Develop Reference

Rotating an n-dimensional picture using Scipy.ndimage.rotate

I am trying to rotate a picture with 11 channels using scipy.ndimage.rotate.
It is stored as an array in the variable im_arr and I use the following line to rotate it:
im_arr = ndimage.rotate(im_arr,-angle)
Yet when I execute the script I get the following error message:
ValueError: negative dimensions are not allowed
I can't quite understand what this means or what this is supposed to tell me. Nor do I know how to solve it. I had the same error message beforehand when I used ndimage.zoom to resize it. The issue there was from my understanding that by using a positive factor for the zoom the picture would have had negative indices for some reason. This was simply solved by putting a - in front of the second zoom factor.
dim = (im_new_x, -im_new_y,1)
im_arr = ndimage.zoom(im_arr,dim)
In this case this is not possible though. No matter what I do here I can't think of a way to bypass this issue.

can locateCenterOnScreen coordinates be passed to the X Y parameter to screenshot a region with Python?

New to python (within the past couple months) and I'm enjoying it. It is easy to understand and to use. Except in this case!
I wrote a script that works for logging into a site with selenium, navigating to a particular page, entering date values and showing the results I need. It scrolls into position, then I need to screenshot just a portion of that page. At first I would just have it save the whole screen and I would crop it later, but I believe it is possible (and more efficient) to only screenshot the area I need.
I have tried multiple methods of locating where the corner would start and selecting the region, and ultimately decided to go with pyautogui using locateCenterOnScreen of a sample screenshot of just the spot I want, where the center marks the upper-left corner of the entire part I want to save. This ensures that if the window is not in the same place every time, it will accurately save the correct region no matter where it is.
Thus, using
location = pyautogui.locateCenterOnScreen('ctr_cornerScreenshot.PNG')
returns a correct (X, Y) value to properly locate the coordinates for the screenshot. Then, I'm using
screengrabPic = pyautogui.screenshot(region=(location, 720, 340))
screengrabPic.save("transactions.png")
the error turns out as
AssertionError: region argument must be a tuple of four ints
I'm sure because of the region parameter passed in as location, and I've tried (int(location) or 'locationX, locationY,
I figured I'd reach out for help rather than spin my wheels too much more. Thanks!

OK, so I did a lot more trial and error then found the final solution.
location = pyautogui.locateCenterOnScreen('ctr_cornerScreenshot.PNG')
print(location)
locationX, locationY = pyautogui.locateCenterOnScreen('ctr_cornerScreenshot.PNG')
screengrabPic = pyautogui.screenshot(region=(locationX, locationY, 720, 340))
screengrabPic.save("tolls_" + filename + ".png")
On pyautogui.readthedocs it explains this syntax, yet it wasn't specific that the requirement was to run locate center once first, then again for locationX and locationY.

Tiling, how to use recursion in this case?

I am trying to make an algorithm that's able to solve a big tileset in the tiling problem. Right now it's able to find the correct Tiles to place based on their width and height, but there are some problems with making it properly recursive.
As you can see the idea is that after each tile that's placed the field will be separated in a Field Right and a Field Below. The algorithm will first try to fill the Field Right and as soon as that's done it has to start trying to fill Field Below.
The problem I have is that once Field Right is solved it has to be "send back" in a way (I think using recursion, though this is quite complex) to get it to go back a Tile and go to the Field Below that belongs to that Tile. I put the idea in some pseudocode to make it a bit easier to follow.
As you can see when FieldRightWidth is solved and the FieldBelowHeight is also solved I want to make it return to the previous tile to check if FieldBelow is solved. I think that's where I need to put some code to make this work, but after hours of Googling I still have no clue.
Pseudocode:
def Methods:
create global tileset
create local tileset (without duplicates)
If globaltiles is empty:
solved
end
else:
if fieldRightWidth == solved:
if fieldBelowHeight == solved:
return True???
#FIELD BELOW
else:
Search for Tile
Place Tile
Return Methods
#FIELD RIGHT
else:
Search for Tile
Place Tile
Return Methods
And a picture of what I want the algorithm to do:
And all of the code:
http://pastebin.com/8t4PeiZP
http://www.filedropper.com/tilingnew
I'm still a newbie in coding, so any advice or help is very appreciated!

