http://www.mediawiki.org/wiki/Special:Code/pywikipedia/11621

Revision: 11621 Author: drtrigon Date: 2013-06-07 14:53:04 +0000 (Fri, 07 Jun 2013) Log Message: ----------- improvement; start of code structure clean-up

Modified Paths: -------------- trunk/pywikipedia/catimages.py

Modified: trunk/pywikipedia/catimages.py =================================================================== --- trunk/pywikipedia/catimages.py 2013-06-06 21:19:06 UTC (rev 11620) +++ trunk/pywikipedia/catimages.py 2013-06-07 14:53:04 UTC (rev 11621) @@ -143,7 +143,199 @@

# all detection and recognition methods - bindings to other classes, modules and libs -class FileData(object): + +class UnknownFile(object): + def __init__(self, filename, *args, **kwargs): + self.filename = filename + self._info = {} + + def getProperties(self): + # check/look into the file by midnight commander (mc) + # https://pypi.python.org/pypi/hachoir-metadata + #self._detect_HeaderAndMetadata() + + # get mime-type file-size, ... + pass + + def getFeatures(self): + pass + + def _detect_Properties_PIL(self): + """Retrieve as much file property info possible, especially the same + as commons does in order to compare if those libraries (ImageMagick, + ...) are buggy (thus explicitely use other software for independence)""" + #self.image_size = (None, None) + result = {'Format': u'-', 'Pages': 0} + if self.image_fileext == u'.svg': # MIME: 'application/xml; charset=utf-8' + # similar to PDF page count OR use BeautifulSoup + svgcountpages = re.compile("<page>") + pc = len(svgcountpages.findall( file(self.image_path,"r").read() )) + + #svg = rsvg.Handle(self.image_path) + + # http://validator.w3.org/docs/api.html#libs + # http://pypi.python.org/pypi/py_w3c/ + vld = HTMLValidator() + valid = u'SVG' + try: + vld.validate(self.image.fileUrl()) + valid = (u'Valid SVG' if vld.result.validity == 'true' else u'Invalid SVG') + except urllib2.URLError: + pass + except ValidationFault: + pass + #print vld.errors, vld.warnings + + #self.image_size = (svg.props.width, svg.props.height) + + result = { 'Format': valid, + 'Mode': u'-', + 'Palette': u'-', + 'Pages': pc, } + # may be set {{validSVG}} also or do something in bot template to + # recognize 'Format=SVG (valid)' ... + elif self.image_mime[1] == 'pdf': # MIME: 'application/pdf; charset=binary' + # http://code.activestate.com/recipes/496837-count-pdf-pages/ + #rxcountpages = re.compile(r"$\s*/Type\s*/Page[/\s]", re.MULTILINE|re.DOTALL) + rxcountpages = re.compile(r"/Type\s*/Page([^s]|$)", re.MULTILINE|re.DOTALL) # PDF v. 1.3,1.4,1.5,1.6 + pc = len(rxcountpages.findall( file(self.image_path,"rb").read() )) + + result = { 'Format': u'PDF', + 'Mode': u'-', + 'Palette': u'-', + 'Pages': pc, } + elif self.image_mime[1] == 'x-xcf': # MIME: 'image/x-xcf; charset=binary' + result = { 'Format': u'%s' % self.image_mime[1].upper() } + # DO NOT use ImageMagick (identify) instead of PIL to get these info !! + elif (self.image_mime[0] == 'image') and \ + (self.image_mime[1] != 'vnd.djvu'): # MIME: 'image/jpeg; charset=binary', ... + try: + i = Image.open(self.image_path) + except IOError: + pywikibot.warning(u'unknown (image) file type [_detect_Properties_PIL]') + return {'Properties': [result]} + + # http://mail.python.org/pipermail/image-sig/1999-May/000740.html + pc=0 # count number of pages + while True: + try: + i.seek(pc) + except EOFError: + break + pc+=1 + i.seek(0) # restore default + + # http://grokbase.com/t/python/image-sig/082psaxt6k/embedded-icc-profiles + # python-lcms (littlecms) may be freeimage library + #icc = i.app['APP2'] # jpeg + #icc = i.tag[34675] # tiff + #icc = re.sub('[^%s]'%string.printable, ' ', icc) + ## more image formats and more post-processing needed... + + #self.image_size = i.size + + result = { #'bands': i.getbands(), + #'bbox': i.getbbox(), + 'Format': i.format, + 'Mode': i.mode, + #'info': i.info, + #'stat': os.stat(self.image_path), + 'Palette': str(len(i.palette.palette)) if i.palette else u'-', + 