CODEWITHSUNDEEP
pythontensorflowtensorflow-liteyoloyolov5
James
James

Reputation: 18379

How to use Yolo 5 converted models

Yolo 5 is an object detection model that can be exported to several different frameworks including TensorFlow and Core ML. https://github.com/ultralytics/yolov5

I have been able to train a Yolo 5 model, and export it to TensorFlow (TF1 graph def, or TF2 savemodel), and tried Apple Core ML.

I have not been able to find any examples for Yolo 5 on how to use these models once exported. i.e. how to take an image file and get the detected objects/labels/coordinates

I tried similar python code to TF1 object detection, but the exported model does not seem compatible, https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/tensorflow-1.14/

neither with TF2, https://www.tensorflow.org/hub/tutorials/object_detection

or TFlite, https://www.tensorflow.org/lite/examples/object_detection/overview

Upvotes: 1

Views: 902

Answers (1)

Illustrati
Illustrati

Reputation: 321

Use the weights that YOLOv5 calculated after training. They are usually in this route:

yolov5/runs/train/your_yolo_model/weights/best.pt

Upvotes: 0

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