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  license: apache-2.0
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  ---
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  | ![Imagen](test_images/Shelf_image2.jpg) | ![Imagen2](test_images/Image1.png) |
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- | --- | --- |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: apache-2.0
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  ---
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  | ![Imagen](test_images/Shelf_image2.jpg) | ![Imagen2](test_images/Image1.png) |
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+ | --- | --- |
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+
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+
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+ - Install yolov5:
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+ ```bash
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+ pip install yolov5==7.0.5
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+ ```
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+ - Set image
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+
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+ ```bash
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+ wget -O 'image.jpg' 'https://images.unsplash.com/photo-1556767576-cf0a4a80e5b8?ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxzZWFyY2h8NXx8c3VwZXJtYXJrZXQlMjBzaGVsdmVzfGVufDB8fDB8fHww&w=1000&q=80'
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+ ```
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+ - Load model and perform prediction:
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+
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+ ```python
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+ import yolov5
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+
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+ # load model
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+ model = yolov5.load('Jonathancasjar/Retail_Shelves')
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+
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+ # set model parameters
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+ model.conf = 0.25 # NMS confidence threshold
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+
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+ # set an image
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+ img = '/content/image.jpg'
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+
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+ # perform inference
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+ results = model(img, size=640)
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+
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+ # inference with test time augmentation
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+ results = model(img, augment=True)
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+
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+ # parse results
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+ predictions = results.pred[0]
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+ boxes = predictions[:, :4] # x1, y1, x2, y2
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+ scores = predictions[:, 4]
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+ categories = predictions[:, 5]
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+
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+ # show detection bounding boxes on image
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+ results.show()
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+
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+ # save results into "results/" folder
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+ results.save(save_dir='results/')
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+ ```
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+