CODEWITHSUNDEEP
tensorflowobject-detection-apitransfer-learning
sejal_chopra
sejal_chopra

Reputation: 31

Evaluate a model created using Tensorflow Object Detection API

I trained a model using Tensorflow object detection API for detecting swimming pools using satellite images. I used 'faster_rcnn_inception_v2_coco_2018_01_28' model for training. I generated a frozen inference graph (.pb). I want to evaluate the precision and recall of the model. Can someone tell me how I can do that, preferably without using pycocotools as I was facing some issues with that. Any suggestions are welcome :)

Upvotes: 1

Views: 1501

Answers (1)

Janikan
Janikan

Reputation: 370

From the Object Detection API you can run "eval.py" from "models/research/object_detection/legacy/".

Your have to define an evaluation metric in your config file (see the supported evaluation protocols)

For example:

   eval_config: {metrics_set: "coco_detection_metrics"}

The Pascal VOC e.g. then gives you the mean Average Precsion (mAP)

Upvotes: 2

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