OpenCV: FFMPEG: tag 0x5634504d/'MP4V' is not supported with codec id 12 and format 'mp4 / MP4 (MPEG-4 Part 14)' OpenCV: FFMPEG: fallback to use tag 0x7634706d/'mp4v' Traceback (most recent call last): File "/usr/local/miniconda3/lib/python3.9/runpy.py", line 197, in _run...
filename:用指定的文件名创建FiledHandler(后边会具体讲解handler的概念),这样日志会被存储在指定的文件中。filemode:文件打开方式,在指定了filename时使用这个参数,默认值为“a”还可指定为“w”。format:指定handler使用的日志显示格式。 datefmt:指定日期时间格式。 level:设置rootlogger(后边会讲解具体概念)的日志级别...
h5_model_path='./my_model_ep{}.h5'.format(epochs) output_path='.' pb_model_name='my_model_ep{}.pb'.format(epochs) """---导入keras模型---""" K.set_learning_phase(0) net_model = load_model(h5_model_path) print('input is :', net_model.input.name) print ('output is:', ...
format(n+1, fullname), file=sys.stderr) import traceback for record in traceback.format_exception(*sys.exc_info()): for line in record.splitlines(): print(' '+line, file=sys.stderr) print("\nRemainder of file ignored", file=sys.stderr) break if reset: known_paths = None return...
from arcface.resnet import resnet_face18 import torch,os from torch2trt import torch2trt current_dir=os.path.dirname(os.path.abspath(__file__)) # 获取当前路径 def load_model(model, pretrained_path, device): print('Loading pretrained model from {}'.format(pretrained_path)) pretrained_dict...
current_dir=os.path.dirname(os.path.abspath(__file__)) # 获取当前路径 def load_model(model, pretrained_path, device): print('Loading pretrained model from {}'.format(pretrained_path)) pretrained_dict = torch.load(pretrained_path, map_location=device) ...
通常要进行软件压力测试的资源包括内部内存、CPU 可用性、磁盘空间和网络带宽。 压力测试涵盖，性能测试，...
export_onnx_file = "./checkpoints/xxx.onnx" # 目的ONNX文件名 print("==> Exporting model to ONNX format at '{}'".format(export_onnx_file))torch.onnx.export(model, x, export_onnx_file, opset_version=9, export_params=True, ...
builder.fp16_mode=True# Parse model fileifnotos.path.exists(onnx_file_path):print('ONNX file {} not found, please run yolov3_to_onnx.py first to generate it.'.format(onnx_file_path)) exit(0)print('Loading ONNX file from path {}...'.format(onnx_file_path))withopen(onnx_fil...
zipfile-based file format. ``torch.load`` still retains the ability to load files in the old format. If for any reason you want ``torch.save`` to use the old format, pass the kwarg ``_use_new_zipfile_serialization=False``.