How to perform inference using yolov8 on edgetpu.

[Arslan-Mehmood1]

I have exported my yolov8 model using ultralytics to edgetpu and tflite formats. I have performed inference of yolov8 edge tpu model on USB coral accelerator. I have the predictions result. I dont know how to parse these predictions Please help out.

Prediction Output:

python3 detect_image.py -m yolov8_int8_edgetpu.tflite -i image.jpg -o inference/detection.jpg
----INFERENCE TIME----
Note: The first inference is slow because it includes loading the model into Edge TPU memory.

Output Details :
[{'name': 'PartitionedCall:0', 'index': 517, 'shape': array([ 1, 251, 33600], dtype=int32), 'shape_signature': array([ 1, 251, 33600], dtype=int32), 'dtype': <class 'numpy.float32'>, 'quantization': (0.0, 0), 'quantization_parameters': {'scales': array([], dtype=float32), 'zero_points': array([], dtype=int32), 'quantized_dimension': 0}, 'sparsity_parameters': {}}]

Output Data Shape:
(1, 251, 33600)
Output Data :
[[[6.8984828e-03 8.4312847e-03 1.4987010e-02 ... 9.1422123e-01
9.3176806e-01 9.5353013e-01]
[8.2258508e-03 8.4541356e-03 8.1687719e-03 ... 9.7039759e-01
9.6757478e-01 9.6137410e-01]
[1.3865395e-02 1.7534753e-02 1.8626634e-02 ... 2.2020416e-01
1.8798628e-01 1.2658052e-01]
...
[8.6820194e-07 1.4569782e-06 1.3537380e-06 ... 4.9203813e-05
3.5585672e-05 3.4364115e-05]
[1.6130493e-06 1.2267126e-06 2.5768195e-06 ... 4.6514473e-05
4.1418200e-05 3.8001206e-05]
[4.9328037e-07 1.4711668e-06 1.1877161e-06 ... 3.2545999e-05
3.1352149e-05 2.2766470e-05]]]