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  • Why do people hesitate using Python 3?

    - by Ham
    Python 3 has been released in December 2008. A lot of time has passed since then but still today many developers hesitate using Python 3. Even popular frameworks like Django are not compatible with Python 3 yet but still rely on Python 2. Sure, Python 3 has some incompatibilities to Python 2 and some people need to rely on backwards-compatibility. But hasn't Python 3 been around long enough now for most projects to switch or start with Python 3? Having two competiting versions has so many drawbacks; two branches need to be maintained, confusion for learners and so on, so why is there such a big hesitation throughout the Python community in switching to Python 3?

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  • Where can I learn image processing? [on hold]

    - by Little Child
    I am learning image processing on my own and I have managed to teach myself a fair few things like: Making images grayscale using 3 different methods Applying a 'pixellate' filter Applying a 'pointillize' filter Make images out of lines Now, I want to take my knowledge further but I do not know how. Adding more information: I am interested in making software like Photoshop or Gimp (although it won't be half as powerful as these 2). So, I want to learn to apply various creative effects to an image. Can someone please suggest resources for this??

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  • Cannot compile GDB7.8 with Python support

    - by j0h
    I am trying to install GDB7.8 with Python support. From the source folder, I am running ./configure --with-python When I did tab-complete from --with- I did not see Python in the list. But when I ran configure with that flag, it did not baulk. When I run make, it complains that Python is not found. checking for python2.7... no but Python is installed: $ which python python python2.7 python2.7-dbg-config python2 python2.7-dbg $ which python2.7 /usr/bin/python2.7 I compiled GDB without --with-python and things installed without error. I was under the impression that GDB7.8 had Python support without the need for special flags. But when I run: $gdb python (gdb) run test.py I get some sort of cannot import gdb Import error So then I tried calling "pi": (gdb) pi printf.py Python scripting is not supported in this copy of GDB. So... how do I get Python support in GDB7.8? is it actually not supported? Or should I not call "pi"?

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  • PHP invalid image's and error handling

    - by Emdiesse
    Using PHP's Image and GD functions you can use the following method to finally output the php image imagepng($image); Sometimes, for whatever reason the image may not be displayed typically the error is not with the image but with the actual php functions not executing successfully. However this causes a blank image to be returned which doesn't help me. What I want to know is, is there a way to detect a blank or an invalid image and create a new image, write the errors to the new image using imagestring() and then display this new (debug) image instead. for example, a successfully displayed image with no errors: $image = imagecreate(256, 256); //create image imagecolortransparent($image, $BLUE); //set transparent imagefilledrectangle($image, 0, 0, 256, 256, $BLUE); //fill with 'transparent colour' //Draw a border round the image imageline($image, 0, 0, 0, 255, $Black); imageline($image, 0, 0, 255, 0, $Black); imageline($image, 255, 0, 255, 255, $Black); imageline($image, 0, 255, 255, 255, $Black); imagestring($image, 1, 10, 10, "I am an image!", $Black); imagepng($image); imagedestroy($image); but if I then introduce some errors in the php script that may or may not be to do with the actual image creation then the php script fails and the image will not be visible... $image = imagecreate(256, 256); //create image imagecolortransparent($image, $BLUE); //set transparent imagefilledrectangle($image, 0, 0, 256, 256, $BLUE); //fill with 'transparent colour' //Draw a border round the image imageline($image, 0, 0, 0, 255, $Black); imageline($image, 0, 0, 255, 0, $Black); imageline($image, 255, 0, 255, 255, $Black); imageline($image, 0, 255, 255, 255, $Black); imagestring($image, 1, 10, 10, "I am an image!", $Black); /* I am here to cause problems with the php script ** and cause the execution to fail, I am a function ** that does't exist... ** ** and I am missing a semi colon! ;)*/ non_existant_function() imagepng($image); imagedestroy($image); At this point I want to create a new image like above but in replacement of the I am an image! text I would put the actual error that has occured.

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  • Image Processing, joining the small images to form the main image

    - by n0idea
    Good morning everyone, Actually I'm having a small issue in image processing and I'm in need of some help. First of all, let me explain what i want to do, i have an image that was split into 4 other small images. I currently have like 6 small images that i need to figure out which ones are part of the real image. Second, what i currently know is that that i should compare these images edges or last column with the first column of the other image. I'm not sure yet what exactly should be done, anyone is able to put me on the same tracks, with some detailed hints and how to compare the edges of 2 images. Some links and example codes will be help full. One more thing, how am i able to read .Raw images using java, c# or python ?

