运行对象检测评估协议(tensorflow) [英] Run object detection evaluation protocols (tensorflow)

问题描述

我想运行 tensorflow 对象检测评估协议之一 [1].我是新手，从网页上我无法理解我必须在哪里添加 metrics_set 配置.例如:

I want to run one of the tensorflow object detection evaluation protocols [1]. I am new with it, and from the webpage I cannot understand where I would have to add the metrics_set configuration. Ex:

EvalConfig.metrics_set='pascal_voc_detection_metrics'

我尝试更改 eval.proto 文件中的值，其中 metrics_set 设置为值 8.有谁知道这是否是更改它的正确位置?我认为更改此值没有任何影响.8"是什么意思?另外，我期望的输出是什么?

I tried changing the value in the eval.proto file, where metrics_set is set to the value 8. Does anyone know if this is the right place to change it? I saw no effect on changing this value. And what does the "8" mean? In addition, what is the output I am to expect?

更新:我回答了我的一个问题:我应该更改设置的地方不是 eval.proto，而是在配置文件中:

Update: I answered one of my questions: the place where I should change the setting is not the eval.proto, but in the configuration file:

eval_config: {
  metrics_set: 'weighted_pascal_voc_detection_metrics'
}

然而，我仍然不明白我在哪里看到了这个效果——我还有其他问题没有回答.

However, I still do not understand where I am to see the effect of this - I still have the other questions unanswered.

[1]

[1] https://github.com/tensorflow/models/blob/fd7b6887fb294e90356d5664724083d1f61671ef/research/object_detection/g3doc/evaluation_protocols.md

推荐答案

我认为8"只是一个占位符 - 它是 eval.proto 文件中的第 8 个条目.

I think "8" is just a placeholder - it's the 8th entry in the eval.proto file.

当您运行评估作业 (eval.py) 时，您指定的这个 metrics_set 将用作计算 eval_input_reader.结果将输出到以 events.out.tfevents 为前缀的事件摘要文件，您可以使用 TensorBoard 或 event_accumulator 来自 tensorboard.backend.event_processing.不同的指标集会略有不同，但我没有尝试对它们进行评论 - 您必须查看每个协议的详细信息.

When you run an evaluation job (eval.py), this metrics_set you specify is used as the protocol by which to compute the metrics on the data set specified in eval_input_reader. The results are output to an events summary file prefixed with events.out.tfevents, which you can visualize using TensorBoard or event_accumulator from tensorboard.backend.event_processing. Different metrics set would vary slightly but I haven't tried them all to comment - you'll have to look into the details of each protocol.

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