Ikomia-dev / YoloDetection

Implementation of YOLO DNN inference with OpenCV

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YoloDetection

Implementation of YOLO DNN inference with OpenCV

We give a Python script to launch inference (detection):

python detection.py "SourceImage" "ConfigFile" "WeightsFile" "ClassFile"

SourceImage (mandatory): path of the image or folder of images on which detection will be done.
ConfigFile (mandatory): path of the YOLO configuration file (.cfg).
WeightsFile (mandatory): path of the YOLO trained model (.weights).
ClassFile (mandatory): path of the text file where are listed all class labels.

Once the detection is done, the result image is shown with bounding boxes around detected objects. Here is the list of possible user interactions:

  1. Press 's' key to save result image into the current folder.
  2. Press 'Esc' key to end process.
  3. Press any other key to process next image

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Implementation of YOLO DNN inference with OpenCV

License:MIT License


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Language:Python 100.0%