Deep Learning, Sora, Computer Vision, Transformers, Attention.
img_sizes = np.asarray([Image.open(i).size for i in tqdm(imgs)]) img_sizes.shape #(5000, 2) ar = img_sizes[:, 0]/img_sizes[:, 1] ar.shape (5000,) fig, ax = plt.subplots(figsize=(12, 2.5), nrows=1, ncols=2) ax.flat[0].scatter(img_sizes[:, 0], img_sizes[:, 1]) ax.flat[0].set_xlabel("w")