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code/annotation_xml_parser.py
0 → 100644
| 1 | +import xml.etree.ElementTree as elemTree | ||
| 2 | +import os | ||
| 3 | + | ||
| 4 | +CLASSES = ['dog'] | ||
| 5 | + | ||
| 6 | +def parseFile(path): | ||
| 7 | + result = "" | ||
| 8 | + annotation = elemTree.parse(path) | ||
| 9 | + | ||
| 10 | + filename = annotation.find('filename') | ||
| 11 | + size = annotation.find('size') | ||
| 12 | + width = size.find('width') | ||
| 13 | + height = size.find('height') | ||
| 14 | + | ||
| 15 | + result += filename.text + ' ' + width.text + ' ' + height.text | ||
| 16 | + for obj in annotation.findall('./object'): | ||
| 17 | + name = obj.find('name') | ||
| 18 | + box = obj.find('bndbox') | ||
| 19 | + | ||
| 20 | + label_index = CLASSES.index(name.text) | ||
| 21 | + xmin = box.find('xmin') | ||
| 22 | + ymin = box.find('ymin') | ||
| 23 | + xmax = box.find('xmax') | ||
| 24 | + ymax = box.find('ymax') | ||
| 25 | + | ||
| 26 | + result += ' ' + str(label_index) + ' ' + xmin.text + ' ' + ymin.text + ' ' + xmax.text + ' ' + ymax.text | ||
| 27 | + | ||
| 28 | + return result | ||
| 29 | + | ||
| 30 | + | ||
| 31 | +def parseDir(path): | ||
| 32 | + result = "" | ||
| 33 | + for file in os.listdir(path): | ||
| 34 | + if file.split('.')[-1] != 'xml': | ||
| 35 | + continue | ||
| 36 | + | ||
| 37 | + result += parseFile(path+'/'+file) + '\n' | ||
| 38 | + return result | ||
| 39 | + | ||
| 40 | + | ||
| 41 | +directory = input('Input directory, or 0 to exit: ') | ||
| 42 | + | ||
| 43 | +if directory != '0': | ||
| 44 | + result = parseDir(directory) | ||
| 45 | + file = open(directory+'/'+'annotation.txt','w') | ||
| 46 | + file.write(result) | ||
| 47 | + file.close() | ||
| 48 | + print("Complete!") |
code/dataset_splitter.py
0 → 100644
| 1 | +import os | ||
| 2 | +import tensorflow as tf | ||
| 3 | + | ||
| 4 | +all_path = '../data/annotation.txt' | ||
| 5 | +train_path = '../data/train.txt' | ||
| 6 | +val_path = '../data/val.txt' | ||
| 7 | +test_path = '../data/test.txt' | ||
| 8 | + | ||
| 9 | +allFile = open(all_path, 'r') | ||
| 10 | +allFile_lines = allFile.readlines() | ||
| 11 | +allFile.close() | ||
| 12 | + | ||
| 13 | +dataset_size = len(allFile_lines) | ||
| 14 | + | ||
| 15 | +train_size = int(0.7 * dataset_size) | ||
| 16 | +val_size = int(0.15 * dataset_size) | ||
| 17 | +test_size = int(0.15 * dataset_size) | ||
| 18 | + | ||
| 19 | +full_dataset = tf.data.TextLineDataset(all_path) | ||
| 20 | +full_dataset = full_dataset.shuffle(dataset_size) | ||
| 21 | +train_dataset = full_dataset.take(train_size) | ||
| 22 | +test_dataset = full_dataset.skip(train_size) | ||
| 23 | +val_dataset = test_dataset.skip(test_size) | ||
| 24 | +test_dataset = test_dataset.take(test_size) | ||
| 25 | + | ||
| 26 | +train_dataset = list(train_dataset) | ||
| 27 | +val_dataset = list(val_dataset) | ||
| 28 | +test_dataset = list(test_dataset) | ||
| 29 | + | ||
| 30 | +writer = open(train_path, 'w') | ||
| 31 | +for data in train_dataset: | ||
| 32 | + writer.write(data.numpy().decode('ascii') + '\n') | ||
| 33 | +writer.close() | ||
| 34 | + | ||
| 35 | +writer = open(val_path, 'w') | ||
| 36 | +for data in val_dataset: | ||
| 37 | + writer.write(data.numpy().decode('ascii') + '\n') | ||
| 38 | +writer.close() | ||
| 39 | + | ||
| 40 | +writer = open(test_path, 'w') | ||
| 41 | +for data in test_dataset: | ||
| 42 | + writer.write(data.numpy().decode('ascii') + '\n') | ||
| 43 | +writer.close() | ||
| 44 | + | ||
| 45 | +print('train dataset counts:', len(train_dataset)) | ||
| 46 | +print('validation dataset counts:', len(val_dataset)) | ||
| 47 | +print('test dataset counts:', len(test_dataset)) | ||
| 48 | + | ||
| 49 | +reader = open(train_path, 'r') | ||
| 50 | +train_file = reader.readlines() | ||
| 51 | +reader.close() | ||
| 52 | +train_file.sort() | ||
| 53 | + | ||
| 54 | +writer = open(train_path, 'w') | ||
| 55 | +for i in range(len(train_file)): | ||
| 56 | + writer.write(str(i) + ' ' + train_file[i]) | ||
| 57 | +writer.close() | ||
| 58 | + | ||
| 59 | +reader = open(val_path, 'r') | ||
| 60 | +val_file = reader.readlines() | ||
| 61 | +reader.close() | ||
| 62 | +val_file.sort() | ||
| 63 | + | ||
| 64 | +writer = open(val_path, 'w') | ||
| 65 | +for i in range(len(val_file)): | ||
| 66 | + writer.write(str(i) + ' ' + val_file[i]) | ||
| 67 | +writer.close() | ||
| 68 | + | ||
| 69 | +reader = open(test_path, 'r') | ||
| 70 | +test_file = reader.readlines() | ||
| 71 | +reader.close() | ||
| 72 | +test_file.sort() | ||
| 73 | + | ||
| 74 | +writer = open(test_path, 'w') | ||
| 75 | +for i in range(len(test_file)): | ||
| 76 | + writer.write(str(i) + ' ' + test_file[i]) | ||
| 77 | +writer.close() | ||
| ... | \ No newline at end of file | ... | \ No newline at end of file |
data/annotation.txt
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data/test.txt
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data/train.txt
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data/val.txt
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