karolzak / cntk-hotel-pictures-classificator Goto Github PK

There are several places you hard coded the configurations of network architecture in the main program.

They are:

1. The input dimension of Fast-RCNN, which is coded as [4096, ]. But it should be possible to be other numbers, e.g. if i want to use ResNet ended with dimension [1000, ].
2. The spatial_scale of RoiPooling layer, which is coded as 1/16. But in my understanding, this ratio is related to the actual total stride in the convolutional layers.

Hello sir,

in your file 'Detection/FasterRasterRCNN/plot_helper.py', you use the font 'Arial' to draw text but it's not a default font for my Linux, Azure DSVM for Linux with Ubuntu 16.04.

I am not sure if the solution for fixing this error should be included in the Readme 'Setup' section to tell Linux users to install 'Arial' font before learning the model. if anyone else encountered this problem too, you can find a help from below link: https://askubuntu.com/questions/651441/how-to-install-arial-font-in-ubuntu

In the plot_helper.py, the color for drawing boxes currently only supports up to 15 classes, which is defined by five base colors and their 3 variants.

But it is not enough for me when i train and evaluate via my own custom dataset, which contains about 50 classes.

I want to detect object and store detected object and bounding box in dataframe or text file or json , so as to run later logic, like if something is found do this. COuld you help in providing code for same

Hello,

There is an error of name mismatching when I wanted to switch the base model to the VGG16. Basically, the problem is that you define the name of model by yourself in the config file, e.g. VGG16, while the real name of VGG model referred by the download is VGG16_ImageNet_Caffe. Then after finish downloading, the program named the model as VGG16 but the other part of main program loads the model via the name VGG16_ImageNet_Caffe.

Obviously, the problem will also happen when loading and using other base models if the program-defined name is different from the name defined by others.

Best wishes!
Lin.

I know this error has been widely discussed and here are some specifications I found for this program.

1. The default cython binaries in the directory 'Detection/utils/cython_modules/' only support for particular version, 3.4(Linux) and 3.5(Windows), of Python. So anyone who got the error info like the title should checks if your Python version is suitable.

2. The latest cython module binaries have been updated on the repo of CNTK. But after copying the corresponding binaries for Python 3.5(Linux), i.e. cpu_nms.cpython-35m.so and cython_bbox.cpython-35m.so, into the directory of current project 'Detection/utils/cython_modules/', it still reports the same error as the title during compilation, while the program will run well if I change my Python to 3.4 by Anaconda virtual environment and run the same project, i.e. same directory and same program.

3. Another solution for this problem is to recompile the above cython modules by ourselves following instructions from CNTK Guide. The lucky thing is that the program can pass the compilation without any error report, while unfortunately it produces/prints some unknown error info during the training.

All of my testing are run on the latest DSVM for Linux.
Default Python: Python 3.5 with CNTK 2.2
Python 3.4 Virtual Environment: Python 3.4 with CNTK 2.1

I was training with 17 images and testing with 3 images but gettign below error. is it is because of object identified as wrong as MAP is zero so getting below error?

warnings.warn(WARNING_MSG_GPU_ONLY % ('GPU-Specific', 'https://docs.microsoft.com/en-us/cognitive-toolkit/Setup-Windows-Python#optional-gpu-specific-packages'))
Selected CPU as the process wide default device.
Using the following parameters:
Flip image : True
Train conv layers: True
Random seed : 3
Momentum per MB : 0.9
E2E epochs : 20
Loading existing model from D:\Dropbox (eClerx Services Ltd.)\Navdeep.Singh05\Documents\navdeep\coe work\Hilton\cntk custom hotels\Detection\FasterRCNN\Output\faster_rcnn_eval_AlexNet_e2e.model
D:\Dropbox (eClerx Services Ltd.)\Navdeep.Singh05\Documents\navdeep\coe work\Hilton\cntk custom hotels\Detection\FasterRCNN..\utils\rpn\proposal_layer.py:33: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
layer_params = yaml.load(self.param_str_)
Evaluating Faster R-CNN model for 3 images.
Number of rois before non-maximum suppression: 0
Number of rois after non-maximum suppression: 0
AP for shacks = 0.0000
AP for pool = 0.0000
Mean AP = 0.0000
D:\Dropbox (eClerx Services Ltd.)\Navdeep.Singh05\Documents\navdeep\coe work\Hilton\cntk custom hotels\Detection\FasterRCNN..\utils\rpn\proposal_layer.py:33: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
layer_params = yaml.load(self.param_str_)
Plotting results from Faster R-CNN model for 3 images.
roiScores min: 0.46174436807632446, max: 1.0, threshold: 0.1
reset decision threshold to: 0.23087218403816223
Traceback (most recent call last):
File "FasterRCNN.py", line 750, in
bgrPlotThreshold=cfg["CNTK"].RESULTS_BGR_PLOT_THRESHOLD)
File "D:\Dropbox (eClerx Services Ltd.)\Navdeep.Singh05\Documents\navdeep\coe work\Hilton\cntk custom hotels\Detection\FasterRCNN\plot_helpers.py", line 186, in eval_and_plot_faster_rcnn
decisionThreshold=bgrPlotThreshold)
File "D:\Dropbox (eClerx Services Ltd.)\Navdeep.Singh05\Documents\navdeep\coe work\Hilton\cntk custom hotels\Detection\FasterRCNN\plot_helpers.py", line 95, in visualizeResultsFaster
text = classes[label]
IndexError: list index out of range

Hello,
when I was trying to train the model with VGG16 base model, I got an error of bac_alloc related to the insufficient memory allocation on my DSVM with 4GB memory.

Basically, this is not a programming error. But I think pointing out the minimum requirements on the resource, like memory, will ease lots of pain for the people whose training aborted after running for a long time due to this problem.

Finally, here are some experiment results collected from the Linux DSVM:

1. VGG16 + e2e: above 4GB but below 8GB
2. VGG16 + 4-stage: around 17GB

Best wishes!

I saw your new commit. You set the font as FreeMono if Arial not found. But the problem of font not found still happens when I try to run the program on the Azure DSVM or DLVM.

So the better way, as i think, is to mention this problem in the Readme so that people will know everything they have to have before the program runs successfully.

help to find parameters which we can tweak for multiple bounding boxes across same object