Python path_join示例

示例#1

文件： run_demo.py 项目： martinkersner/py-DeconvNet

def main():
  config = {}
  config['imageset'] = 'test'
  config['cmap']= './voc_gt_cmap.mat'
  config['gpuNum'] = 0
  config['Path.CNN.caffe_root'] = './caffe'
  config['save_root'] = './results'

  # cache FCN-8s results
  config['write_file'] = 1 # used to be 1
  config['Path.CNN.script_path'] = './FCN'
  config['Path.CNN.model_data'] = path_join(config['Path.CNN.script_path'], 
                                  'fcn-8s-pascal.caffemodel')
  config['Path.CNN.model_proto'] = path_join(config['Path.CNN.script_path'], 
                                   'fcn-8s-pascal-deploy.prototxt')
  config['im_sz'] = 500
  
  #cache_FCN8s_results(config, VOCopts)
  
  # generate EDeconvNet+CRF results
  config['write_file'] = 1 
  config['edgebox_cache_dir'] = './data/edgebox_cached/VOC2012_TEST'
  config['Path.CNN.script_path'] = './DeconvNet'
  config['Path.CNN.model_data'] = path_join(config['Path.CNN.script_path'],
                                  'DeconvNet_trainval_inference.caffemodel')
  config['Path.CNN.model_proto'] = path_join(config['Path.CNN.script_path'], 
                                   'DeconvNet_inference_deploy_modified.prototxt')
  config['max_proposal_num'] = 50
  config['im_sz'] = 224
  config['fcn_score_dir'] = './results/FCN8s'
  
  generate_EDeconvNet_CRF_results(config, VOCopts)

示例#2

def main():
    config = {}
    config['imageset'] = 'test'
    config['cmap'] = './voc_gt_cmap.mat'
    config['gpuNum'] = 0
    config['Path.CNN.caffe_root'] = './caffe'
    config['save_root'] = './results'

    # cache FCN-8s results
    config['write_file'] = 1  # used to be 1
    config['Path.CNN.script_path'] = './FCN'
    config['Path.CNN.model_data'] = path_join(config['Path.CNN.script_path'],
                                              'fcn-8s-pascal.caffemodel')
    config['Path.CNN.model_proto'] = path_join(
        config['Path.CNN.script_path'], 'fcn-8s-pascal-deploy.prototxt')
    config['im_sz'] = 500

    #cache_FCN8s_results(config, VOCopts)

    # generate EDeconvNet+CRF results
    config['write_file'] = 1
    config['edgebox_cache_dir'] = './data/edgebox_cached/VOC2012_TEST'
    config['Path.CNN.script_path'] = './DeconvNet'
    config['Path.CNN.model_data'] = path_join(
        config['Path.CNN.script_path'],
        'DeconvNet_trainval_inference.caffemodel')
    config['Path.CNN.model_proto'] = path_join(
        config['Path.CNN.script_path'],
        'DeconvNet_inference_deploy_modified.prototxt')
    config['max_proposal_num'] = 50
    config['im_sz'] = 224
    config['fcn_score_dir'] = './results/FCN8s'

    generate_EDeconvNet_CRF_results(config, VOCopts)

示例#3

文件： run_demo.py 项目： martinkersner/py-DecoupledNet

def main():
  # 'Full', '25', '10', '5'
  annotations = 'Full'
  
  config = {}
  config['imageset'] = 'test'
  config['cmap']= './voc_gt_cmap.mat'
  config['gpuNum'] = 0
  config['Path.CNN.caffe_root'] = './caffe'
  config['save_root'] = './results'

  ## configuration
  config['write_file'] = 1
  config['thres'] = 0.5
  config['im_sz'] = 320
  config['num_classes'] = 20

  if annotations == 'Full':
    ## DecoupledNet Full annotations
    config['model_name'] = 'DecoupledNet_Full_anno';
    config['Path.CNN.script_path'] = './DecoupledNet_Full_anno';
    config['Path.CNN.model_data'] = path_join(config['Path.CNN.script_path'],
                                    'DecoupledNet_Full_anno_inference.caffemodel')
    config['Path.CNN.model_proto'] = path_join(config['Path.CNN.script_path'], 
                                     'DecoupledNet_Full_anno_inference_deploy.prototxt')