'Pages': pc, } + elif self.image_mime[1] == 'ogg': # MIME: 'application/ogg; charset=binary' + # 'ffprobe' (ffmpeg); audio and video streams files (ogv, oga, ...) + d = self._util_get_DataStreams_FFMPEG() + #print d + result['Format'] = u'%s' % d['format']['format_name'].upper() + elif self.image_mime[1] == 'midi': # MIME: 'audio/midi; charset=binary' + result['Format'] = u'%s' % self.image_mime[1].upper() + # djvu: python-djvulibre or python-djvu for djvu support + # http://pypi.python.org/pypi/python-djvulibre/0.3.9 + else: + pywikibot.warning(u'unknown (generic) file type [_detect_Properties_PIL]') + return {'Properties': [result]} + + result['Dimensions'] = self.image_size + result['Filesize'] = os.path.getsize(self.image_path) + result['MIME'] = u'%s/%s' % tuple(self.image_mime[:2]) + + #self._info['Properties'] = [result] + self._info['Properties'][0].update(result) + return {'Properties': [result]} + + +class JpegFile(UnknownFile): + # for '_detect_Trained_CV' + cascade_files = [(u'Legs', 'haarcascade_lowerbody.xml'), + (u'Torsos', 'haarcascade_upperbody.xml'), + (u'Ears', 'haarcascade_mcs_leftear.xml'), + (u'Ears', 'haarcascade_mcs_rightear.xml'), + (u'Eyes', 'haarcascade_lefteye_2splits.xml'), # (http://yushiqi.cn/research/eyedetection) + (u'Eyes', 'haarcascade_righteye_2splits.xml'), # (http://yushiqi.cn/research/eyedetection) + #externals/opencv/haarcascades/haarcascade_mcs_lefteye.xml + #externals/opencv/haarcascades/haarcascade_mcs_righteye.xml + # (others include indifferent (left and/or right) and pair) + (u'Automobiles', 'cars3.xml'), # http://www.youtube.com/watch?v=c4LobbqeKZc + (u'Hands', '1256617233-2-haarcascade-hand.xml', 300.),] # http://www.andol.info/ + # ('Hands' does not behave very well, in fact it detects any kind of skin and other things...) + #(u'Aeroplanes', 'haarcascade_aeroplane.xml'),] # e.g. for 'Category:Unidentified aircraft' + + def getProperties(self): + pass + + # Image size + self._detect_Properties_PIL() + + def getFeatures(self): + # Faces (extract EXIF data) + self._detect_Faces_EXIF() + # Faces and eyes (opencv pre-trained haar) + self._detect_Faces_CV() +# TODO: test and use or switch off + # Face via Landmark(s) +# self._detect_FaceLandmark_xBOB() + # exclude duplicates (CV and EXIF) + faces = [item['Position'] for item in self._info['Faces']] + for i in self._util_merge_Regions(faces)[1]: + del self._info['Faces'][i] + + # Segments and colors + self._detect_SegmentColors_JSEGnPIL() + # Average color + self._detect_AverageColor_PILnCV() + + # People/Pedestrian (opencv pre-trained hog and haarcascade) + self._detect_People_CV() + + # Geometric object (opencv hough line, circle, edges, corner, ...) + self._detect_Geometry_CV() + + # general (opencv pre-trained, third-party and self-trained haar + # and cascade) classification + # http://www.computer-vision-software.com/blog/2009/11/faq-opencv-haartraining... + for cf in self.cascade_files: + self._detect_Trained_CV(*cf) + + # optical and other text recognition (tesseract & ocropus, ...) + self._detect_EmbeddedText_poppler() +# self._recognize_OpticalText_ocropus() + # (may be just classify as 'contains text', may be store text, e.g. to wikisource) + + # barcode and Data Matrix recognition (libdmtx/pydmtx, zbar, gocr?) + self._recognize_OpticalCodes_dmtxNzbar() + + # Chessboard (opencv reference detector) + self._detect_Chessboard_CV() + + # general (self-trained) detection WITH classification + # BoW: uses feature detection (SIFT, SURF, ...) AND classification (SVM, ...) +# self._detectclassify_ObjectAll_CV() + # Wavelet: uses wavelet transformation AND classification (machine learning) +# self._detectclassify_ObjectAll_PYWT() + + # general file EXIF history information + self._detect_History_EXIF() + # .../opencv/samples/c/facedetect.cpp # http://opencv.willowgarage.com/documentation/python/genindex.html def _detect_Faces_CV(self): @@ -157,7 +349,8 @@ # http://www.cognotics.com/opencv/servo_2007_series/part_4/index.html

