nightrome / cocostuff10k Goto Github PK

Hello after running the run_cocostuff_vgg16.sh script, I am getting this error :

Could not open or find file cocostuff/data/annotations/COCO_train2014_000000034795.png

It happens because all files' formats are .mat under annotations folder. I think this step doing it but I don't have any MATLAB experience and knowledge.

Convert the annotations by running the Matlab script: startup(); convertAnnotationsDeeplab();

thank you for all helps.

I download the cocostuff-10k-v1.1.zip. when i extract it, error occured.
Could you help check it?

Should it be 183 or 172?

I would like to use this stuff annotation tool to annotate another dataset(like coco-format)
but how can I generate data/input/regions/***.mat ?

Thanks for your great works. But I have questions : 1. Could this tool make bboxes of objects? 2. Could this tool make captions of single image? 3. Should all parts be labeled as some names?
Thanks a lot.

Hi, @nightrome , I appreciate for your works, it really helpful. But for fair comparison, I have to evaluate the models on the older COCO_stuff dataset, i.e., vision 1.0. I have no idea about the full class list of it which only contains 172 classes. Can you help me to get these information? Thanks a lot.

Hi
I have annotated json files of each image made through (labelme) tool how should I convert this into cocostuff dataset formt?

Hi all,

While I was using annotator to convert my own annotations to DeepLab format, I failed to do so.

Here is what I did,

1. I followed the procedure and ran the Matlab command "CocoStuffAnnotator()". I was able to annotate my own image and saved changes.
2. I then ran the Matalb command "convertAnnotationsDeeplab()". But Matlab gave me an error message like this:

   Reference to non-existent field 'S'.
     Error in convertAnnotationsDeeplab (line 26)
     labelMap = labelStruct.S;

3. Since I did not change any line of code in Matlab scripts, I was thinking maybe something went wrong with my image file. Then I compared the example annotated image file and then applied my own annotation to that file. Interestingly, the results are different.
   Here is the labelStruct content of file annotated by myself:

COCO_train2014_000000439995_2.mat
      drawSizeMap: [427×640 double]
         imageIdx: 2
        imageName: 'COCO_train2014_000000439995'
        imageSize: [427 640 3]
         labelMap: [427×640 double]
       labelNames: {94×1 cell}
      timeDiffMap: [427×640 double]
        timeImage: 19.6003
    timeImageDraw: 0
          timeMap: [427×640 double]
        timeTotal: 6.4350
         userName: 'example'

Here is the labelStruct content of default annotated file:

COCO_train2014_000000439995.mat
                    S: [427×640 double]
             captions: {5×1 cell}
                names: {182×1 cell}
    regionLabelsStuff: [925×1 double]
       regionMapStuff: [427×640 double]

Clearly, the output of CocoStuff annotator does not contain field "S", which could fail the Matalb command "convertAnnotationsDeeplab(). Why is that?

Thanks in advance!

Hi I am trying to convert the provided json file cocostuff-10k-v1.1.json to t7 format using coco api available here. I am using the lua function coco.CocoApi("cocostuff-10k-v1.1.json") to do this. Iam getting an error
convert: cocostuff-10k-v1.1.json --> .t7 [please be patient] ...ri/mnt_hari/torch/install/share/lua/5.1/coco/CocoApi.lua:142: Expected comma or array end but found T_OBJ_BEGIN at character 104320833 stack traceback: [C]: in function 'decode' ...ri/mnt_hari/torch/install/share/lua/5.1/coco/CocoApi.lua:142: in function '__convert' ...ri/mnt_hari/torch/install/share/lua/5.1/coco/CocoApi.lua:128: in function '__init' ...hari/mnt_hari/torch/install/share/lua/5.1/torch/init.lua:91: in function <...hari/mnt_hari/torch/install/share/lua/5.1/torch/init.lua:87> [C]: in function 'CocoApi' [string "_RESULT={coco.CocoApi("cocostuff-10k-v1.1.jso..."]:1: in main chunk [C]: in function 'xpcall' ...hari/mnt_hari/torch/install/share/lua/5.1/trepl/init.lua:661: in function 'repl' ...hari/torch/install/lib/luarocks/rocks/trepl/scm-1/bin/th:204: in main chunk [C]: at 0x00405d50 [1.4312s]
while running this. Is there a way to do this?

