| commit | author | age | ||
| 69abed | 1 | 3 |
| 1b70ca | 2 | Í÷[ ã @ st d dl Z d dlZd dlmZmZ d dlZdZeje eZ |
| 69abed | 3 | dd Z dd Z dd Z d |
| SP | 4 | d Zd d Zdd Zdd ZdS )é N)Ú |
| 5 | morphologyÚ img_as_ubytez/template-8.pngc C s t j| |ft jS )z8 | |
| 6 | Function greates square kernel of size x and y | |
| 7 | )ÚnpZonesÚuint8)ÚxÚy© r ú@/home/samo/programiranje/python/sizif-ocr/aoi_ocr/sid_process.pyÚkernel s r | |
| 1b70ca | 8 | c C sâ |d dkrd}n|d dkr$d}nd}t j|t jtdddd}t j| t jtd d |
| SP | 9 | dd}t|dk}t jd | t j|j t j t j |
| 10 | \}}}t |d d d} t j | d \} | |
| 69abed | 11 | } } } | | | | | |
| SP | 12 | d |
| 13 | | | | |
| 1b70ca | 14 | | d f } | S )Nr Ú1é- r é2 é é )Ú |
| SP | 15 | iterationsé é z/tmp/sidblock1.pngc S s |
| 16 | t j| S )N)Úcv2Z contourArea)Úctrr r r Ú<lambda>% s z#find_biggest_blob.<locals>.<lambda>)Úkeyé é éÿÿÿÿ) r Ú morphologyExÚ | |
| 69abed | 17 | MORPH_OPENr |
| 1b70ca | 18 | Ú MORPH_DILATEr ÚimwriteÚ findContoursÚcopyÚ RETR_EXTERNALÚCHAIN_APPROX_SIMPLEÚsortedÚ boundingRect)ÚimageÚoriginal_imageÚsid_maskZ move_leftZimage2Zimage1Úim2ÚctrsÚhierÚ sorted_ctrsr r ÚwÚhr r r Úfind_biggest_blob s" (r- c C s0 x*t || D ] \}}|dkr ||kr dS q W dS )zÎ |
| 69abed | 19 | Function compares student id number with student id mask if the recognised number is valid according to the mask |
| SP | 20 | :param sid_no: |
| 21 | :param sid_mask: | |
| 22 | :return: True if they match, else False | |
| 1b70ca | 23 | r FT)Úzip)Úsid_nor& ÚsÚesr r r Ú sid_compare, s r2 c C sò d}t | ||} tjd| tj| j tjtj\}}}t|dd d}x¤t|D ]\} } |
| 69abed | 24 | tj | |
| SP | 25 | \} } } }| |d k r|d }qR| | | | | | | f }t |
| 26 | |dk }tj |d}tjd | |
| 27 | j | | |t |j|jd dd d }qRW |S )zæ | |
| 28 | First algorithm. it segments numerals with contours. It works with numbers where individual numerals does not touch. | |
| 29 | :param image: | |
| 30 | :param original_image: | |
| 31 | :param classifier: | |
| 32 | :return: student id as a string | |
| 1b70ca | 33 | Ú z/tmp/sid_contour1.pngc S s t j| d S )Nr )r r# )r r r r r H s z%segment_by_contours.<locals>.<lambda>)r r r é é z/tmp/sid_no_{}.pngr g ào@r )r5 r5 r )r- r r r r r r! r" Ú enumerater# r ÚresizeÚformatÚstrÚpredictÚreshape)r$ r% Ú |
| SP | 34 | classifierr& r/ r' r( r) r* Úir r r r+ r, Úroir r r Úsegment_by_contours9 s" &r? c C sÆ d}t |}t| ||} tjd| | jdd \}}t|| }x~td|D ]p} | dd | | | d | f } |
| 69abed | 35 | t| |
| SP | 36 | dk } |
| 37 | tj| | |
| 38 | d } | |
| 39 | tjd j | | | |
| 40 | |t | |
| 41 | |j | | |
| 42 | j dd d | |
| 43 | d }qNW |S ) aR | |
| 44 | Third algorithm. It trys to get biggest "blob" in the image and then it cuts it into individual numbers by force. | |
| 45 | It has some problems with finding individual numbers, so some tweaking must be done! | |
| 46 | ||
| 47 | :param image: | |
| 48 | :param original_image: | |
| 49 | :param sid_mask: | |
| 50 | :param classifier: | |
