|
125 | 125 | E.segmented(0) |
126 | 126 | ) |
127 | 127 | for row in image[1].iterrows(): |
128 | | - objectNode = E.object( |
129 | | - E.name(str(row[1]['category_id'])), |
130 | | - E.pose("Unspecified"), |
131 | | - E.truncated("0"), |
132 | | - E.difficult("0"), |
133 | | - E.bndbox( |
134 | | - E.xmin( |
135 | | - str(int(round(row[1]['bbox'][0]))) if ROUND_COORDS else str(int(row[1]['bbox'][0]))), |
136 | | - E.ymin( |
137 | | - str(int(round(row[1]['bbox'][1]))) if ROUND_COORDS else str(int(row[1]['bbox'][1]))), |
138 | | - E.xmax(str(int(round(row[1]['bbox'][0] + row[1]['bbox'][2]))) |
139 | | - if ROUND_COORDS else str(int(row[1]['bbox'][0] + row[1]['bbox'][2]))), |
140 | | - E.ymax(str(int(round(row[1]['bbox'][1] + row[1]['bbox'][3]))) |
141 | | - if ROUND_COORDS else str(int(row[1]['bbox'][1] + row[1]['bbox'][3]))), |
142 | | - ), |
143 | | - ) |
| 128 | + if row[1]['category_id'] in label_ids: |
| 129 | + objectNode = E.object( |
| 130 | + E.name(str(row[1]['category_id'])), |
| 131 | + E.pose("Unspecified"), |
| 132 | + E.truncated("0"), |
| 133 | + E.difficult("0"), |
| 134 | + E.bndbox( |
| 135 | + E.xmin( |
| 136 | + str(int(round(row[1]['bbox'][0]))) if ROUND_COORDS else str(int(row[1]['bbox'][0]))), |
| 137 | + E.ymin( |
| 138 | + str(int(round(row[1]['bbox'][1]))) if ROUND_COORDS else str(int(row[1]['bbox'][1]))), |
| 139 | + E.xmax(str(int(round(row[1]['bbox'][0] + row[1]['bbox'][2]))) |
| 140 | + if ROUND_COORDS else str(int(row[1]['bbox'][0] + row[1]['bbox'][2]))), |
| 141 | + E.ymax(str(int(round(row[1]['bbox'][1] + row[1]['bbox'][3]))) |
| 142 | + if ROUND_COORDS else str(int(row[1]['bbox'][1] + row[1]['bbox'][3]))), |
| 143 | + ), |
| 144 | + ) |
144 | 145 | img_annotation.append(objectNode) |
145 | 146 | xml_pretty = etree.tostring(img_annotation, pretty_print=True) |
146 | 147 | with open(ANN_DIR + imagename + ".xml", 'wb') as ann_file: |
|
151 | 152 | if TRAIN_SPLIT and TRAIN_SPLIT < 1.0: |
152 | 153 | TRAIN_DIR = 'Images/train_minusminival%d/' % (YEAR) |
153 | 154 | TRAIN_FULL_DIR = '%s%s' % (ROOT_COCO, TRAIN_DIR) |
154 | | - TRAIN_ANN_DIR = 'Annotations/train_minusminival%d/' % ( |
155 | | - ROOT_COCO, YEAR) |
| 155 | + TRAIN_ANN_DIR = 'Annotations/train_minusminival%d/' % (YEAR) |
156 | 156 | TRAIN_FULL_ANN_DIR = '%s%s' % (ROOT_COCO, TRAIN_ANN_DIR) |
157 | | - MINIVAL_DIR = 'Images/minival%d/' % (ROOT_COCO, YEAR) |
| 157 | + MINIVAL_DIR = 'Images/minival%d/' % (YEAR) |
158 | 158 | MINIVAL_FULL_DIR = '%s%s' % (ROOT_COCO, MINIVAL_DIR) |
159 | | - MINIVAL_ANN_DIR = 'Annotations/minival%d/' % (ROOT_COCO, YEAR) |
| 159 | + MINIVAL_ANN_DIR = 'Annotations/minival%d/' % (YEAR) |
160 | 160 | MINIVAL_FULL_ANN_DIR = '%s%s' % (ROOT_COCO, MINIVAL_ANN_DIR) |
161 | 161 | if not path.isdir(TRAIN_DIR): |
162 | 162 | mkdir(TRAIN_FULL_DIR) |
|
173 | 173 | SELECTED_FOR_MINIVAL.append(int(RANDOM_IDX)) |
174 | 174 | SELECTED_FOR_TRAIN = sorted( |
175 | 175 | list(set(list(range(len(IMAGE_NAMES)))).difference(SELECTED_FOR_MINIVAL))) |
176 | | - with open('train.txt', 'w') as train_file: |
| 176 | + with open('train2.txt', 'w') as train_file: |
177 | 177 | for idx in SELECTED_FOR_TRAIN: |
178 | 178 | if COPY_FILES: |
179 | 179 | copyfile( |
|
191 | 191 | TRAIN_FULL_ANN_DIR + IMAGE_NAMES[idx] + ".xml") |
192 | 192 | train_file.write( |
193 | 193 | "/" + TRAIN_DIR + IMAGE_NAMES[idx] + ".jpg /" + TRAIN_ANN_DIR + IMAGE_NAMES[idx] + ".xml\n") |
194 | | - with open('minival.txt', 'w')as minival_file: |
| 194 | + with open('minival2.txt', 'w')as minival_file: |
195 | 195 | for idx in SELECTED_FOR_MINIVAL: |
196 | 196 | if COPY_FILES: |
197 | 197 | copyfile( |
|
214 | 214 | minival_file.write( |
215 | 215 | "/" + MINIVAL_DIR + IMAGE_NAMES[idx] + ".jpg /" + MINIVAL_ANN_DIR + IMAGE_NAMES[idx] + ".xml\n") |
216 | 216 | else: |
217 | | - with open('train.txt', 'w') as train_file: |
| 217 | + with open('train2.txt', 'w') as train_file: |
218 | 218 | IMG_RELATIVE = '/Images/train%d/' % (YEAR) |
219 | 219 | TRAIN_ANN_DIR = 'Annotations/train%d/' % (YEAR) |
220 | 220 | TRAIN_FULL_ANN_DIR = "%s%s" % (ROOT_COCO, TRAIN_ANN_DIR) |
|
224 | 224 | train_file.write( |
225 | 225 | IMG_RELATIVE + IMAGE_NAMES[i] + ".jpg /" + TRAIN_ANN_DIR + IMAGE_NAMES[i] + ".xml\n") |
226 | 226 | else: |
227 | | - with open('val.txt', 'w') as val_file: |
| 227 | + with open('val2.txt', 'w') as val_file: |
228 | 228 | IMG_RELATIVE = '/Images/val%d/' % (YEAR) |
229 | 229 | VAL_ANN_DIR = 'Annotations/val%d/' % (YEAR) |
230 | 230 | VALL_FULL_ANN_DIR = '%s%s' % (ROOT_COCO, VAL_ANN_DIR) |
|
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