It cannot access gasonMex.CPP file even the path is given

Matlab is generating following error upon executing "demo_cocoStuff();" after "startup();"

Undefined function or variable 'imageInsertBlobLabels'.
Error in demo_cocoStuff (line 52)
labelMapThingsIm = imageInsertBlobLabels(labelMapThingsIm, labelMapThings, labelNames);

Additional paths are required in startup.m for specifying location of extra source files in Matlab 2015b.

addpath('dataset/code/utils');
addpath('dataset/code/conversion');

Hi，

First of all, thanks for your great work.

My question is, after I finished training my model, the training process gave me some results for my test set. Those results are in .mat format. Is there any script that I can use to visualize .mat files (e.g., a script that help me convert .mat file into .png file with different color for different class)? I have been searching a lot but I am not a Matlab guru.

Thanks in advance!

Hi , for saving time, could you share the trained Deeplab models(resnet101, vgg16)?

Hello
I want to load this dataset by using pycocotools but I got this problem

And I am quite confused about some part of the file 'cocostuff-10k-v1.1.json'

In Annotation tool,
While doing this step: Extract the thing annotations for all images in Matlab: extractThings()
I get error on Matlab
Loading and preparing annotations... Undefined function or variable 'gasonMex'
Did anyone had similar issue or know how to fix it?
Thank you!

Is cocostuff available in the coco json annotation format?

Hello! I download COCO dataset for training dataset on YOLO. But annotations turns out on .json format. How i convert them to YOLO? YOLO have a .txt labels .

Thanks, and sorry if my question is stupid :-)

Hi,

Can I use this directly on images to get results ?

If I download the Semantic Segmentation Models will it work ?

Thanks

hi~
I download the code of SLIC_mex.
i run the code of SLIC_mex successfully.
but how to generate data/input/regions/***.mat?

my software:matlabR2016a

Thanks for your great work, but I met this following problems:

extractThings
Loading COCO API...
Loading and preparing annotations... DONE (t=11.14s).
Error using containers.Map/subsref
The specified key is not present in this container.

Error in CocoApi/getAnnIds (line 121)
t = coco.loadAnns(coco.inds.imgAnnIdsMap(imgIds));

Error in extractThings>getImLabelMap (line 88)
annIds = cocoApi.getAnnIds('imgIds', imgId, 'iscrowd', []);

Error in extractThings (line 71)
labelMap = getImLabelMap(cocoApi, image, imageName);

Could u tell me what's wrong here? I use new dataset. And I want to create new annotation of new classes. Thanks a lot.

Is the normal annotation (coco) of things not included in the JSON of stuff? As in how would i get the category of every object on an image and not just the category other for all the thing classes?

Thanks for your code.The following is the result after I implemented the command :bash run_cocostuff.sh.I don't kown where is wrong and how to solve it.Can you help me?

