Bad detect result after training
I've trained this network with self defined dataset, configurations are listed below. num_train_image: 700, num_test_image: 300, pretrain_model: models/model_pre_train_syn.caffemodel, resize_height: 384, resize_width: 384, base_lr: 0.0001, batch_size: 50
After 1800 iterations, loss declined from 5.3 to 2.1, but the detection result looks strange. https://drive.google.com/open?id=1_T-Bi89nIU8Z7-xYc9w0Rj9BafpbfTz3 All detection boxes look like triangles and start from the left top corner.
My annotation files look like below, I don't think there are any problems with annotation files. Is there anyone with the same issue?
<annotation>
<folder>train</folder>
<filename>bCXpXXunYpLFXX.jpg</filename>
<size>
<width>800</width>
<height>800</height>
<depth>3</depth>
</size>
<object>
<difficult>0</difficult>
<content>THEREISAWAY</content>
<name>text</name>
<bndbox>
<x1>407</x1>
<y1>413</y1>
<x2>407</x2>
<y2>425</y2>
<x3>598</x3>
<y3>411</y3>
<x4>600</x4>
<y4>397</y4>
<xmin>407</xmin>
<ymin>397</ymin>
<xmax>600</xmax>
<ymax>425</ymax>
</bndbox>
</object>
....
</annotation>
@BIOTONIC The vertexes of the quadrilaterals should be in clockwise.
@MhLiao Thank you for your help. I've checked all my labels and changed the sequence of vertexes into clockwise but still have this problem. Any ideas?
Hi, I have the same bad result. https://drive.google.com/file/d/1HurdKGzqSudUF3yhHPpNn4TGDvL0h0qd @BIOTONIC Are you fixed the error ?
which tool did you use for label image?
which tool did you use for labeling images?
Did you find which tool was used?