Object Detection
Collection
7 items
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Updated
This model is a fine-tuned version of hustvl/yolos-small on the forklift-object-detection dataset.
For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/tree/main/Computer%20Vision/Object%20Detection/Forklift%20Object%20Detection
This model is intended to demonstrate my ability to solve a complex problem using technology.
Dataset Source: https://huggingface.co/datasets/keremberke/forklift-object-detection
The following hyperparameters were used during training:
Metric Name | IoU | Area Category | maxDets | Metric Value |
---|---|---|---|---|
Average Precision (AP) | IoU=0.50:0.95 | area= all | maxDets=100 | 0.136 |
Average Precision (AP) | IoU=0.50 | area= all | maxDets=100 | 0.400 |
Average Precision (AP) | IoU=0.75 | area= all | maxDets=100 | 0.054 |
Average Precision (AP) | IoU=0.50:0.95 | area= small | maxDets=100 | 0.001 |
Average Precision (AP) | IoU=0.50:0.95 | area=medium | maxDets=100 | 0.051 |
Average Precision (AP) | IoU=0.50:0.95 | area= large | maxDets=100 | 0.177 |
Average Recall (AR) | IoU=0.50:0.95 | area= all | maxDets= 1 | 0.178 |
Average Recall (AR) | IoU=0.50:0.95 | area= all | maxDets= 10 | 0.294 |
Average Recall (AR) | IoU=0.50:0.95 | area= all | maxDets=100 | 0.340 |
Average Recall (AR) | IoU=0.50:0.95 | area= small | maxDets=100 | 0.075 |
Average Recall (AR) | IoU=0.50:0.95 | area=medium | maxDets=100 | 0.299 |
Average Recall (AR) | IoU=0.50:0.95 | area= large | maxDets=100 | 0.373 |
Base model
hustvl/yolos-small