Open pecia6 opened 5 years ago
I got the same problem as the above picture, and got some errors about urllib3
.
Can you tell me if you solve this problem now?
change line 57 to utils.draw_bounding_box_on_image_array(img_raw, ymin/scale, xmin/scale, ymax/scale, xmax/scale)
change line 57 to utils.draw_bounding_box_on_image_array(img_raw, ymin/scale, xmin/scale, ymax/scale, xmax/scale)
also need to place ‘_, H, W = img.shape’ after ‘img = img.transpose((2,0,1))’
This work is great but the code is absolutely disaster
Hi Guys, I am sorry you are facing these issue of displacement error. However, I didn't face any such issue when I tested the model on this dataset. However, I need to debug the code once. Give me some time I will rectify the error and get back soon.
And also the problem that was pointed out by
I got the same problem as the above picture, and got some errors about
urllib3
. Can you tell me if you solve this problem now?
I think you shouldn't use torchnet module in test phase since. It's better to clearly seperate the code in train part and test part.
Hi Guys, I am sorry you are facing these issue of displacement error. However, I didn't face any such issue when I tested the model on this dataset. However, I need to debug the code once. Give me some time I will rectify the error and get back soon.
hei, brother, you really did a great work. I can run the test-demo now and get a nice result. Thanks for your work very much.
@dagongji10 Glad that you liked the work. May I know what changes you made in order to make it work?
@dagongji10 Glad that you liked the work. May I know what changes you made in order to make it work?
I think maybe the code ‘_, H, W = img.shape’ should after ‘img = img.transpose((2,0,1))’, so we can get the right H and scale. The box predict is very accurate,but when draw it on img_raw , maybe we can change like that: 'ymin, xmin, ymax, xmax = predbboxes[i,:]/scale' then the box can align to img_raw.
I don't konw whether am i right, but it really works for me.
change line 57 to utils.draw_bounding_box_on_image_array(img_raw, ymin/scale, xmin/scale, ymax/scale, xmax/scale)
also need to place ‘_, H, W = img.shape’ after ‘img = img.transpose((2,0,1))’
thanks bro, nice job, and @aditya-vora nice project ~
Hi Guys, I confirm that your fix solves the displacement problem, but it seems to make the performance worse.
For example, the image I posted previously becomes this:
There are four false negative more and a false positive more.
@pecia6 I am facing same problem with the accuracy. Have you found any solution?
i am facing same problem,Rect not ok
I tested this code on your image and I am also getting the same results. Definitely not OK! Did you find any other better methods for head detector?
Could somebody please share the weights of the pretrained model? it seems to have been taken down You can email me at theefaris@gmail.com if you have the weights, thank you!
I have run "head_detection_demo.py" and I haven't received good results. The bounding boxes seem correct but there is a kind of displacement respect to ground truth.