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  ### Model Description
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- Object detection model trained using YOLO v5x. The model was pre-trained on the Cashew Disease Identification with AI (CADI-AI) train set (3788 images) at a resolution of 640x640 pixels.
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- CADI-AI dataset is available in hugging face dataset hub
 
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  ## Intended uses & limitations
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@@ -38,6 +39,7 @@ model = torch.hub.load('ultralytics/yolov5', 'KaraAgroAI/CADI-AI')
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  img = ['/path/to/CADI-AI-image.jpg']# batch of images
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  # set model parameters
 
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  model.conf = 0.20 # NMS confidence threshold
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  # perform inference
 
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  ### Model Description
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+ Object detection model trained using [YOLO v5x](https://github.com/ultralytics/yolov5/releases), a SOTA object detection algorithm.
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+ The model was pre-trained on the Cashew Disease Identification with AI (CADI-AI) train set (3788 images) at a resolution of 640x640 pixels.
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+ CADI-AI dataset is available in hugging face dataset hub.
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  ## Intended uses & limitations
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  img = ['/path/to/CADI-AI-image.jpg']# batch of images
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  # set model parameters
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+ # set Non-Maximum-Suppression(NMS) threshold to define minimum confidence score that a bounding box must have in order to be kept.
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  model.conf = 0.20 # NMS confidence threshold
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  # perform inference