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  • Fastest image iteration in Python

    - by Greg
    I am creating a simple green screen app with Python 2.7.4 but am getting quite slow results. I am currently using PIL 1.1.7 to load and iterate the images and saw huge speed-ups changing from the old getpixel() to the newer load() and pixel access object indexing. However the following loop still takes around 2.5 seconds to run for an image of around 720p resolution: def colorclose(Cb_p, Cr_p, Cb_key, Cr_key, tola, tolb): temp = math.sqrt((Cb_key-Cb_p)**2+(Cr_key-Cr_p)**2) if temp < tola: return 0.0 else: if temp < tolb: return (temp-tola)/(tolb-tola) else: return 1.0 .... for x in range(width): for y in range(height): Y, cb, cr = fg_cbcr_list[x, y] mask = colorclose(cb, cr, cb_key, cr_key, tola, tolb) mask = 1 - mask bgr, bgg, bgb = bg_list[x,y] fgr, fgg, fgb = fg_list[x,y] pixels[x,y] = ( (int)(fgr - mask*key_color[0] + mask*bgr), (int)(fgg - mask*key_color[1] + mask*bgg), (int)(fgb - mask*key_color[2] + mask*bgb)) Am I doing anything hugely inefficient here which makes it run so slow? I have seen similar, simpler examples where the loop is replaced by a boolean matrix for instance, but for this case I can't see a way to replace the loop. The pixels[x,y] assignment seems to take the most amount of time but not knowing Python very well I am unsure of a more efficient way to do this. Any help would be appreciated.

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  • Python requests - saving cookie for later url usage

    - by PythonRocks
    I been trying to get a cookie and post it to a url in later use in the program, but I cant seem to get the cookie parameters to work. Right now I have response = requests.get("url") But how exactly do I retrive cookies from this url and post them to a new url (the same cookies). The tutorial in requests is somewhat vague on the topic and gives examples I cannot test. Hope someone can help with further examples. This is python 2.7 btw.

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  • Python Parse regex

    - by Nemo
    Let's say I have string in the form given below: myString={"name", "age", "address", "contacts", "Email"} I need to get all the items of myString into a List using python. Here's what I did r= re.search("myString=\{\"(.+)\", $\}", line) if r: items.append(r.group(1)) print(items) Here line is the variable that holds the content of my text file. What change do I have to make to my regex to get all the items in myString? Please kindly help me out. Thanks.

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  • python metaprogramming

    - by valya
    I'm trying to archive a task which turns out to be a bit complicated since I'm not very good at Python metaprogramming. I want to have a module locations with function get_location(name), which returns a class defined in a folder locations/ in the file with the name passed to function. Name of a class is something like NameLocation. So, my folder structure: program.py locations/ __init__.py first.py second.py program.py will be smth with with: from locations import get_location location = get_location('first') and the location is a class defined in first.py smth like this: from locations import Location # base class for all locations, defined in __init__ (?) class FirstLocation(Location): pass etc. Okay, I've tried a lot of import and getattribute statements but now I'm bored and surrender. How to archive such behaviour?

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  • bad request error 400 while using python requests.post function

    - by Toussah
    I'm trying to make a simple post request via the requests library of Python and I get a bad request error (400) while my url is supposedly correct since I can use it to perform a get. I'm very new in REST requests, I read many tutorials and documentation but I guess there are still things I don't get so my error could be basic. Maybe a lack of understanding on the type of url I'm supposed to send via POST. Here my code : import requests v_username = "username" v_password = "password" v_headers = {'content-type':'application/rdf+xml'} url = 'https://my.url' params = {'param': 'val_param'} payload = {'data': 'my_data'} r = requests.post(url, params = params, auth=(v_username, v_password), data=payload, headers=v_headers, verify=False) print r I used the example of the requests documentation.