alright, let's think the area you want to calculate are either square or rectangular,(not rotated), it start from minimum [x,y] and end maximum [x,y] right, like so:
SMaxX = 5
SMinX = 0
SMaxY = 5
SMinY = 0
or if you are familiar with 2D vector you can optimize it like so:
S = [5,5]
you might know about 2D vector, just in case i explain what is vector in 2D cartesian coordinate:
S = [5,5] means, if S start from [0,0], it will end at [5,5], (simpler right?)
so boxes also will be like so:
#space each box taking
box1 = [3,3]
box2 = [2,2]
box3 = [1,1]
and since there is priority for each box, let's say:
#priority of each box
box1 = 6
box2 = 4
box3 = 2
we can merge both space and priority into dictionary like so:
#Items
dic = {'box1':{'space':[3,3] , 'priority ':6},
'box2':{'space':[2,2] , 'priority ':4},
'box3':{'space':[1,1] , 'priority ':2}}
having priority and spaces of each boxes, looks like Knapsack problem algorithm.
if you are familiar about Knapsack problem algorithm, in a table we are trying to find the highest priority that fill the space perfectly, or in other word best possible way of fitting boxes. check this link1 and link2.
however Knapsack problem algorithm's chart is 1D solution, which if you do it, you will get 10, so Box1 and Box2. but since it's 2D and you have different height and width, so the standard 1D formula wont work, maybe you need to look into it see if you can come up with 2D formula or ask around see if someone done that before.
other than Knapsack problem algorithm you can try Flood fill algorithm which is a bit slower if you have huge area, but it work just like how Tetris game is.
you need to set standard size like 1x1, and then define the whole area with 1x1 data, and store it in a variable and set each True (Boolean), then with higher priority of boxes fill the area and set those 1x1 date to False, then really easy you can check if how many of the them are True and what area are they taking.
anyway, i'm trying to figure out the same thing in irregular shape, so that was all i found out, hope that help you.
(check this link as well, i got some useful answers.)
Edit: okay, if you use Tetris idea with defining the area and Knapsack problem algorithm in one axis and then base on standard Tetris area, use Knapsack problem algorithm again in other axis should work perfectly.

Hacking a closed source program to help me sort real life objects with python/screenshot/OCR

In my job,we are using a dedicated MS ACCESS program (let's call it XYZ)to help us in our work.
I cannot access source code/API of this program, but I want to write a python script to help me automate a sorting task (which is not implemented), that I'm telling you.
We take 12 random objects/tools/pieces which are identified by a barcode with a unique id (for example 50286,50285,50277,50280 ....), we shoot them with a barcode gun scanner and in the program XYZ we get this result.
before sorting
This is a screenshot of the pc at work, I added by hand the blue colored numbers to the right just for clarity, to explain to you what I'm trying to accomplish.
Remember we took these objects randomly, now we have to sort them.
They are sorted by program XYZ keeping in mind some important sorting stuff that it isn't important to know.
This script makes two screenshot, the first before sorting the list and the second after sorting the list.
After this sorting, my list looks like this.
after sorting
I want my script to output the numbers 3,12,11,9,8,7,10,6,4,5,1,2.
I thought this was a simple task because I already managed to get for example Element_#1_in_before_list
50826 before
and Element_#11_in_after_list,
50286 after
However I cannot tell the first item is now the eleventh element because the two pictures aren't similar due to random annoying noise blue/cyan pixels (Truetype?)
I tried OCR to recognize the characters, but sometimes it fails and it's too complicated.
I tried to convert to Black and White but noise pixels become sometimes black or white and the two images don't match perfectly (I came up with the solution to perform md5sum to tell if they are the same)
How can I solve the problem?
Maybe it's simple but i'm noob.
Help me surprise the XYZ developer!!

Have you tried matching in a non-exact way? You could match each image in list 1 to the image in list 2 with the lowest MSE.
def mse(imageA, imageB):
# the 'Mean Squared Error' between the two images is the
# sum of the squared difference between the two images;
# NOTE: the two images must have the same dimension
err = np.sum((imageA.astype("float") - imageB.astype("float")) ** 2)
err /= float(imageA.shape[0] * imageA.shape[1])
# return the MSE, the lower the error, the more "similar"
# the two images are
return err
Source for MSE function: http://www.pyimagesearch.com/2014/09/15/python-compare-two-images/

How do I numerically position a barcode in reportlab?

I have a bit of a specific case that I can't seem to figure out a solution to. I'm writing a shipping label template object in ReportLab for Python. I have the following code that creates a barcode as a drawing.
uspsBarcode = createBarcodeDrawing('USPS_4State', value=self.imbval, routing=self.zip4.replace('-',''))
print uspsBarcode.getBounds() # print out of position and scale
Using that code, I later add it to a shape group, and that shape group gets returned. So I need the barcode to be positioned relative to the object. I can't seem to find any way to pass positioning to this, even though I've dug through the inheritance. Though as you can see from the print, positioning is set somwhere.

Just for anyone else that runs across this issue. It turns out that if you put the barcode drawing in a shape group, the shape group container can be moved around numerically with the shift function.
uspsBarcode = shapes.Group()
bc = createBarcodeDrawing('USPS_4State', value=self.imbVal, routing=self.zip4.replace('-',''))
uspsBarcode.add(bc)
uspsBarcode.shift(self.x+(s*0.2), self.y)