layer {
name: "drop7_2"
type: "Dropout"
bottom: "fc7_2"
top: "fc7_2"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc8_cocostuff_2"
type: "Convolution"
bottom: "fc7_2"
top: "fc8_cocostuff_2"
convolution_param {
num_output: 172
kernel_size: 1
}
}
layer {
name: "fc6_3"
type: "Convolution"
bottom: "pool5"
top: "fc6_3"
convolution_param {
num_output: 1024
pad: 18
kernel_size: 3
dilation: 18
}
}
layer {
name: "relu6_3"
type: "ReLU"
bottom: "fc6_3"
top: "fc6_3"
}
layer {
name: "drop6_3"
type: "Dropout"
bottom: "fc6_3"
top: "fc6_3"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc7_3"
type: "Convolution"
bottom: "fc6_3"
top: "fc7_3"
convolution_param {
num_output: 1024
kernel_size: 1
}
}
layer {
name: "relu7_3"
type: "ReLU"
bottom: "fc7_3"
top: "fc7_3"
}
layer {
name: "drop7_3"
type: "Dropout"
bottom: "fc7_3"
top: "fc7_3"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc8_cocostuff_3"
type: "Convolution"
bottom: "fc7_3"
top: "fc8_cocostuff_3"
convolution_param {
num_output: 172
kernel_size: 1
}
}
layer {
name: "fc6_4"
type: "Convolution"
bottom: "pool5"
top: "fc6_4"
convolution_param {
num_output: 1024
pad: 24
kernel_size: 3
dilation: 24
}
}
layer {
name: "relu6_4"
type: "ReLU"
bottom: "fc6_4"
top: "fc6_4"
}
layer {
name: "drop6_4"
type: "Dropout"
bottom: "fc6_4"
top: "fc6_4"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc7_4"
type: "Convolution"
bottom: "fc6_4"
top: "fc7_4"
convolution_param {
num_output: 1024
kernel_size: 1
}
}
layer {
name: "relu7_4"
type: "ReLU"
bottom: "fc7_4"
top: "fc7_4"
}
layer {
name: "drop7_4"
type: "Dropout"
bottom: "fc7_4"
top: "fc7_4"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc8_cocostuff_4"
type: "Convolution"
bottom: "fc7_4"
top: "fc8_cocostuff_4"
convolution_param {
num_output: 172
kernel_size: 1
}
}
layer {
name: "fc8_cocostuff"
type: "Eltwise"
bottom: "fc8_cocostuff_1"
bottom: "fc8_cocostuff_2"
bottom: "fc8_cocostuff_3"
bottom: "fc8_cocostuff_4"
top: "fc8_cocostuff"
eltwise_param {
operation: SUM
}
}
layer {
name: "fc8_interp"
type: "Interp"
bottom: "fc8_cocostuff"
top: "fc8_interp"
interp_param {
zoom_factor: 8
}
}
layer {
name: "fc8_mat"
type: "MatWrite"
bottom: "fc8_interp"
include {
phase: TEST
}
mat_write_param {
prefix: "cocostuff/features/deeplabv2_vgg16/val/fc8/"
source: "cocostuff/list/val_id.txt"
strip: 0
period: 1
}
}
layer {
name: "silence"
type: "Silence"
bottom: "label"
bottom: "data_dim"
}
I0616 15:55:01.469554 6570 layer_factory.hpp:77] Creating layer data
I0616 15:55:01.469599 6570 net.cpp:106] Creating Layer data
I0616 15:55:01.469609 6570 net.cpp:411] data -> data
I0616 15:55:01.469641 6570 net.cpp:411] data -> label
I0616 15:55:01.469656 6570 net.cpp:411] data -> data_dim
I0616 15:55:01.469676 6570 image_seg_data_layer.cpp:46] Opening file cocostuff/list/val.txt
I0616 15:55:01.470676 6570 image_seg_data_layer.cpp:68] A total of 1000 images.
F0616 15:55:01.510185 6570 syncedmem.hpp:18] Check failed: error == cudaSuccess (30 vs. 0) unknown error
*** Check failure stack trace: ***
@ 0x7fbaaa9dadaa (unknown)
@ 0x7fbaaa9dace4 (unknown)
@ 0x7fbaaa9da6e6 (unknown)
@ 0x7fbaaa9dd687 (unknown)
@ 0x7fbaab106ca8 caffe::SyncedMemory::mutable_cpu_data()
@ 0x7fbaab115f0c caffe::Blob<>::Reshape()
@ 0x7fbaab1163a9 caffe::Blob<>::Reshape()
@ 0x7fbaab00c95a caffe::ImageSegDataLayer<>::DataLayerSetUp()
@ 0x7fbaab08c3d3 caffe::ImageDimPrefetchingDataLayer<>::LayerSetUp()
@ 0x7fbaab159005 caffe::Net<>::Init()
@ 0x7fbaab15a758 caffe::Net<>::Net()
@ 0x406bf7 test()
@ 0x4059dc main
@ 0x7fbaa9ce5f45 (unknown)
@ 0x406111 (unknown)
@ (nil) (unknown)
run_cocostuff.sh: line 82: 6570 Aborted (core dumped) ${CMD}
hdl1@hdl1:~/cocostuff/models/deeplab-public-ver2$

Hello,

i downloaded the dataset but to only realize that the annotations folder has .mat files instead of png files.

how can i covert these .mat files to png ?

i plan to train them on pytorch deeplab v3

Hii

The annotation for segmentation in cocostuff-10k-v1.1.json is a list. ie
"segmentation":[ { "counts":xxxxxx, "size":[x,y] } ]
How ever the output produced by convertAnnotationsJSON.py does not contain this . The corresponding code just has
anndata['segmentation'] = Rs
which will produce this
"segmentation": { "counts":xxxxxx, "size":[x,y] }

Is this a bug or my understanding is wrong ?