# skip file formats not supported (yet?) - if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']): + if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']) or \ + (self.image_mime[0] in ['audio']): return

# https://code.ros.org/trac/opencv/browser/trunk/opencv_extra/testdata/gpu/haa... @@ -699,7 +892,8 @@ self._info['Geometry'] = []

# skip file formats not supported (yet?) - if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']): + if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']) or \ + (self.image_mime[0] in ['audio']): return

result = self._util_get_Geometry_CVnSCIPY() @@ -970,7 +1164,8 @@ self._info['ColorRegions'] = []

# skip file formats not supported (yet?) - if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']): + if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']) or \ + (self.image_mime[0] in ['audio']): return

try: @@ -1032,7 +1227,8 @@ self._info['ColorAverage'] = []

# skip file formats not supported (yet?) - if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']): + if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']) or \ + (self.image_mime[0] in ['audio']): return

try: @@ -1050,109 +1246,6 @@ self._info['ColorAverage'] = [result] return

- def _detect_Properties_PIL(self): - """Retrieve as much file property info possible, especially the same - as commons does in order to compare if those libraries (ImageMagick, - ...) are buggy (thus explicitely use other software for independence)""" - #self.image_size = (None, None) - self._info['Properties'] = [{'Format': u'-', 'Pages': 0}] - if self.image_fileext == u'.svg': # MIME: 'application/xml; charset=utf-8' - # similar to PDF page count OR use BeautifulSoup - svgcountpages = re.compile("<page>") - pc = len(svgcountpages.findall( file(self.image_path,"r").read() )) - - #svg = rsvg.Handle(self.image_path) - - # http://validator.w3.org/docs/api.html#libs - # http://pypi.python.org/pypi/py_w3c/ - vld = HTMLValidator() - valid = u'SVG' - try: - vld.validate(self.image.fileUrl()) - valid = (u'Valid SVG' if vld.result.validity == 'true' else u'Invalid SVG') - except urllib2.URLError: - pass - except ValidationFault: - pass - #print vld.errors, vld.warnings - - #self.image_size = (svg.props.width, svg.props.height) - - result = { 'Format': valid, - 'Mode': u'-', - 'Palette': u'-', - 'Pages': pc, } - # may be set {{validSVG}} also or do something in bot template to - # recognize 'Format=SVG (valid)' ... - elif self.image_mime[1] == 'pdf': # MIME: 'application/pdf; charset=binary' - # http://code.activestate.com/recipes/496837-count-pdf-pages/ - #rxcountpages = re.compile(r"$\s*/Type\s*/Page[/\s]", re.MULTILINE|re.DOTALL) - rxcountpages = re.compile(r"/Type\s*/Page([^s]|$)", re.MULTILINE|re.DOTALL) # PDF v. 1.3,1.4,1.5,1.6 - pc = len(rxcountpages.findall( file(self.image_path,"rb").read() )) - - result = { 'Format': u'PDF', - 'Mode': u'-', - 'Palette': u'-', - 'Pages': pc, } - elif (self.image_mime[0] == 'image') and \ - (self.image_mime[1] != 