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  • Bit by bit comparison of using Java or Python for unit testing frameworks and Selenium

    - by Anirudh
    Currently we are in the process of finalizing which language out of Java, Python should be used for Automation using selenium webdriver and a suitable unit testing frameworks. I have made use of Junit, TestNG and webdriver while using with Java and have designed frameworks without much fuss before. I am new to python though I came across pyhton's unit testing frameworks like unittest, pyunit, nose e.t.c but I have doubts if they would be as successful as testNG or Java. I would like to analyze point by point when used with selenium webdriver as below: 1)I have read that as Python is an interpreted language hence it's execution is slower, so say if I have to run 1000 test cases which take about 6 hours to run in Java, would python take considerably longer time for the same test cases like 8 hours? 2)Can the Python unit testing framework be as flexible as a Java unit testing framework like testNG in terms or Grouping the tests, parallel execution, skipping test. e.t.c 3)Also one point that I think of is that Python with selenium webdriver doeasn't have as big or learned community as we have for Java with webdriver, say if I run into trouble with something I am more likely to find an answer for Java as compared to python? 4)Somewhat related to point 3, is it safe to rely on tools, plugins or even webderiver's python's binding as a continuously well maintained? 5)One major drawback as I see while using python's unit testing framework is lack of boilerplate code or libraries for nicely illustrative HTML reports preferably historical reports with Pie charts, bar graphs and timelines as we have in case of Java like Allure, TestNG's default reports, reportNG or Junit reports with the help of ANT as shown below Allure Reports Junit Historical reports Also I would like to emphasize on the fact if there is a way for one to write the framework in java and make libraries or utilities according to out application in webdriver which can easily be called or integrated in with python code or modules? That would actually solve the problem for us as the client would be able to use the code we write in Java and make use of the same or call it from their python modules?

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  • How to set the image into fit screen in the image view

    - by Pugal Devan
    Hi, I am new to iphone development. I want to display the actual size of the image in image view. I have created image view by using Interface builder and set the properties. Now the problem is, I have set into "Scale to Fill", then the image will be stretched in the full screen. Now i want to display the actual size of the image will be displayed in image view. For example 52X52 size image should be displayed with the same size in the image view.The 1200X1020 size image should be fit to the size of the image view .So according the size of the image it should fit to image view and i want the image smaller than image view should retain its original size(It should not stretch to fit the image view). Is it any possible solution to achieve it, please guide me. Thanks.

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  • Python - Calling a non python program from python?

    - by Seafoid
    Hi, I am currently struggling to call a non python program from a python script. I have a ~1000 files that when passed through this C++ program will generate ~1000 outputs. Each output file must have a distinct name. The command I wish to run is of the form: program_name -input -output -o1 -o2 -o3 To date I have tried: import os cwd = os.getcwd() files = os.listdir(cwd) required_files = [] for i in file: if i.endswith('.ttp'): required_files.append(i) So, I have an array of the neccesary files. My problem - how do I iterate over the array and for each entry, pass it to the above command (program_name) as an argument and specify a unique output id for each file? Much appreciated, S :-)

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  • Python Image Library, Close method

    - by DNN
    Hello, I have been using pil for the first time today. And I wanted to resize an image assuming it was larger than 800x600 and also create a thumbnail. I could do either of these tasks separately but not together in one method (I am doing a custom save method in django admin). This returns a "cannot identify image file" error message. The error is on the line "image = Image.open(self.photo)" after "#if image is size is greatet than 800 x 600 then resize image." I thought this may be because the image is already open, but if i remove the line I still get issues. So I thought I could try closing after creating a thumbnail and then reopening. But I couldn't find a close method.... This is my code: def save(self): #create thumbnail Thumb_Size = (75, 75) image = Image.open(self.photo) if image.mode not in ('L', 'RGB'): image = image.convert('RGB') image.thumbnail(Thumb_Size, Image.ANTIALIAS) temp_handle = StringIO() image.save(temp_handle, 'jpeg') temp_handle.seek(0) suf = SimpleUploadedFile(os.path.split(self.photo.name)[-1], temp_handle.read(), content_type='image/jpg') self.thumbnail.save(suf.name+'.jpg', suf, save=False) #if image is size is greatet than 800 x 600 then resize image. image = Image.open(self.photo) if image.size[0] > 800: if image.size[1] > 600: Max_Size = (800, 600) if image.mode not in ('L', 'RGB'): image = image.convert('RGB') image.thumbnail(Max_Size, Image.ANTIALIAS) temp_handle = StringIO() image.save(temp_handle, 'jpeg') temp_handle.seek(0) suf = SimpleUploadedFile(os.path.split(self.photo.name)[-1], temp_handle.read(), content_type='image/jpg') self.photo.save(suf.name+'.jpg', suf, save=False) #enter info to database super(Photo, self).save()

