tensorflow / tensorflow/models
Low mAP due to wrong num_gt
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Since Jan 12, 2021.
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Description
I run the tensorflow 2.3 Object Detection API on my own dataset, but the mAP is very low.
Since I have dense objects on the images, I changed the (max_number_of_boxes) here to 600.
I used the evaluation protocol of pascal_voc_detection_metrics.
After running the model_main_tf2.py with checkpoint_dir for evaluation on 30 images, we can find the printed num_gt, precision and recall from here are weird as showed below.
The max_number_of_boxes is 600 as shown in eval_input_reader (in Configuration file) below for each images. Thus, I guess the num_gt=18000 is actuallly the sum for 30 images. And when I change the max_number_of_boxes, the num_gt will change, correspondingly!
In additon, the result for the same dataset in tensorflow 1.13 seems correct.
num-gt=6474, which is right.
How can I get the right num_gt? Please do me a favor. Many thanks!
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