDets=10 | 0.484 |
Average Recall (AR) | IoU=0.50:0.95 | all | maxDets=100 | 0.558 |
Average Recall (AR) | IoU=0.50:0.95 | small | maxDets=100 | 0.320 |
Average Recall (AR) | IoU=0.50:0.95 | medium | maxDets=100 | 0.538 |
Average Recall (AR) | IoU=0.50:0.95 | large | maxDets=100 | 0.743 |
Base model
hustvl/yolos-tiny