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@@ -18,7 +18,7 @@ Achieved a 93% validation accuracy
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  ### Model Sources
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  - **Repository:** https://github.com/magichampz/lego-sorting-machine-ag-ak
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- ![image/gif](https://cdn-uploads.huggingface.co/production/uploads/652dc3dab86e108d0fea458c/E7UZXLWPvU_39cxrF49jD.gif)
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  ## Uses
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  The files in the create-model folder are meant to be used on your own computer.
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  The model was trained on Google Colab, so create_training_data_array.py was used to creata a numpy array file to upload data in the form of a numpy array to Google Colab.
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  After transfering the tflite model to your Pi, you can then run the image classification file in the raspberry-pi folder to detect and classify lego pieces in real time.
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  ## Bias, Limitations and Recommendations
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  The images of the lego pieces used to train the model were taken in room lighting conditions, illuminated with a torchlight. <br>
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  To use the model, would recommend trying to recreate the conditions and achieve photographs with a similar lighting. <br>
 
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  ### Model Sources
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  - **Repository:** https://github.com/magichampz/lego-sorting-machine-ag-ak
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  ## Uses
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  The files in the create-model folder are meant to be used on your own computer.
 
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  The model was trained on Google Colab, so create_training_data_array.py was used to creata a numpy array file to upload data in the form of a numpy array to Google Colab.
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  After transfering the tflite model to your Pi, you can then run the image classification file in the raspberry-pi folder to detect and classify lego pieces in real time.
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+ Example of real time object detection and classification:
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+ ![image/gif](https://cdn-uploads.huggingface.co/production/uploads/652dc3dab86e108d0fea458c/E7UZXLWPvU_39cxrF49jD.gif)
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  ## Bias, Limitations and Recommendations
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  The images of the lego pieces used to train the model were taken in room lighting conditions, illuminated with a torchlight. <br>
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  To use the model, would recommend trying to recreate the conditions and achieve photographs with a similar lighting. <br>