diff --git a/mainscripts/Sorter.py b/mainscripts/Sorter.py index a802f95..db766e0 100644 --- a/mainscripts/Sorter.py +++ b/mainscripts/Sorter.py @@ -359,8 +359,95 @@ def sort_by_hist(input_path): return img_list -def sort_by_hist_dissim(input_path): +class HistDissimSubprocessor(SubprocessorBase): + #override + def __init__(self, img_list ): + self.img_list = img_list + self.img_list_range = [i for i in range(0, len(img_list) )] + self.result = [] + + super().__init__('HistDissim', 60) + + #override + def onHostClientsInitialized(self): + pass + + #override + def process_info_generator(self): + for i in range(0, min(multiprocessing.cpu_count(), 8) ): + yield 'CPU%d' % (i), {}, {'device_idx': i, + 'device_name': 'CPU%d' % (i), + 'img_list' : self.img_list + } + + #override + def get_no_process_started_message(self): + print ( 'Unable to start CPU processes.') + + #override + def onHostGetProgressBarDesc(self): + return "Sorting" + + #override + def onHostGetProgressBarLen(self): + return len (self.img_list) + + #override + def onHostGetData(self): + if len (self.img_list_range) > 0: + return [self.img_list_range.pop(0)] + + return None + + #override + def onHostDataReturn (self, data): + self.img_list_range.insert(0, data[0]) + + #override + def onClientInitialize(self, client_dict): + self.img_list = client_dict['img_list'] + self.img_list_len = len(self.img_list) + + self.safe_print ('Running on %s.' % (client_dict['device_name']) ) + return None + + #override + def onClientFinalize(self): + pass + + #override + def onClientProcessData(self, data): + i = data[0] + score_total = 0 + for j in range( 0, self.img_list_len): + if i == j: + continue + score_total += cv2.compareHist(self.img_list[i][1], self.img_list[j][1], cv2.HISTCMP_BHATTACHARYYA) + \ + cv2.compareHist(self.img_list[i][2], self.img_list[j][2], cv2.HISTCMP_BHATTACHARYYA) + \ + cv2.compareHist(self.img_list[i][3], self.img_list[j][3], cv2.HISTCMP_BHATTACHARYYA) + + return score_total + + #override + def onClientGetDataName (self, data): + #return string identificator of your data + return data[1] + + #override + def onHostResult (self, data, result): + self.img_list[data[0]][4] = result + return 1 + + #override + def onHostProcessEnd(self): + pass + + #override + def get_start_return(self): + return self.img_list + +def sort_by_hist_dissim(input_path): print ("Sorting by histogram dissimilarity...") img_list = [] @@ -371,24 +458,13 @@ def sort_by_hist_dissim(input_path): cv2.calcHist([img], [2], None, [256], [0, 256]), 0 ]) - img_list_len = len(img_list) - for i in tqdm ( range(0, img_list_len), desc="Sorting"): - score_total = 0 - for j in range( 0, img_list_len): - if i == j: - continue - score_total += cv2.compareHist(img_list[i][1], img_list[j][1], cv2.HISTCMP_BHATTACHARYYA) + \ - cv2.compareHist(img_list[i][2], img_list[j][2], cv2.HISTCMP_BHATTACHARYYA) + \ - cv2.compareHist(img_list[i][3], img_list[j][3], cv2.HISTCMP_BHATTACHARYYA) - - img_list[i][4] = score_total - - + img_list = HistDissimSubprocessor(img_list).process() + print ("Sorting...") img_list = sorted(img_list, key=operator.itemgetter(4), reverse=True) return img_list - + def final_rename(input_path, img_list): for i in tqdm( range(0,len(img_list)), desc="Renaming" , leave=False): src = Path (img_list[i][0])