小编y_ *_*ani的帖子

我尝试使用 DeepLab v3+ 进行语义分割，但结果全黑。

我删除了原始文件，并将原始数据分别放在 ImageSets/,JPEGImages/ 和 SegmentationClass/ 中。

我根据 PASCAL VOC 2012 颜色的规则准备了 SegmentationClassRaw 图像。

我编辑了 build_voc2012_data.py 和 segmenting_dataset.py

[build_voc2012_data.py]

FLAGS = tf.app.flags.FLAGS

tf.app.flags.DEFINE_string('image_folder',
                           './VOCdevkit/VOC2012/JPEGImages',
                           'Folder containing images.')

tf.app.flags.DEFINE_string(
    'semantic_segmentation_folder',
    './VOCdevkit/VOC2012/SegmentationClassRaw',
    'Folder containing semantic segmentation annotations.')

tf.app.flags.DEFINE_string(
    'list_folder',
    './VOCdevkit/VOC2012/ImageSets/Segmentation',
    'Folder containing lists for training and validation')

tf.app.flags.DEFINE_string(
    'output_dir',
    './tfrecord',
    'Path to save converted SSTable of TensorFlow examples.')


_NUM_SHARDS = 4

# add -->>
FLAGS.image_folder = "./pascal_voc_seg/VOCdevkit/VOC2012/JPEGImages"
FLAGS.semantic_segmentation_folder = "./pascal_voc_seg/VOCdevkit/VOC2012/SegmentationClassRaw"
FLAGS.list_folder = "./pascal_voc_seg/VOCdevkit/VOC2012/ImageSets/Segmentation"
FLAGS.image_format = "png"
FLAGS.output_dir = "./pascal_voc_seg/tfrecord"
# …