请问 Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz 处理器应该是intel平台么？不在这个amd和arm范围内吧？

这是docker

这是postman

base64

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

最开始我测试时报了这个错 我看了app.py 25行这个地方

以为是那两个文件需要替换 结果替换过之后又报了另一个错，大佬帮忙看下呗

TypeError: Cannot interpret feed_dict key as Tensor: Tensor Tensor("Placeholder:0", shape=(3, 3, 1, 64), dtype=float32) is not an element of this graph.

一次请求的完整报错:

[2019-12-19 16:41:21,102] ERROR in app: Exception on /verify/base64/ [POST]
Traceback (most recent call last):
  File "/media/pi/udisk/projects/12306_code_server/venv/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1119, in _run
    subfeed, allow_tensor=True, allow_operation=False)
  File "/media/pi/udisk/projects/12306_code_server/venv/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 3468, in as_graph_element
    return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
  File "/media/pi/udisk/projects/12306_code_server/venv/lib/python3.7/site-packages/tensorflow_core/python/framework/ops.py", line 3547, in _as_graph_element_locked
    raise ValueError("Tensor %s is not an element of this graph." % obj)
ValueError: Tensor Tensor("Placeholder:0", shape=(3, 3, 1, 64), dtype=float32) is not an element of this graph.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/media/pi/udisk/projects/12306_code_server/venv/lib/python3.7/site-packages/flask/app.py", line 2446, in wsgi_app
    response = self.full_dispatch_request()
  File "/media/pi/udisk/projects/12306_code_server/venv/lib/python3.7/site-packages/flask/app.py", line 1944, in full_dispatch_request
    self.try_trigger_before_first_request_functions()
  File "/media/pi/udisk/projects/12306_code_server/venv/lib/python3.7/site-packages/flask/app.py", line 1992, in try_trigger_before_first_request_functions
    func()
  File "/home/pi/udisk/projects/12306_code_server/app.py", line 23, in load_model
    textModel = models.load_model('model.v2.0.h5')
  File "/media/pi/udisk/projects/12306_code_server/venv/lib/python3.7/site-packages/keras/engine/saving.py", line 419, in load_model
    model = _deserialize_model(f, custom_objects, compile)
  File "/media/pi/udisk/projects/12306_code_server/venv/lib/python3.7/site-packages/keras/engine/saving.py", line 287, in _deserialize_model
    K.batch_set_value(weight_value_tuples)
  File "/media/pi/udisk/projects/12306_code_server/venv/lib/python3.7/site-packages/keras/backend/tensorflow_backend.py", line 2470, in batch_set_value
    get_session().run(assign_ops, feed_dict=feed_dict)
  File "/media/pi/udisk/projects/12306_code_server/venv/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 956, in run
    run_metadata_ptr)
  File "/media/pi/udisk/projects/12306_code_server/venv/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1122, in _run
    e.args[0])
TypeError: Cannot interpret feed_dict key as Tensor: Tensor Tensor("Placeholder:0", shape=(3, 3, 1, 64), dtype=float32) is not an element of this graph.

在同一台设备上，我使用 12306 python程序本地识别验证码可以正常使用，

但是当我 clone 这个项目，准备搭建验证码识别服务，运行后，请求时出现这个错误，服务无法正常使用

您已设置使用云打码，但是服务器资源有限，请尽快改为本地打码
验证码识别坐标为184,77,184,149
184,77,184,149
验证码通过,开始登录..
url: /passport/web/login返回参数为空, 接口状态码: 302
url: /passport/web/login返回参数为空, 接口状态码: 302
url: /passport/web/login返回参数为空, 接口状态码: 302
url: /passport/web/login返回参数为空, 接口状态码: 302
url: /passport/web/login返回参数为空, 接口状态码: 302
url: /passport/web/login返回参数为空, 接口状态码: 302

我看这个文档里面只有arm和amd，不懂有没有x86平台的docker部署方法

RT,已安装，后台运行gunicorn,不知道如何测试?

其他版本的下载地址
https://www.tensorflow.org/lite/guide/python

2. 安装依赖 自行根据平台和python选择对应的tflite（下面的例子为amd64，python3.7）
   pip3 install -r requirements.txt

ERROR: tflite_runtime-1.14.0-cp37-cp37m-linux_x86_64.whl is not a supported wheel on this platform.

执行gunicorn app:app -c gunicorn.conf.py时报错：
-bash: gunicorn: command not found

作者，您好！
我将您的docker run之后 不知道具体怎么提交，能否将post提交的规范详细一些呢？ 我尝试了不同的提交均失败告终，无奈请教您！！盼相助