| 51 | :return: student id as a string | |
| 1b70ca | 52 | r3 z/tmp/sidblock2.pngr r Nr r4 r5 z/tmp/sid_no_{}.pngg ào@)r5 r5 r ) Úlenr- r r ÚshapeÚintÚranger r7 r8 r9 r: r; ) r$ r% r& r< r/ Zsid_lenÚ imgHeightÚimgWidthZnumWidthr= Únumr r r Úsegment_by_sid_len[ s &rG c C sH t j|t jtdddd}t|dk }t jd| t jtd}|jddd \}}t j ||t j |
| 69abed | 53 | }t j |d k} t j | t j} |
| SP | 54 | g } g } xNt| ddd D ]8} | d d | d d f} | j| d | j| d qW t| dkræd |
| 55 | S ttt| | \} } t j| t|d k}t j|d }t j| } t j| } | | | | g}xBt|ddd D ],} t j| | |
| 56 | | | d | | d | fdd qVW t jd | | |
| 57 | d | |
| 58 | }x¬tt|ddd D ]\}} | | d | d | | d | d | f }t|dk }yt j|d}W n | |
| 59 | d | |
| 60 | S t jdj|| |t|j|j ddd d }q®W |S )aI | |
| 61 | Second attempt. It dilates the image to get all 7 segments wisible as 8888888 then it does pattern matching of 8 with | |
| 62 | pattern image. It works if the scaned gray level is high enough. | |
| 63 | ||
| 64 | :param image: | |
| 65 | :param original_image: | |
| 66 | :param sid_mask: | |
| 67 | :param classifier: | |
| 68 | :return: student id number as a string | |
| 69 | r é | |
| 1b70ca | 70 | )r r z/tmp/sid_3rd1.pngr Nr g è?r3 Téÿ z/tmp/sid_3rd2.pngr4 r5 z/tmp/sid_3no_{}.pngg ào@r r r )r rI rI r )r5 r5 r ) r r Ú MORPH_CLOSEr |
| SP | 71 | r r ÚimreadÚ template8rA Ú matchTemplateÚTM_CCOEFF_NORMEDr ÚwhereÚcvtColorÚCOLOR_GRAY2BGRr. Úappendr@ r" ÚdiffrB ÚarrayÚ rectangler6 r7 r8 r9 r: r; )r$ r% r& r< Z block_imageÚtemplater+ r, ÚresÚlocÚcimgÚloc_filtered_xÚloc_filtered_yÚptÚaÚpointsr/ r= rF r r r Úsegment_by_7segmentsu sJ |
| 69abed | 72 | |
| 1b70ca | 73 | , , (r_ c C s g }g }d| } | j }t| dk} tjd| tj| tjtdddd} tj| tjtdddd} tj| tjtdddd} ttj | d k} tjd |
| 5460bf | 74 | | tj| tj |
| 1b70ca | 75 | tdd dd} tj| tjtd d } ttj | d k} tj| tj |
| SP | 76 | td d } tjd| t | |||}t |t |ks.t|| rF|jd t| |||}t |t |krpt| |||}|jd t||sdg}|||fS )aÔ |
| 69abed | 77 | Tries different approaches on image to get student id number. Firstly clears image of noise and then skeletonizes |
| SP | 78 | numbers and thickens it until it gets normalized image. It sends it to the segmentation and recognition functions. |
| 79 | ||
| 80 | Tweak both MORPH_OPEN lines.... | |
| 81 | ||
| 82 | :param image: | |
| 83 | :param classifier: | |
| 84 | :param sid_mask: | |
| 85 | :return: (student_id, error, warning) student id as a string, list of errors and list of warnings during the recognition | |
| 86 | ||
| 1b70ca | 87 | rI éF z/tmp/enSID0.pngr )r r r é r4 z/tmp/enSID1.pngr rH g à?z/tmp/enhancedSID.pngz Trying second SID algorithm.zTrying third SID algorithm.z |
| SP | 88 | Wrong SID!)r r r r r r r |
| 89 | rJ r Zthinr Z skeletonizer? r@ r2 rR r_ rG )r$ r< r& Zsid_warnZsid_errZimage_originalr/ r r r ÚgetSID s4 | |
| 69abed | 90 | |
| 1b70ca | 91 | rb )r Únumpyr Zskimager r Ú pkg_resourcesZ templatefileÚresource_filenameÚ__name__rL r |
| SP | 92 | r- r2 r? rG r_ rb r r r r Ú<module> s "8 |