'vnd.djvu'): # MIME: 'image/jpeg; charset=binary', ... - try: - i = Image.open(self.image_path) - except IOError: - pywikibot.warning(u'unknown (image) file type [_detect_Properties_PIL]') - return - - # http://mail.python.org/pipermail/image-sig/1999-May/000740.html - pc=0 # count number of pages - while True: - try: - i.seek(pc) - except EOFError: - break - pc+=1 - i.seek(0) # restore default - - # http://grokbase.com/t/python/image-sig/082psaxt6k/embedded-icc-profiles - # python-lcms (littlecms) may be freeimage library - #icc = i.app['APP2'] # jpeg - #icc = i.tag[34675] # tiff - #icc = re.sub('[^%s]'%string.printable, ' ', icc) - ## more image formats and more post-processing needed... - - #self.image_size = i.size - - result = { #'bands': i.getbands(), - #'bbox': i.getbbox(), - 'Format': i.format, - 'Mode': i.mode, - #'info': i.info, - #'stat': os.stat(self.image_path), - 'Palette': str(len(i.palette.palette)) if i.palette else u'-', - 'Pages': pc, } - elif self.image_mime[1] == 'ogg': # MIME: 'application/ogg; charset=binary' - # 'ffprobe' (ffmpeg); audio and video streams files (ogv, oga, ...) - d = self._util_get_DataStreams_FFMPEG() - #print d - result = { 'Format': u'%s' % d['format']['format_name'].upper() } - elif self.image_mime[0] == 'audio': # MIME: 'audio/midi; charset=binary' - result = {} - # djvu: python-djvulibre or python-djvu for djvu support - # http://pypi.python.org/pypi/python-djvulibre/0.3.9 - #elif self.image_fileext == u'.xcf' - # result = {} - # # DO NOT use ImageMagick (identify) instead of PIL to get these info !! - else: - pywikibot.warning(u'unknown (generic) file type [_detect_Properties_PIL]') - return - - result['Dimensions'] = self.image_size - result['Filesize'] = os.path.getsize(self.image_path) - result['MIME'] = u'%s/%s' % tuple(self.image_mime[:2]) - - #self._info['Properties'] = [result] - self._info['Properties'][0].update(result) - return - # http://stackoverflow.com/questions/2270874/image-color-detection-using-pytho... # https://gist.github.com/1246268 # colormath-1.0.8/examples/delta_e.py, colormath-1.0.8/examples/conversions.py @@ -1413,7 +1506,8 @@ self._info[info_desc] = []

# skip file formats not supported (yet?) - if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']): + if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']) or \ + (self.image_mime[0] in ['audio']): return

# http://tutorial-haartraining.googlecode.com/svn/trunk/data/haarcascades/ @@ -1634,7 +1728,8 @@ self._info['OpticalCodes'] = []

# skip file formats not supported (yet?) - if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']): + if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']) or \ + (self.image_mime[0] in ['audio']): return

# DataMatrix @@ -1734,7 +1829,8 @@ self._info['Chessboard'] = []

# skip file formats not supported (yet?) - if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']): + if (self.image_mime[1] in ['ogg', 'pdf', 'vnd.djvu']) or \ + (self.image_mime[0] in ['audio']): return

