Yolo v3 Tiny is a object detection network, that localizes and identifies objects in an input image. This is a floating point version that takes a 416x416 input image and outputs detections for this image. This model is generated using the weights from the YOLO website.
The class labels associated with this model can be downloaded by running the script get_class_labels.sh.
Code to recreate this model can be found here.
A guide on how to deploy this model using the Arm NN SDK can be found here.
| Network Information | Value |
|---|---|
| Framework | TensorFlow Lite |
| SHA-1 Hash | b38f7be6856eed4466493bdc86be1879f4b743fb |
| Size (Bytes) | 35455980 |
| Provenance | https://pjreddie.com/media/files/yolov3-tiny.weights & https://github.com/mystic123/tensorflow-yolo-v3 |
| Paper | https://arxiv.org/abs/1804.02767 |
Dataset: MS COCO Validation
| Metric | Value |
|---|---|
| mAP | 0.331 |
| Platform | Optimized |
|---|---|
| Cortex-A | ✔️ |
| Cortex-M | ✖️ |
| Mali GPU | ✔️ |
| Ethos U | ✖️ |
- ✔️ - Will run on this platform.
- ✖️ - Will not run on this platform.
| Input Node Name | Shape | Description |
|---|---|---|
| inputs | (1, 416, 416, 3) | A 416x416 floating point input image. |
| Output Node Name | Shape | Description |
|---|---|---|
| output_boxes | (1, 2535, 85) | A 1xNx85 map of predictions, where the first 4 entries of the 3rd dimension are the bounding box coordinates and the 5th is the confidence. The remaining entries are softmax scores for each class. |