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  • Python regex to parse text file, get the items in list and count the list

    - by Nemo
    I have a text file which contains some data. I m particularly interested in finding the count of the number of items in v_dims v_dims pattern in my text file looks like this : v_dims={ "Sales", "Product Family", "Sales Organization", "Region", "Sales Area", "Sales office", "Sales Division", "Sales Person", "Sales Channel", "Sales Order Type", "Sales Number", "Sales Person", "Sales Quantity", "Sales Amount" } So I m thinking of getting all the elements in v_dims and dumping them out in a Python list. Then compute the len(mylist) to get the count of the items. The challenge is in getting all the elements of v_dims from my text file and putting them in an empty list. I m particularly interested in items in v_dims in my text file. The text file has data in the form of v_dims pattern i showed in my original post. Some data has nested patterns of v_dims. Thanks. Here's what I have tried and failed. Any help is appreciated. TIA. import re fname = "C:\Users\XXXX\Test.mrk" with open(fname, "r") as fo: content_as_string = fo.read() match = re.findall(r'v_dims={\"(.+?)\"}',content_as_string) Though I have a big text file, Here's a snippet of what's the structure of my text file version "1"; // Computer generated object language file object 'MRKR' "Main" { Data_Type=2, HeaderBlock={ Version_String="6.3 (25)" }, Printer_Info={ Orientation=0, Page_Width=8.50000000, Page_Height=11.00000000, Page_Header="", Page_Footer="", Margin_type=0, Top_Margin=0.50000000, Left_Margin=0.50000000, Bottom_Margin=0.50000000, Right_Margin=0.50000000 }, Marker_Options={ Close_All="TRUE", Hide_Console="FALSE", Console_Left="FALSE", Console_Width=217, Main_Style="Maximized", MDI_Rect={ 0, 0, 892, 1063 } }, Dives={ { Dive="A", Windows={ { View_Index=0, Window_Info={ Window_Rect={ 0, -288, 400, 1008 }, Window_Style="Maximized Front", Window_Name="Theater [Previous Qtr Diveplan-Dive A]" }, Dependent_bool="FALSE", Colset={ Dive_Type="Normal", Dimension_Name="Theater", Action_List={ Actions={ { Action_Type="Select", select_type=5 }, { Action_Type="Select", select_type=0, Key_Names={ "Theater" }, Key_Indexes={ { "AMERICAS" } } }, { Action_Type="Focus", Focus_Rows="True" }, { Action_Type="Dimensions", v_dims={ "Theater", "Product Family", "Division", "Region", "Install at Country Name", "Connect Home Type", "Connect In Type", "SymmConnect Enabled", "Connect Home Refusal Reason", "Sales Order Channel Type", "Maintained By Group", "PS Flag", "Avalanche Flag", "Product Item Family" }, Xtab_Bool="False", Xtab_Flip="False" }, { Action_Type="Select", select_type=5 }, { Action_Type="Select", select_type=0, Key_Names={ "Theater", "Product Family", "Division", "Region", "Install at Country Name", "Connect Home Type", "Connect In Type", "SymmConnect Enabled", "Connect Home Refusal Reason", "Sales Order Channel Type", "Maintained By Group", "PS Flag", "Avalanche Flag" }, Key_Indexes={ { "AMERICAS", "ATMOS", "Latin America CS Division", "37000 CS Region", "Mexico", "", "", "", "", "DIRECT", "EMC", "N", "0" } } } } }, Num_Palette_cols=0, Num_Palette_rows=0 }, Format={ Window_Type="Tabular", Tabular={ Num_row_labels=8 } } } } } }, Widget_Set={ Widget_Layout="Vertical", Go_Button=1, Picklist_Width=0, Sort_Subset_Dimensions="TRUE", Order={ } }, Views={ { Data_Type=1, dbname="Previous Qtr Diveplan", diveline_dbname="Current Qtr Diveplan", logical_name="Current Qtr Diveplan", cols={ { name="Total TSS installs", column_type="Calc[Total TSS installs]", output_type="Number", format_string="." }, { name="TSS Valid Connectivity Records", column_type="Calc[TSS Valid Connectivity Records]", output_type="Number", format_string="." }, { name="% TSS Connectivity Record", column_type="Calc[% TSS Connectivity Record]", output_type="Number" }, { name="TSS Not Applicable", column_type="Calc[TSS Not Applicable]", output_type="Number", format_string="." }, { name="TSS Customer Refusals", column_type="Calc[TSS Customer Refusals]", output_type="Number", format_string="." }, { name="% TSS Refusals", column_type="Calc[% TSS Refusals]", output_type="Number" }, { name="TSS Eligible for