def sort_findings(model, image_tuples, test_images, labels, false_positives, false_negatives,
fp_images, fn_images, index):
"""False positive if model says road doesn't exist, but OpenStreetMap says it does.
False negative if model says road exists, but OpenStreetMap doesn't list it.
"""
pred_index = 0
for p in model.predict(test_images):
label = labels[index][0]
if has_ways_in_center(label, 1) and p[0] > .5:
false_positives.append(p)
fp_images.append(image_tuples[pred_index])
elif not has_ways_in_center(label, 16) and p[0] <= .5:
false_negatives.append(p)
fn_images.append(image_tuples[pred_index])
pred_index += 1
index += 1
return index, false_positives, false_negatives, fp_images, fn_images
def sort_findings(model, image_tuples, test_images, labels, false_positives,
false_negatives, fp_images, fn_images, index):
"""False positive if model says road doesn't exist, but OpenStreetMap says it does.
False negative if model says road exists, but OpenStreetMap doesn't list it.
"""
pred_index = 0
for p in model.predict(test_images):
label = labels[index][0]
if has_ways_in_center(label, 1) and p[0] > .5:
false_positives.append(p)
fp_images.append(image_tuples[pred_index])
elif not has_ways_in_center(label, 16) and p[0] <= .5:
false_negatives.append(p)
fn_images.append(image_tuples[pred_index])
pred_index += 1
index += 1
return index, false_positives, false_negatives, fp_images, fn_images