Comments (2)
The output of the test file includes a map that contains entries of type "label" : "number" where label is a fruit class name, an the number represents how many test images from that label were classified incorrectly. This is to show which fruit classes are more difficult to classify.
For example, in your case 'banana': 30 means that 30 images with bananas were classified as something else.
When using the detection script, bear in mind that it is only a basic example that takes an image, resizes it to 100 x 100 pixels and runs it through the network.
Also, if the images you are trying to use in detection are very different from the training ones (for example there is a lot of light, or very little light, or the background of the image is not white) then the network won't predict them properly.
from fruit-images-dataset.
thanks so much
from fruit-images-dataset.
Related Issues (20)
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from fruit-images-dataset.