Open MiKEWUUUU opened 6 years ago
There are two kind of groundtruths in our system:
thanks a lot! I have some new problem, please help me :(
Hi,
tool/demo_img.py
, line 228
The utils
folder also provides more information about how to the prepare the data.
Appreciate for your help, my own dataset works with your help !!! cheers!!!
Great to hear that!
hi nqanh, I found an interesting question, in models/pascal_voc/VGG16/faster_rcnn_end2end/train.prototxt, at line 13, the num_classes is 11, and your comment is "10 obj categories + 1 background" at line 890, the num_output is 10, your comment is "9 affordance classes +1 backgtound" may I ask why the obj classes are different from affordance classes? thanks a lot !!!!
The object class and the affordance class are not the same since they're defined separately.
The object categories refer to the whole object (e.g., pan, bottle, hammer), while the affordace classes are the object parts (e.g, the pan has two affordances: contain and grasp).
hi nqanh, I met a serious problem, I have tested my own object, but I can't get any mask. I wonder know if I used the wrong label name in using "LABEL ME"? Here are my steps,
The process looks ok to me. But maybe something wrong in one of your step.
thanks, I will follow your steps, Would u mind tell me, where I can find the specific affordance ID for IIT-AFF dataset ?
You can download the original version of the IIT-AFF dataset. The IDs are in the ReadMe file.
hi nqanh There is a problem for me. When I used the "labelme_json_to_dataset” function to make my own dataset, the output png file is an "unit16" type .png image. But, the images in your example (eg. /utils/instance_png/0_1.png), the types are "uint8". Can I just transfer the type by using matlab code?
Yes, you can do it if you want. I think "uint16" will work fine too.
hi nqanh, me again, I met a problem when training my own dataset. the error code is : gt_mask = mask_flipped_ims[gt_mask_ind] IndexError: list index out of range I found the code in rpn/proposal_target_layer.py
how can I solve this problem?
thanks a lot
Hi, it seems something missing in your dataset. Please check Issues 8 for a recent discussion.
Basically, By looking at Issues 8, I found that there was only one .sm file for one picture in my dataset, no matter how many goals there were in the picture. Do you think I found the key to the problem?
No, it's not correct. For each object in the xml file, you need a mask groundtruth.
In general, each object in the .xml file must have a groundtruth mask file. The first object in the .xml file should have 'IMGID_1_segmask.sm" mask, the second object in the .xml should have "IMGID_2_segmask.sm", etc.
According to your reply, the number of .sm files must equal to the number of targets in the xml file, otherwise, the training target can not find the ground truth of the mask. Is my understanding correct?
Yes, the number of .sm files must equal to the number of objects in the xml file.
Thank you for your help,and I have another problem here: What I was doing was a job of dividing the Ammeter scale. I found that the segmentation of the small target was not very good. I exported the intermediate model and found that there was no mask at all for the first 60,000 iteration models after 70,000 iteration, there are some mask results(but they are far away from the ground truth mask). Do you think it is not enough iteration for my model?
would you mind to tell me how to produce the "instance_png" images? Is there any requirement for the instance_png? such as: different object need different colour?
thanks