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The above images is the collection of all predictions of the raw images. It is hard to see on this images. But it is large enough actually, so you can download it and see it one by one. Or better you can just see individuals  in links below . But is is already obvious that most of the prediction are bed and has nothing to do with the true position.

https://drive.google.com/open?id=0B-tdhSV_wzITVXhHaWNZbkNwUE0

I also considered the training error and the performance. The training error is the difference between the predicted y_min and the true y_min.

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Again, it's hard to find the beam on the spot. But if you see the individual images in the following link, you see that this time, we have got much better result. Only 20 images do not have precise predictions.

https://drive.google.com/open?id=0B-tdhSV_wzITMm92c0M4bjRXRlE

Another thing needed to mention is that because I plot the above huge images all in once. Thus this time it shows the absolute intensity of the beam rather than the relative intensity as is in the individual images.

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8. Links to Related Files

The following link contains three different files,  ' beam_detection.tar.gz ' is the compressed file of ' beam_detection ' folder. 'beam_detection' folder contains essential codes and results of my projects. Even though I am new to python and these codes and resutls may not be of value to professional user, I think it may help if you are want to know how I got the results.  ' First_Quarter_Project_All_Files.tar.gz ' contains nearly all files I used and generated in the project. But unfortunately, i accidently deleted the file that contains the newly generated raw images for vcc screen. 

There is a 'folder_may.txt' in folder 'beam_detection' which describes the structure of the folder.

https://drive.google.com/open?id=0B-tdhSV_wzITcWMzVm45a0RFNWs