Physical Connectivity", column_type="Calc[TSS Eligible for Physical Connectivity]", output_type="Number", format_string="." }, { name="TSS Boxes with Physical Connectivty", column_type="Calc[TSS Boxes with Physical Connectivty]", output_type="Number", format_string="." }, { name="% TSS Physical Connectivity", column_type="Calc[% TSS Physical Connectivity]", output_type="Number" } }, dim_cols={ { name="Model", column_type="Dimension[Model]", output_type="None" }, { name="Model", column_type="Dimension[Model]", output_type="None" }, { name="Connect In Type", column_type="Dimension[Connect In Type]", output_type="None" }, { name="Connect Home Type", column_type="Dimension[Connect Home Type]", output_type="None" }, { name="SymmConnect Enabled", column_type="Dimension[SymmConnect Enabled]", output_type="None" }, { name="Theater", column_type="Dimension[Theater]", output_type="None" }, { name="Division", column_type="Dimension[Division]", output_type="None" }, { name="Region", column_type="Dimension[Region]", output_type="None" }, { name="Sales Order Number", column_type="Dimension[Sales Order Number]", output_type="None" }, { name="Product Item Family", column_type="Dimension[Product Item Family]", output_type="None" }, { name="Item Serial Number", column_type="Dimension[Item Serial Number]", output_type="None" }, { name="Sales Order Deal Number", column_type="Dimension[Sales Order Deal Number]", output_type="None" }, { name="Item Install Date", column_type="Dimension[Item Install Date]", output_type="None" }, { name="SYR Last Dial Home Date", column_type="Dimension[SYR Last Dial Home Date]", output_type="None" }, { name="Maintained By Group", column_type="Dimension[Maintained By Group]", output_type="None" }, { name="PS Flag", column_type="Dimension[PS Flag]", output_type="None" }, { name="Connect Home Refusal Reason", column_type="Dimension[Connect Home Refusal Reason]", output_type="None", col_width=177 }, { name="Cust Name", column_type="Dimension[Cust Name]", output_type="None" }, { name="Sales Order Channel Type", column_type="Dimension[Sales Order Channel Type]", output_type="None" }, { name="Sales Order Type", column_type="Dimension[Sales Order Type]", output_type="None" }, { name="Part Model Key", column_type="Dimension[Part Model Key]", output_type="None" }, { name="Ship Date", column_type="Dimension[Ship Date]", output_type="None" }, { name="Model Number", column_type="Dimension[Model Number]", output_type="None" }, { name="Item Description", column_type="Dimension[Item Description]", output_type="None" }, { name="Customer Classification", column_type="Dimension[Customer Classification]", output_type="None" }, { name="CS Customer Name", column_type="Dimension[CS Customer Name]", output_type="None" }, { name="Install At Customer Number", column_type="Dimension[Install At Customer Number]", output_type="None" }, { name="Install at Country Name", column_type="Dimension[Install at Country Name]", output_type="None" }, { name="TLA Serial Number", column_type="Dimension[TLA Serial Number]", output_type="None" }, { name="Product Version", column_type="Dimension[Product Version]", output_type="None" }, { name="Avalanche Flag", column_type="Dimension[Avalanche Flag]", output_type="None" }, { name="Product Family", column_type="Dimension[Product Family]", output_type="None" }, { name="Project Number", column_type="Dimension[Project Number]", output_type="None" }, { name="PROJECT_STATUS", column_type="Dimension[PROJECT_STATUS]", output_type="None" } }, Available_Columns={ "Total TSS installs", "TSS Valid Connectivity Records", "% TSS Connectivity Record", "TSS Not Applicable", "TSS Customer Refusals", "% TSS Refusals", "TSS Eligible for Physical Connectivity", "TSS Boxes with Physical Connectivty", "% TSS Physical Connectivity", "Total Installs", "All Boxes with Valid Connectivty Record", "% All Connectivity Record", "Overall Refusals", "Overall Refusals %", "All Eligible for Physical Connectivty", "Boxes with Physical Connectivity", "% All with Physical Conectivity" }, Remaining_columns={ { name="Total Installs", column_type="Calc[Total Installs]", output_type="Number", format_string="." }, { name="All Boxes with Valid Connectivty Record", column_type="Calc[All