scale = 1. @@ -2306,45 +2402,6 @@

return self._buffer_FFMPEG

- def _detect_Streams_FFMPEG(self): - self._info['Streams'] = [] - - # skip file formats that interfere and can cause strange results (pdf is oga?!) - # or file formats not supported (yet?) - if (self.image_mime[1] in ['pdf']) or (self.image_fileext in [u'.svg']): - return - - # audio and video streams files (ogv, oga, ...) - d = self._util_get_DataStreams_FFMPEG() - if not d: - return - - result = [] - for s in d['streams']: - #print s - if (s["codec_type"] == "video"): - rate = s["avg_frame_rate"] - dim = (int(s["width"]), int(s["height"])) - #asp = s["display_aspect_ratio"] - elif (s["codec_type"] == "audio"): -# switch this part off since 'ffprobe' (on toolserver) is too old -# rate = u'%s/%s/%s' % (s["channels"], s["sample_fmt"], s["sample_rate"]) - rate = u'%s/%s/%s' % (s["channels"], u'-', int(float(s["sample_rate"]))) - dim = None - elif (s["codec_type"] == "data"): - rate = None - dim = None - - result.append({ 'ID': int(s["index"]) + 1, - 'Format': u'%s/%s' % (s["codec_type"], s.get("codec_name",u'?')), - 'Rate': rate or u'-', - 'Dimensions': dim or (None, None), - }) - - if 'image' not in d["format"]["format_name"]: - self._info['Streams'] = result - return - def _util_merge_Regions(self, regs, sub=False, overlap=False, close=False): # sub=False, overlap=False, close=False ; level 0 ; similar regions, similar position (default) # sub=True, overlap=False, close=False ; level 1 ; region contained in other, any shape/size @@ -2410,70 +2467,74 @@

return (regs, drop)

- def _detect_AudioFeatures_MUSIC21(self): - # skip file formats not supported - if (self.image_mime[1] not in ['midi']): - return

- self._info['Audio'] = [] +class PngFile(JpegFile): + pass

- import _music21 as music21 +class GifFile(JpegFile): + pass

- #audiofile = '/home/ursin/Desktop/3_Ships.mid' - audiofile = self.image_path +class TiffFile(JpegFile): + pass

- #music21.features.jSymbolic.getCompletionStats() - try: - #s = music21.converter.ConverterMidi() - #s.parseFile(audiofile) - #s = s.stream - s = music21.midi.translate.midiFilePathToStream(audiofile) - except music21.midi.base.MidiException: - pywikibot.warning(u'unknown file type [_detect_AudioFeatures_MUSIC21]') +class XcfFile(JpegFile): + pass + +class SvgFile(JpegFile): + pass + +class PdfFile(JpegFile): + pass + +#class DjvuFile(JpegFile): +# pass + + +class OggFile(JpegFile): + def getFeatures(self): + # general handling of all audio and video formats + self._detect_Streams_FFMPEG() + + # general audio feature extraction +# self._detect_AudioFeatures_YAAFE() + + def _detect_Streams_FFMPEG(self): + self._info['Streams'] = [] + + # skip file formats that interfere and can cause strange results (pdf is oga?!) + # or file formats not supported (yet?) + if (self.image_mime[1] in ['pdf']) or (self.image_fileext in [u'.svg']): return

- #fs = music21.features.jSymbolic.extractorsById - #for k in fs: - # for i in range(len(fs[k])): - # if fs[k][i] is not None: - # n = fs[k][i].__name__ - # if fs[k][i] not in music21.features.jSymbolic.featureExtractors: - # n += " (not implemented)" - # print k, i, n - # else: - # fe = fs[k][i](s) - # print k, i, n, - # try: - # f = fe.extract() - # print f.name, f.vector - # except AttributeError: - # print "ERROR" - data = {} - for item in ['MostCommonPitchFeature', - 'ImportanceOfBassRegisterFeature', - 'ImportanceOfMiddleRegisterFeature', - 'ImportanceOfHighRegisterFeature', - 'AverageNoteDurationFeature', - 'MaximumNoteDurationFeature', - #'DurationFeature', - 'InitialTempoFeature', - 'MaximumNumberOfIndependentVoicesFeature', - 'AverageNumberOfIndependentVoicesFeature',]: - fe = getattr(music21.features.jSymbolic, item)(s) - f = fe.extract() - #data[f.name] = f.vector[0] - data[item.replace('Feature', '')] = f.vector[0] - #print s.duration - data['Duration'] = s.highestTime - #print s.offsetMap - #print s.measureOffsetMap() - data['Metadata'] = s.metadata - data['Lyrics'] = s.lyrics() - #print s.seconds - #print s.secondsMap + # audio and video streams files (ogv, oga, ...) + d = self._util_get_DataStreams_FFMPEG() + if not d: + return

