# limitations under the License. from utils.util import AttrDict, merge_cfg_from_args, get_arguments import os args = get_arguments() cfg = AttrDict() # 待预测图像所在路径 cfg.data_dir = os.path.join("data", "testing_images") # 待预测图像名称列表 cfg.data_list_file = os.path.join("data", "test_id.txt") # 模型加载路径 cfg.model_path = args.example # 预测结果保存路径 cfg.vis_dir = "result" # 预测类别数 cfg.class_num = 20 # 均值, 图像预处理减去的均值 cfg.MEAN = 0.406, 0.456, 0.485 # 标准差,图像预处理除以标准差 cfg.STD = 0.225, 0.224, 0.229 # 多尺度预测时图像尺寸 cfg.multi_scales = (377, 377), (473, 473), (567, 567) # 多尺度预测时图像是否水平翻转 cfg.flip = True merge_cfg_from_args(args, cfg)
# distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from utils.util import AttrDict, merge_cfg_from_args, get_arguments import os args = get_arguments() cfg = AttrDict() # 待预测图像所在路径 cfg.data_dir = os.path.join(args.example, "data", "test_images") # 待预测图像名称列表 cfg.data_list_file = os.path.join(args.example, "data", "test.txt") # 模型加载路径 cfg.model_path = os.path.join(args.example, "model") # 预测结果保存路径 cfg.vis_dir = os.path.join(args.example, "result") # 预测类别数 cfg.class_num = 2 # 均值, 图像预处理减去的均值 cfg.MEAN = 127.5, 127.5, 127.5 # 标准差,图像预处理除以标准差 cfg.STD = 127.5, 127.5, 127.5 # 待预测图像输入尺寸 cfg.input_size = 1536, 576 merge_cfg_from_args(args, cfg)
import os from utils.util import AttrDict, get_arguments, merge_cfg_from_args args = get_arguments() cfg = AttrDict() # 待预测图像所在路径 cfg.data_dir = os.path.join(args.example, "data", "SemirClothes") # cfg.data_dir = 'E:\\SemirClothes' # 待预测图像名称列表 cfg.data_list_file = os.path.join(args.example, "data", "semirlist.txt") # 模型加载路径 cfg.model_path = os.path.join(args.example, "ACE2P") # 预测结果保存路径 cfg.vis_dir = os.path.join(args.example, "result_semirclothe") # 预测类别数 cfg.class_num = 20 # 均值, 图像预处理减去的均值 cfg.MEAN = 0.406, 0.456, 0.485 # 标准差,图像预处理除以标准差 cfg.STD = 0.225, 0.224, 0.229 # 多尺度预测时图像尺寸 cfg.multi_scales = (377, 377), (473, 473), (567, 567) # 多尺度预测时图像是否水平翻转 cfg.flip = True merge_cfg_from_args(args, cfg)