Boxes with Valid Connectivty Record]", output_type="Number", format_string="." }, { name="% All Connectivity Record", column_type="Calc[% All Connectivity Record]", output_type="Number" }, { name="Overall Refusals", column_type="Calc[Overall Refusals]", output_type="Number", format_string="." }, { name="Overall Refusals %", column_type="Calc[Overall Refusals %]", output_type="Number" }, { name="All Eligible for Physical Connectivty", column_type="Calc[All Eligible for Physical Connectivty]", output_type="Number" }, { name="Boxes with Physical Connectivity", column_type="Calc[Boxes with Physical Connectivity]", output_type="Number" }, { name="% All with Physical Conectivity", column_type="Calc[% All with Physical Conectivity]", output_type="Number" } }, calcs={ { name="Total TSS installs", definition="Total[Total TSS installs]", ts_flag="Not TS Calc" }, { name="TSS Valid Connectivity Records", definition="Total[PS Boxes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="% TSS Connectivity Record", definition="Total[PS Boxes w/ valid connectivity record (1=yes)] /Total[Total TSS installs]", ts_flag="Not TS Calc" }, { name="TSS Not Applicable", definition="Total[Bozes w/ valid connectivity record (1=yes)]-Total[Boxes Eligible (1=yes)]-Total[TSS Refusals]", ts_flag="Not TS Calc" }, { name="TSS Customer Refusals", definition="Total[TSS Refusals]", ts_flag="Not TS Calc" }, { name="% TSS Refusals", definition="Total[TSS Refusals]/Total[PS Boxes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="TSS Eligible for Physical Connectivity", definition="Total[TSS Eligible]-Total[Exception]", ts_flag="Not TS Calc" }, { name="TSS Boxes with Physical Connectivty", definition="Total[PS Physical Connectivity] - Total[PS Physical Connectivity, SymmConnect Enabled=\"Capable not enabled\"]", ts_flag="Not TS Calc" }, { name="% TSS Physical Connectivity", definition="Total[Boxes w/ phys conn]/Total[Boxes Eligible (1=yes)]", ts_flag="Not TS Calc" }, { name="Total Installs", definition="Total[Total Installs]", ts_flag="Not TS Calc" }, { name="All Boxes with Valid Connectivty Record", definition="Total[Bozes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="% All Connectivity Record", definition="Total[Bozes w/ valid connectivity record (1=yes)]/Total[Total Installs]", ts_flag="Not TS Calc" }, { name="Overall Refusals", definition="Total[Overall Refusals]", ts_flag="Not TS Calc" }, { name="Overall Refusals %", definition="Total[Overall Refusals]/Total[Bozes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="All Eligible for Physical Connectivty", definition="Total[Boxes Eligible (1=yes)]-Total[Exception]", ts_flag="Not TS Calc" }, { name="Boxes with Physical Connectivity", definition="Total[Boxes w/ phys conn]-Total[Boxes w/ phys conn,SymmConnect Enabled=\"Capable not enabled\"]", ts_flag="Not TS Calc" }, { name="% All with Physical Conectivity", definition="Total[Boxes w/ phys conn]/Total[Boxes Eligible (1=yes)]", ts_flag="Not TS Calc" } }, merge_type="consolidate", merge_dbs={ { dbname="connectivityallproducts.mdl", diveline_dbname="/DI_PSREPORTING/connectivityallproducts.mdl" } }, skip_constant_columns="FALSE", categories={ { name="Geography", dimensions={ "Theater", "Division", "Region", "Install at Country Name" } }, { name="Mappings and Flags", dimensions={ "Connect Home Type", "Connect In Type", "SymmConnect Enabled", "Connect Home Refusal Reason", "Sales Order Channel Type", "Maintained By Group", "Customer Installable", "PS Flag", "Top Level Flag", "Avalanche Flag" } }, { name="Product Information", dimensions={ "Product Family", "Product Item Family", "Product Version", "Item Description" } }, { name="Sales Order Info", dimensions={ "Sales Order Deal Number", "Sales Order Number", "Sales Order Type" } }, { name="Dates", dimensions={ "Item Install Date", "Ship Date", "SYR Last Dial Home Date" } }, { name="Details", dimensions={ "Item Serial Number", "TLA Serial Number", "Part Model Key", "Model Number" } }, { name="Customer Infor", dimensions={ "CS Customer Name", "Install At Customer Number", "Customer Classification", "Cust Name" } }, { name="Other Dimensions", dimensions={ "Model" } } }, Maintain_Category_Order="FALSE", popup_info="false" } } };

