Zaktualizuj 'neurons.py'
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@ -11,7 +11,7 @@ class Neurons:
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output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]
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return output_layers
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def whatIsIt(self, path):
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image = cv2.imread(path)
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"""image = cv2.imread(path)
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scale = 0.00392
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classes = None
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with open("yolov3.txt", 'r') as f:
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@ -28,7 +28,7 @@ class Neurons:
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confidence = scores[class_id]
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if confidence > 0.5:
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class_ids.append(class_id)
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print([classes[ids] for ids in class_ids])
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print([classes[ids] for ids in class_ids])"""
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x = [1, 0, 0, 0, 0]
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numpy.random.shuffle(x)
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if x[0]==1:
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