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--- |
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license: agpl-3.0 |
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pipeline_tag: object-detection |
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tags: |
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- AIoT |
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- QNN |
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--- |
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## YOLOv5n: Object Detection |
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YOLOv5 is a one-stage structure target detection network framework, in which the main structure consists of 4 parts, including the network backbone composed of modified CSPNet, the high-resolution feature fusion module composed of FPN (Feature Paramid Network), composed of SPP (Spatial Pyramid Pooling) constitutes a pooling module, and three different detection heads are used to detect targets of different sizes. |
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### Source model |
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- Input shape: 640x640 |
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- Number of parameters: 1.968M |
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- Model size: 7.56 MB |
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- Output shape: 1x25200x85 |
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Source model repository: [yolov5](https://github.com/ultralytics/yolov5) |
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## Performance Reference |
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Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
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## Inference & Model Conversion |
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Please search model by model name in [Model Farm](https://aiot.aidlux.com/en/models) |
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## License |
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- Source Model: [AGPL-3.0](https://github.com/ultralytics/yolov5/blob/master/LICENSE) |
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- Deployable Model: [AGPL-3.0](https://github.com/ultralytics/yolov5/blob/master/LICENSE) |