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  • image filters for iphone sdk development

    - by plsp
    Hi All, I am planning to develop an iphone app which makes use of image filters like blurring, sharpening,etc. I noticed that there are few approaches for this one, Use openGL ES. I even found an example code on apple iphone dev site. How easy is openGL for somebody who has never used it? Can the image filters be implemented using the openGL framework? There is a Quartz demo as well posted on apple iphone dev site. Has anybody used this framework for doing image processing? How is this approach compared to openGL framework? Don't use openGL and Quartz framework. Basically access the raw pixels from the image and do the manipulation myself. Make use of any custom built image processing libraries like this one. Do you know of any other libraries like this one? Can anybody provide insights/suggestions on which option is the best? Your opinions are highly appreciated. Thanks!

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  • Create Custom Sized Thumbnail Images with Simple Image Resizer [Cross-Platform]

    - by Asian Angel
    Are you looking for an easy way to create custom sized thumbnail images for use in blog posts, photo albums, and more? Whether is it a single image or a CD full, Simple Image Resizer is the right app to get the job done for you. To add the new PPA for Simple Image Resizer open the Ubuntu Software Center, go to the Edit Menu, and select Software Sources. Access the Other Software Tab in the Software Sources Window and add the first of the PPAs shown below (outlined in red). The second PPA will be automatically added to your system. Once you have the new PPAs set up, go back to the Ubuntu Software Center and click on the PPA listing for Rafael Sachetto on the left (highlighted with red in the image). The listing for Simple Image Resizer will be right at the top…click Install to add the program to your system. After the installation is complete you can find Simple Image Resizer listed as Sir in the Graphics sub-menu. When you open Simple Image Resizer you will need to browse for the directory containing the images you want to work with, select a destination folder, choose a target format and prefix, enter the desired pixel size for converted images, and set the quality level. Convert your image(s) when ready… Note: You will need to determine the image size that best suits your needs before-hand. For our example we chose to convert a single image. A quick check shows our new “thumbnailed” image looking very nice. Simple Image Resizer can convert “into and from” the following image formats: .jpeg, .png, .bmp, .gif, .xpm, .pgm, .pbm, and .ppm Command Line Installation Note: For older Ubuntu systems (9.04 and previous) see the link provided below. sudo add-apt-repository ppa:rsachetto/ppa sudo apt-get update && sudo apt-get install sir Links Note: Simple Image Resizer is available for Ubuntu, Slackware Linux, and Windows. Simple Image Resizer PPA at Launchpad Simple Image Resizer Homepage Command Line Installation for Older Ubuntu Systems Bonus The anime wallpaper shown in the screenshots above can be found here: The end where it begins [DesktopNexus] Latest Features How-To Geek ETC Macs Don’t Make You Creative! So Why Do Artists Really Love Apple? MacX DVD Ripper Pro is Free for How-To Geek Readers (Time Limited!) HTG Explains: What’s a Solid State Drive and What Do I Need to Know? How to Get Amazing Color from Photos in Photoshop, GIMP, and Paint.NET Learn To Adjust Contrast Like a Pro in Photoshop, GIMP, and Paint.NET Have You Ever Wondered How Your Operating System Got Its Name? Create Shortcuts for Your Favorite or Most Used Folders in Ubuntu Create Custom Sized Thumbnail Images with Simple Image Resizer [Cross-Platform] Etch a Circuit Board using a Simple Homemade Mixture Sync Blocker Stops iTunes from Automatically Syncing The Journey to the Mystical Forest [Wallpaper] Trace Your Browser’s Roots on the Browser Family Tree [Infographic]

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  • Create Image Maps with GIMP