- self._info['Audio'] = [data] -# print self._info['Audio'] + result = [] + for s in d['streams']: + #print s + if (s["codec_type"] == "video"): + rate = s["avg_frame_rate"] + dim = (int(s["width"]), int(s["height"])) + #asp = s["display_aspect_ratio"] + elif (s["codec_type"] == "audio"): +# switch this part off since 'ffprobe' (on toolserver) is too old +# rate = u'%s/%s/%s' % (s["channels"], s["sample_fmt"], s["sample_rate"]) + rate = u'%s/%s/%s' % (s["channels"], u'-', int(float(s["sample_rate"]))) + dim = None + elif (s["codec_type"] == "data"): + rate = None + dim = None + + result.append({ 'ID': int(s["index"]) + 1, + 'Format': u'%s/%s' % (s["codec_type"], s.get("codec_name",u'?')), + 'Rate': rate or u'-', + 'Dimensions': dim or (None, None), + }) + + if 'image' not in d["format"]["format_name"]: + self._info['Streams'] = result return

def _detect_AudioFeatures_YAAFE(self): @@ -2634,10 +2695,125 @@ return

+class MidiFile(UnknownFile): + def getProperties(self): + result = {} + result.update( self._detect_HeaderAndMetadata() ) # Metadata + result.update( self._detect_Properties_PIL() ) # Properties + return result + + def getFeatures(self): + result = {} + result.update( self._detect_AudioFeatures_MUSIC21() ) # Audio + return result + + def _detect_HeaderAndMetadata(self): + result = {} + + # extract data from midi file + # http://valentin.dasdeck.com/midi/midifile.htm + # http://stackoverflow.com/questions/3943149/reading-and-interpreting-data-fro... + ba = bytearray(open(self.filename, 'rb').read()) + i = -1 + for key, data in [('Text', '\x01'), ('Copyright', '\x02'), ('Lyrics', '\x05')]: + result[key] = [] + while True: + i = ba.find('\xff%s' % data, i+1) + if i < 0: # something found? + break + e = (i+3+ba[i+2]) + if ba[e] != 0: # length match with string end (00)? + e = ba.find('\x00', (i+3+ba[i+2])) + result[key].append(ba[i+3:e].decode('latin-1').strip()) + result[key] = u'\n'.join(result[key]) + + import _music21 as music21 + try: + s = music21.converter.parse(self.filename) + if s.metadata: + pywikibot.output(unicode(s.metadata)) + result['Metadata'].update(s.metadata) + except music21.midi.base.MidiException: + pass + + self._info['Metadata'] = [result] + return {'Metadata': [result]} + + # midi audio feature extraction + def _detect_AudioFeatures_MUSIC21(self): + # skip file formats not supported + if (self.image_mime[1] not in ['midi']): + return + + import _music21 as music21 + + #audiofile = '/home/ursin/Desktop/3_Ships.mid' + audiofile = self.image_path + + #music21.features.jSymbolic.getCompletionStats() + try: + #s = music21.midi.translate.midiFilePathToStream(audiofile) + s = music21.converter.parse(audiofile) + except music21.midi.base.MidiException: + pywikibot.warning(u'unknown file type [_detect_AudioFeatures_MUSIC21]') + return + + #fs = music21.features.jSymbolic.extractorsById + #for k in fs: + # for i in range(len(fs[k])): + # if fs[k][i] is not None: + # n = fs[k][i].__name__ + # if fs[k][i] not in music21.features.jSymbolic.featureExtractors: + # n += " (not implemented)" + # print k, i, n + # else: + # fe = fs[k][i](s) + # print k, i, n, + # try: + # f = fe.extract() + # print f.name, f.vector + # except AttributeError: + # print "ERROR" + data = {'RegisterImportance': (music21.features.jSymbolic.ImportanceOfBassRegisterFeature(s).extract().vector[0], + music21.features.jSymbolic.ImportanceOfMiddleRegisterFeature(s).extract().vector[0], + music21.features.jSymbolic.ImportanceOfHighRegisterFeature(s).extract().vector[0],), + 'NoteDuration': (music21.features.jSymbolic.AverageNoteDurationFeature(s).extract().vector[0], + music21.features.jSymbolic.MaximumNoteDurationFeature(s).extract().vector[0],), + 'IndependentVoices': (music21.features.jSymbolic.AverageNumberOfIndependentVoicesFeature(s).extract().vector[0], + music21.features.jSymbolic.MaximumNumberOfIndependentVoicesFeature(s).extract().vector[0],), + 'MostCommonPitch': music21.features.jSymbolic.MostCommonPitchFeature(s).extract().vector[0], + 'Tempo': music21.features.jSymbolic.InitialTempoFeature(s).extract().vector[0], + 'Duration': s.highestTime, + #'Metadata': s.metadata if s.metadata else u'', + 'Lyrics': s.lyrics(recurse=True) if s.lyrics(recurse=True) else u'',} + #print music21.text.assembleLyrics(s) + #print s.duration + #print s.offsetMap + #print s.measureOffsetMap() + #print s.seconds + #print s.secondsMap + + self._info['Audio'] += [data] + return {'Audio': [data]} + + +FILETYPES = { '*': UnknownFile, + ( 'image', 'jpeg'): JpegFile, + ( 'image', 'png'): PngFile, + ( 'image', 'gif'): GifFile, + ( 'image', 'tiff'): TiffFile, + ( 'image', 'x-xcf'): XcfFile, + ( 'image', 'svg+xml'): SvgFile, + ('application', 'pdf'): PdfFile, +# ( 'image', 'vnd.djvu'): DjvuFile, + ('application', 'ogg'): OggFile, + ( 'audio', 'midi'): MidiFile,} + + # all classification and categorization methods and definitions - default variation # use simplest classification I can think of (self-made) and do categorization # mostly based on filtered/reported features -class CatImages_Default(FileData): +class CatImages_Default(object): #ignore = [] ignore = ['color']

