34eb970b4ee951887d991c95b7334a8c1c7d73eb,batchflow/tests/segmentation_metrics_test.py,,,#,5

Before Change

sample_length = 100
num_classes = 10
targets_sample = np.random.randint(0, num_classes - 2, sample_length)
noise_sample = np.random.binomial(1, 1/10, sample_length)
predics_sample = targets_sample + noise_sample

batch_size = 3
image_size = 2
pull_out = lambda s,x,y: s[:x*y*y].reshape(x, y, y)
targets = pull_out(targets_sample, batch_size, image_size)
predics = pull_out(predics_sample, batch_size, image_size)

@pytest.mark.parametrize("metrics_name", metrics_names)
class TestShape:

After Change

batch_size = 2
image_size = 2
num_classes = 3
targets = np.array([0, 1, 2, 2, 0, 0, 1, 1]).reshape(batch_size, image_size, image_size)
predics = np.array([0, 1, 1, 0, 2, 0, 1, 1]).reshape(batch_size, image_size, image_size)
onehots = np.eye(num_classes)[predics] //it"s basically like probs, just with all 0 and a single 1

@pytest.mark.parametrize("metrics_name", metrics_names)

Instances