SSD project based on caffe

Deps

• caffe-ssd: https://github.com/weiliu89/caffe.git
• commit: 9d6e8151eedf3e8d3abaecde47b788a1ec2d2156

Usage:

• create soft link of some bin files(caffe, convert_annoset, get_image_size) with caffe-ssd project
• export PYTHONPATH=$SSD_CAFFE_ROOT/python:$PYTHONPATH
• write labelmap_voc.prototxt files
• run with the continuously num files
• 1_createXml.py: create xml formats from origin labels or use labelImg tools to get the xml format labels
• 2_createTrainVal.py: generate the test and trainval image name lists in ImageSets/Main, generate trainval test file lists and get test image size
• [3_create_list.sh]: optional, 2_createTrainVal.py, generate the test, trainval image lists and get test image size
• 4_create_data.sh: get label map and generate LMDB datas
• 5_ssd_run.py: run ssd training and get the solver.prototxt and train_net
• 6_ssd_run_direct.sh: training the net directly based on the train_net have generated

Note:

• testLabelImgs/JPEGImages: the jpeg images
• testLabelImgs/labels: the labels for each image
• testLabelImgs/Annotations: the labels with .xml format
• testLabelImgs/ImageSets/Main: the test and trainval txt files
• the original labels is created by BBox-Label-Tool, the format is:
  object_num
className x1min y1min x1max y1max
className x2min y2min x2max y2max

Output Dirs

• models:
• examples:
• job:
• results:
• data/test.txt
• data/trainval.txt
• data/test_name_size.txt

Net Instruction

• ``http://www.cnblogs.com/hansjorn/p/7445411.html