87f878b96bf00cb19d850992f01d9370b57b8345,skvideo/measure/niqe.py,,_get_patches_generic,#Any#Any#Any#Any#,52

Before Change




    img = img.astype(np.float32)
    img2 = scipy.misc.imresize(img, 0.5, interp="bicubic", mode="F")

    mscn1, var, mu = compute_image_mscn_transform(img)
    mscn1 = mscn1.astype(np.float32)

After Change




    img = img.astype(np.float32)
    img2 = np.array(Image.fromarray(img).resize(
        (int(0.5 * img.shape[0]), int(img.shape[1] * 0.5)),
        resample=PIL.Image.BICUBIC)
    )

    mscn1, var, mu = compute_image_mscn_transform(img)
    mscn1 = mscn1.astype(np.float32)
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 8

Instances


Project Name: scikit-video/scikit-video
Commit Name: 87f878b96bf00cb19d850992f01d9370b57b8345
Time: 2019-10-21
Author: stg7@gmx.de
File Name: skvideo/measure/niqe.py
Class Name:
Method Name: _get_patches_generic


Project Name: wkentaro/labelme
Commit Name: 512d9affe75ccddf666ee932acc6bd56d00ce6e7
Time: 2018-02-06
Author: www.kentaro.wada@gmail.com
File Name: labelme/utils.py
Class Name:
Method Name: draw_label


Project Name: scikit-video/scikit-video
Commit Name: 87f878b96bf00cb19d850992f01d9370b57b8345
Time: 2019-10-21
Author: stg7@gmx.de
File Name: skvideo/measure/brisque.py
Class Name:
Method Name: brisque_features