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October 23, 2018 15:43
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YOLOv2 Prediction
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# loop 845 bounding boxes | |
for i in range(Net_YOLO_pred.shape[0]): | |
# get the confidence on the object | |
confidence_on_box = Net_YOLO_pred[i][4] | |
# find the class index with the highest probability | |
probability_list = Net_YOLO_pred[i][5:] | |
class_index = probability_list.argmax(axis=0) | |
probability_on_class = probability_list[class_index] | |
# get the score | |
score = confidence_on_box * probability_on_class | |
# draw the bounding box | |
if (score > threshold): | |
x_center = Net_YOLO_pred[i][0] * cols | |
y_center = Net_YOLO_pred[i][1] * rows | |
width = Net_YOLO_pred[i][2] * cols | |
height = Net_YOLO_pred[i][3] * rows | |
left = int(x_center - width * 0.5) | |
top = int(y_center - height * 0.5) | |
right = int(x_center + width * 0.5) | |
bottom = int(y_center + height * 0.5) | |
box = patch.Rectangle((int(left), int(top)), | |
width, | |
height, | |
linewidth=2, edgecolor='r', facecolor='none') | |
ax2.add_patch(box) |
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