    - by SGWellens
    Having a clickable image in a web page is not a big deal. Having an image in a web page with clickable hotspots is a big deal. The powerful GIMP editor has a tool to make creating clickable hotspots much easier. GIMP stands for GNU Image Manipulation Program. Its home page and download links are here: http://www.gimp.org/ (it is completely free). Beware: GIMP is an extraordinarily advanced and powerful image editor. If you wish to use it for general image editing tasks, you have a steep learning curve to climb. FYI: I used it to create the shadows you see on the images below. Fortunately, the tool to make Image Maps is separate from the main program. To start, open an image with GIMP or, drag and drop an image onto the GIMP main window. I'm using the image of a bar graph. Next, we have to find the Image Map tool and launch it (Filters->Web->Image Map…): Why is the Image Map tool under Filters and not Tools? I don't know. It's mystery—much like the Loch Ness Monster, the Bermuda Triangle, or why my socks keep disappearing when I do laundry. I swear I've got twenty single unmatched socks. But I digress… Here is what the Image Map tool looks like: If we click the blue 'I' button, we can add information to the Image Map: Now we'll use the rectangle tool to create some clickable hotspots. Select the Blue Rectangle tool, drag a rectangle, click when done and you'll get something like this: You can also make circle/oval and polygon areas. You can edit all the parameters of an image map area after drawing it. Rectangle settings (for fine tweaking): JavaScript functions (it's up to you to write them): Here is a setup with two rectangles and one polygon area: When you hit save a map file is generated that looks something like this: Paste the contents into a web page and you are almost there. I made some tweaks before it became usable: Replaced &apos; with apostrophes in the javascript functions. Changed the image path so it would find the image in my images directory Tweaked the href urls. Added Title="Some Text" to get tool tips. Cleaned out the comments. Result: The final markup (with JavaScript function): function ImageMapMouseHover(Msg) { $("#Label1").html(Msg); } It may seem like a lot of bother but, the tool does the heavy lifting: i.e. the coordinates. Getting the regions positioned and sized is easy using a visual tool…much better than doing it by hand. This, of course, isn't a full treatise on the tool but it should give you enough information to decide if it's helpful. I hope someone finds this useful Steve Wellens

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  • Convertion of tiff image in Python script - OCR using tesseract

    - by PYTHON TEAM
    I want to convert a tiff image file to text document. My code perfectly as I expected to convert tiff images with usual font but its not working for french script font . My tiff image file contains text. The font of text is in french script format.I here is my code import Image import subprocess import util import errors tesseract_exe_name = 'tesseract' # Name of executable to be called at command line scratch_image_name = "temp.bmp" # This file must be .bmp or other Tesseract-compatible format scratch_text_name_root = "temp" # Leave out the .txt extension cleanup_scratch_flag = True # Temporary files cleaned up after OCR operation def call_tesseract(input_filename, output_filename): """Calls external tesseract.exe on input file (restrictions on types), outputting output_filename+'txt'""" args = [tesseract_exe_name, input_filename, output_filename] proc = subprocess.Popen(args) retcode = proc.wait() if retcode!=0: errors.check_for_errors() def image_to_string(im, cleanup = cleanup_scratch_flag): """Converts im to file, applies tesseract, and fetches resulting text. If cleanup=True, delete scratch files after operation.""" try: util.image_to_scratch(im, scratch_image_name) call_tesseract(scratch_image_name, scratch_text_name_root) text = util.retrieve_text(scratch_text_name_root) finally: if cleanup: util.perform_cleanup(scratch_image_name, scratch_text_name_root) return text def image_file_to_string(filename, cleanup = cleanup_scratch_flag, graceful_errors=True): If cleanup=True, delete scratch files after operation.""" try: try: call_tesseract(filename, scratch_text_name_root) text = util.retrieve_text(scratch_text_name_root) except errors.Tesser_General_Exception: if graceful_errors: im = Image.open(filename) text = image_to_string(im, cleanup) else: raise finally: if cleanup: util.perform_cleanup(scratch_image_name, scratch_text_name_root) return text if __name__=='__main__': im = Image.open("/home/oomsys/phototest.tif") text = image_to_string(im) print text try: text = image_file_to_string('fnord.tif', graceful_errors=False) except errors.Tesser_General_Exception, value: print "fnord.tif is incompatible filetype. Try graceful_errors=True" print value text = image_file_to_string('fnord.tif', graceful_errors=True) print "fnord.tif contents:", text text = image_file_to_string('fonts_test.png', graceful_errors=True) print text

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