@@ -2854,6 +3030,21 @@

return (u'Graphics', bool(relevance))

+# # Category:MIDI files created with GNU LilyPond +# def _cat_audio_MIDIfilescreatedwithGNULilyPond(self): +# # find metadata in extracted data +# print [item.strip() for item in re.findall('Generated .*?\n', u'\n'.join(result['Text']))] +# #u"Cr'eateur: GNU LilyPond 2.0.1" +# import dateutil.parser +# dates = [] +# for line in result['Text']: +# # http://stackoverflow.com/questions/3276180/extracting-date-from-a-string-in-... +# try: +# dates.append(dateutil.parser.parse(line, fuzzy=True).isoformat(' ').decode('utf-8')) +# except ValueError: +# pass +# print dates + # Category:Categorized by DrTrigonBot def _addcat_BOT(self): # - ALWAYS - @@ -3099,7 +3290,7 @@ self.image_mime = re.split('[/;\s]', m.file(self.image_path)) #self.image_size = (None, None) mime = mimetypes.guess_all_extensions('%s/%s' % tuple(self.image_mime[0:2])) - if self.image_fileext.lower() not in mime: + if mime and (self.image_fileext.lower() not in mime): pywikibot.warning(u'File extension does not match MIME type! File extension should be %s.' % mime)

# SVG: rasterize the SVG to bitmap (MAY BE GET FROM WIKI BY DOWNLOAD?...) @@ -3146,6 +3337,9 @@ #data = Popen("identify -verbose info: %s" % self.image_path, # shell=True, stderr=PIPE).stderr.read() #print data + if not os.path.exists(self.image_path_JPEG): + # xcf can have more than 1 layer/page like gif, tiff, and movies... + self.image_path_JPEG = self.image_path_JPEG.replace('.jpg', '-0.jpg') self.image_size = Image.open(self.image_path_JPEG).size else: try: @@ -3168,6 +3362,8 @@

self.image_size = (img.shape[1], img.shape[0]) except: + if os.path.exists(self.image_path_JPEG): + os.remove(self.image_path_JPEG) self.image_path_JPEG = self.image_path except: self.image_path_JPEG = self.image_path @@ -3502,69 +3698,38 @@