  elif annotations == '25':
    ## DecoupledNet 25 annotations
    config['model_name'] = 'DecoupledNet_25_anno'
    config['Path.CNN.script_path'] = './DecoupledNet_25_anno'
    config['Path.CNN.model_data'] = path_join(config['Path.CNN.script_path'], 
                                    'DecoupledNet_25_anno_inference.caffemodel')
    config['Path.CNN.model_proto'] = path_join(config['Path.CNN.script_path'], 
                                     'DecoupledNet_25_anno_inference_deploy.prototxt')
    
  elif annotations == '10':
    ## DecoupledNet 10 annotations
    config['model_name'] = 'DecoupledNet_10_anno'
    config['Path.CNN.script_path'] = './DecoupledNet_10_anno'
    config['Path.CNN.model_data'] = path_join(config['Path.CNN.script_path'], 
                                    'DecoupledNet_10_anno_inference.caffemodel')
    config['Path.CNN.model_proto'] = path_join(config['Path.CNN.script_path'], 
                                     'DecoupledNet_10_anno_inference_deploy.prototxt')
    
  elif annotations == '5':
    ## DecoupledNet 5 annotations
    config['model_name'] = 'DecoupledNet_5_anno'
    config['Path.CNN.script_path'] = './DecoupledNet_5_anno'
    config['Path.CNN.model_data'] = path_join(config['Path.CNN.script_path'], 
                                    'DecoupledNet_5_anno_inference.caffemodel')
    config['Path.CNN.model_proto'] = path_join(config['Path.CNN.script_path'], 
                                     'DecoupledNet_5_anno_inference_deploy.prototxt')
    
  else:
    print "You have to specify the number of employed annotations."
    exit()
  
  DecoupledNet_inference(config)

示例#4

文件： run_demo.py 项目： martinkersner/py-DecoupledNet

def main():
    # 'Full', '25', '10', '5'
    annotations = 'Full'

    config = {}
    config['imageset'] = 'test'
    config['cmap'] = './voc_gt_cmap.mat'
    config['gpuNum'] = 0
    config['Path.CNN.caffe_root'] = './caffe'
    config['save_root'] = './results'

    ## configuration
    config['write_file'] = 1
    config['thres'] = 0.5
    config['im_sz'] = 320
    config['num_classes'] = 20

    if annotations == 'Full':
        ## DecoupledNet Full annotations
        config['model_name'] = 'DecoupledNet_Full_anno'
        config['Path.CNN.script_path'] = './DecoupledNet_Full_anno'
        config['Path.CNN.model_data'] = path_join(
            config['Path.CNN.script_path'],
            'DecoupledNet_Full_anno_inference.caffemodel')
        config['Path.CNN.model_proto'] = path_join(
            config['Path.CNN.script_path'],
            'DecoupledNet_Full_anno_inference_deploy.prototxt')

    elif annotations == '25':
        ## DecoupledNet 25 annotations
        config['model_name'] = 'DecoupledNet_25_anno'
        config['Path.CNN.script_path'] = './DecoupledNet_25_anno'
        config['Path.CNN.model_data'] = path_join(
            config['Path.CNN.script_path'],
            'DecoupledNet_25_anno_inference.caffemodel')
        config['Path.CNN.model_proto'] = path_join(
            config['Path.CNN.script_path'],
            'DecoupledNet_25_anno_inference_deploy.prototxt')

    elif annotations == '10':
        ## DecoupledNet 10 annotations
        config['model_name'] = 'DecoupledNet_10_anno'
        config['Path.CNN.script_path'] = './DecoupledNet_10_anno'
        config['Path.CNN.model_data'] = path_join(
            config['Path.CNN.script_path'],
            'DecoupledNet_10_anno_inference.caffemodel')
        config['Path.CNN.model_proto'] = path_join(
            config['Path.CNN.script_path'],
            'DecoupledNet_10_anno_inference_deploy.prototxt')

    elif annotations == '5':
        ## DecoupledNet 5 annotations
        config['model_name'] = 'DecoupledNet_5_anno'
        config['Path.CNN.script_path'] = './DecoupledNet_5_anno'
        config['Path.CNN.model_data'] = path_join(
            config['Path.CNN.script_path'],
            'DecoupledNet_5_anno_inference.caffemodel')
        config['Path.CNN.model_proto'] = path_join(
            config['Path.CNN.script_path'],
            'DecoupledNet_5_anno_inference_deploy.prototxt')

    else:
        print "You have to specify the number of employed annotations."
        exit()

    DecoupledNet_inference(config)