CODEWITHSUNDEEP
pythonnumpyimage-segmentation
jimmy15923
jimmy15923

Reputation: 291

Instance IOU fast calculation on large image

I have a instances boolean mask which shape is (448, 1000, 1000) for 448 instances, the average pixel of instance is around 100.

Now if I have a prediction matrix which shape is (1000, 1000) and predict instance by integer, i.e. If the matrix predict 500 instance, np.unique(pred) will be 501 (500 class + 1 background).

I need to calculate the IOU (jaccard index) for each pair prediction and mask to find the maximum IOU. I have wrote codes below but it's super slow and inefficient.

c = 0 #intersection count
u = 0 #union count
pred_used = [] #record prediction used

# loop for every ground truth mask
for idx_m in range(len(mask[:,0,0])):
    m = mask[idx_m,:,:] #take one mask
    intersect_list = []
    union_list = []

    # loop every prediction
    for idx_pred in range(1, int(np.max(pred))+1):
        p = (pred==idx_pred) # take one prediction mask
        intersect = np.sum(m.ravel() * p.ravel()) #calculate intersect
        union = np.sum(m.ravel() + p.ravel() - m.ravel()*p.ravel())
        intersect_list.append(intersect)
        union_list.append(union_list)

    if np.sum(intersect_list) > 0:
        idx_max_iou = np.argmax(np.array(intersect_list))
        c += intersect_list[idx_max_iou]
        u += union_list[idx_max_iou]
        pred_used.append(idx_max_iou)

Upvotes: 1

Views: 1415

Answers (1)

Farshid Rayhan
Farshid Rayhan

Reputation: 1214

So you have an output image sized [1000,1000] which is the predicted array/tensor by your model.

One of the first thing you can do is reshape the labels and predictions from [1000,1000] to [1000*1000, ]. This reduces the complexity from being N^2 to N. This should boostup the speed significantly .

And you can also try the IoU from Scikit which maybe a bit faster than your vesion.

You can find an example here: How to find IoU from segmentation masks?

Doc: http://scikit-learn.org/stable/modules/generated/sklearn.metrics.jaccard_similarity_score.html

Upvotes: 1

Related Questions