# gather data from all information interfaces def gatherFeatures(self): - # Image size - self._detect_Properties_PIL() - + self._info['Properties'] = [{'Format': u'-', 'Pages': 0}] + self._info['Metadata'] = [] + self._info['ColorAverage'] = [] + self._info['ColorRegions'] = [] self._info['Faces'] = [] - # Faces (extract EXIF data) - self._detect_Faces_EXIF() - # Faces and eyes (opencv pre-trained haar) - self._detect_Faces_CV() -# TODO: test and use or switch off - # Face via Landmark(s) -# self._detect_FaceLandmark_xBOB() - # exclude duplicates (CV and EXIF) - faces = [item['Position'] for item in self._info['Faces']] - for i in self._util_merge_Regions(faces)[1]: - del self._info['Faces'][i] + self._info['OpticalCodes'] = [] + self._info['People'] = [] + self._info['Chessboard'] = [] + self._info['Text'] = [] + self._info['Streams'] = [] + self._info['Audio'] = [] + self._info['Legs'] = [] + self._info['Hands'] = [] + self._info['Torsos'] = [] + self._info['Ears'] = [] + self._info['Eyes'] = [] + self._info['Automobiles'] = []

- # Segments and colors - self._detect_SegmentColors_JSEGnPIL() - # Average color - self._detect_AverageColor_PILnCV() + # split detection and extraction according to file types; JpegFile, ... + TypeFile = FILETYPES.get(tuple(self.image_mime[:2]), FILETYPES['*']) + tf = TypeFile(self.image_path) + import copy + tf.__dict__.update(copy.deepcopy(self.__dict__)) + for func in ['getProperties', 'getFeatures']: + result = getattr(tf, func)() + if result: + self._info.update(result) +# print self._info +# print tf._info + #print tf.__dict__ + self._info = tf._info

- # People/Pedestrian (opencv pre-trained hog and haarcascade) - self._detect_People_CV() - - # Geometric object (opencv hough line, circle, edges, corner, ...) - self._detect_Geometry_CV() - - # general (opencv pre-trained, third-party and self-trained haar - # and cascade) classification - # http://www.computer-vision-software.com/blog/2009/11/faq-opencv-haartraining... - for cf in self.cascade_files: - self._detect_Trained_CV(*cf) - - # optical and other text recognition (tesseract & ocropus, ...) - self._detect_EmbeddedText_poppler() -# self._recognize_OpticalText_ocropus() - # (may be just classify as 'contains text', may be store text, e.g. to wikisource) - - # barcode and Data Matrix recognition (libdmtx/pydmtx, zbar, gocr?) - self._recognize_OpticalCodes_dmtxNzbar() - - # Chessboard (opencv reference detector) - self._detect_Chessboard_CV() - - # general (self-trained) detection WITH classification - # BoW: uses feature detection (SIFT, SURF, ...) AND classification (SVM, ...) -# self._detectclassify_ObjectAll_CV() - # Wavelet: uses wavelet transformation AND classification (machine learning) -# self._detectclassify_ObjectAll_PYWT() - - # general handling of all audio and video formats - self._detect_Streams_FFMPEG() - - # general file EXIF history information - self._detect_History_EXIF() - - # general audio feature extraction -# self._detect_AudioFeatures_YAAFE() - - # midi audio feature extraction -# TODO: improve midi/audio stuff ... - self._detect_AudioFeatures_MUSIC21() - def _existInformation(self, info, ignore = ['Properties', 'ColorAverage']): result = [] for item in info: @@ -3684,6 +3849,11 @@ result = self._info['Streams'] return {'Streams': result}

+# def _filter_Audio(self): +# # use all, (should be reliable) +# result = self._info['Audio'] +# return {'Audio': result} + #def _filter_Geometry(self): # result = [] # for item in self._info['Geometry']: