(sample_batchs, hr_sample_batchs,
captions_batch, batch_size,
startID, save_dir)
| 103 | |
| 104 | |
| 105 | def save_super_images(sample_batchs, hr_sample_batchs, |
| 106 | captions_batch, batch_size, |
| 107 | startID, save_dir): |
| 108 | if not os.path.isdir(save_dir): |
| 109 | print('Make a new folder: ', save_dir) |
| 110 | mkdir_p(save_dir) |
| 111 | |
| 112 | # Save up to 16 samples for each text embedding/sentence |
| 113 | img_shape = hr_sample_batchs[0][0].shape |
| 114 | for j in range(batch_size): |
| 115 | if not re.search('[a-zA-Z]+', captions_batch[j]): |
| 116 | continue |
| 117 | |
| 118 | padding = np.zeros(img_shape) |
| 119 | row1 = [padding] |
| 120 | row2 = [padding] |
| 121 | # First row with up to 8 samples |
| 122 | for i in range(np.minimum(8, len(sample_batchs))): |
| 123 | lr_img = sample_batchs[i][j] |
| 124 | hr_img = hr_sample_batchs[i][j] |
| 125 | hr_img = (hr_img + 1.0) * 127.5 |
| 126 | re_sample = scipy.misc.imresize(lr_img, hr_img.shape[:2]) |
| 127 | row1.append(re_sample) |
| 128 | row2.append(hr_img) |
| 129 | row1 = np.concatenate(row1, axis=1) |
| 130 | row2 = np.concatenate(row2, axis=1) |
| 131 | superimage = np.concatenate([row1, row2], axis=0) |
| 132 | |
| 133 | # Second 8 samples with up to 8 samples |
| 134 | if len(sample_batchs) > 8: |
| 135 | row1 = [padding] |
| 136 | row2 = [padding] |
| 137 | for i in range(8, len(sample_batchs)): |
| 138 | lr_img = sample_batchs[i][j] |
| 139 | hr_img = hr_sample_batchs[i][j] |
| 140 | hr_img = (hr_img + 1.0) * 127.5 |
| 141 | re_sample = scipy.misc.imresize(lr_img, hr_img.shape[:2]) |
| 142 | row1.append(re_sample) |
| 143 | row2.append(hr_img) |
| 144 | row1 = np.concatenate(row1, axis=1) |
| 145 | row2 = np.concatenate(row2, axis=1) |
| 146 | super_row = np.concatenate([row1, row2], axis=0) |
| 147 | superimage2 = np.zeros_like(superimage) |
| 148 | superimage2[:super_row.shape[0], |
| 149 | :super_row.shape[1], |
| 150 | :super_row.shape[2]] = super_row |
| 151 | mid_padding = np.zeros((64, superimage.shape[1], 3)) |
| 152 | superimage =\ |
| 153 | np.concatenate([superimage, mid_padding, superimage2], axis=0) |
| 154 | |
| 155 | top_padding = np.zeros((128, superimage.shape[1], 3)) |
| 156 | superimage =\ |
| 157 | np.concatenate([top_padding, superimage], axis=0) |
| 158 | |
| 159 | fullpath = '%s/sentence%d.jpg' % (save_dir, startID + j) |
| 160 | superimage = drawCaption(np.uint8(superimage), captions_batch[j]) |
| 161 | scipy.misc.imsave(fullpath, superimage) |
| 162 |
no test coverage detected