Not able to reproduce the prediction results

[fanghuaqi]

Hi @hszhao , I am evaluating the ICNet, and run eval_all.m on the evaluation/samplelist/cityscapes_val.txt.

Model using to evaluate:

model_weights = 'model/icnet_cityscapes_train_30k.caffemodel'; %trainval_90k for testset
model_deploy = 'prototxt/icnet_cityscapes.prototxt';

Here is my result on ICNet train on trainset for 30K, evaluated on valset (mIoU/pAcc):

==== Summary IoU ====
  1             road: 0.0000
  2         sidewalk: 0.0045
  3         building: 0.0109
  4             wall: 0.0025
  5            fence: 0.0438
  6             pole: 0.0101
  7    traffic light: 0.0000
  8     traffic sign: 0.0001
  9       vegetation: 0.0008
 10          terrain: 0.0047
 11              sky: 0.0000
 12           person: 0.0031
 13            rider: 0.0008
 14              car: 0.0012
 15            truck: 0.0000
 16              bus: 0.0000
 17            train: 0.0000
 18       motorcycle: 0.0005
 19          bicycle: 0.0000
 
Mean IoU over 19 classes: 0.44%
Pixel-wise Accuracy: 0.51%

Is there anything I am missing to run this model, thanks in advance for anything input.

By the way, does anybody be able to reproduce the result, and if yes, please let me know, what was missing?

Thanks
Huaqi

[fanghuaqi]

Figure out why the result is different, according to the tensorflow ICNet implementation

Here are the steps:

• Download Cityscape dataset from Official website first (you'll need to request access which may take couple of days).
• Then convert downloaded dataset ground truth to training format by following instructions to install cityscapesScripts then running these commands

export CITYSCAPES_DATASET=<cityscapes dataset path>
csCreateTrainIdLabelImgs