We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
你好, 我参考文章 验证码识别新革命:源码+通用识别模型 已经成功训练出了模型, 想使用 tf2onnx 转换为 onnx 命令如下
python -m tf2onnx.convert --input out/graph/are-CNN5-NoRecurrent-H64-CrossEntropy-C1_9033.pb --inputs input:0 --outputs output:0 --output model.onnx
然后报错提示 output is not in graph
output is not in graph
查找资料后应该是需要 配置 --inputs --outputs , 请问该如何配置该参数?
我也查看了 tf_onnx_util.py 文件, 仍然不知道如何调用?
The text was updated successfully, but these errors were encountered:
No branches or pull requests
你好, 我参考文章 验证码识别新革命:源码+通用识别模型 已经成功训练出了模型, 想使用 tf2onnx 转换为 onnx
命令如下
然后报错提示
output is not in graph
查找资料后应该是需要 配置 --inputs --outputs , 请问该如何配置该参数?
我也查看了 tf_onnx_util.py 文件, 仍然不知道如何调用?
The text was updated successfully, but these errors were encountered: