def check_performance(self, validate_generator, times=1, metrics=['distance', 'youden', 'jaccard', 'dice']): for i in range(times): pic = validate_generator.next() true = pic[1][0] pred = self.model.predict(pic[0][0].reshape( 1, self.rowDim, self.colDim, self.channels)) pred = moil.convertImageNetOutput(pred) true = moil.convertImageNetOutput(true) met.customMetric(pred, true, metrics=metrics) x = [] x.append(pic[0][0].reshape( (self.rowDim, self.colDim, self.channels))) x.append(true) x.append(pred) if self.show_function != None: self.show_function(x)
def validate(self, pathForce=None, validateMode=0, preprocessFunc=lambda x: x, draw=True, onlyWithMetric=False, onlyWithoutMetric=False, sumTimes=None, metrics=['distance', 'youden', 'jaccard', 'dice'], validTimes=1, weightsTimesValids=None, validName=''): avgs, globals = (0, 0) for i in range(validTimes): if weightsTimesValids is not None: self.constantVar = i * weightsTimesValids self.load_weights() sum = [0] * len(metrics) confusion_matrix = [0] * 4 globalCount = False for metr in metrics: if 'global' in metr: globalCount = True times = 0 visited_path = {} while True: if pathForce is None: path = self.validate_path_provider_func( self.validate_start_path, visited_path) visited_path[path] = times else: path = pathForce if path is None: break if not os.path.exists(path): continue images = os.listdir(path) for imp in images: # len(os.listdir(path)) - 2): true_path = path + 'mask/' if not os.path.exists(os.path.join(path, imp)): continue if onlyWithMetric and not os.path.exists( os.path.join(true_path, imp)): continue else: if onlyWithoutMetric and os.path.exists( os.path.join(true_path, imp)): continue im = self.read_func(name=imp, extension='', path=path, target_size=(self.colDim, self.rowDim), mode=0) imgX, img = self.prepareImage(im, retboth=True) pred = self.model.predict(imgX) pred = moil.convertImageNetOutput(pred) toDraw = im if draw else None x = [im, pred, img] if os.path.exists(os.path.join(true_path, imp)): true = self.read_func(name=imp, extension='', path=true_path, target_size=(self.colDim, self.rowDim)) true = true.reshape( (self.rowDim, self.colDim, self.out_channels)) x.append(true) results = met.customMetric(pred, true, toDraw=toDraw, metrics=metrics, globalCount=globalCount) sum = list(map(add, sum, results[0])) confusion_matrix = list( map(add, confusion_matrix, results[1])) times += 1 if sumTimes is not None and times >= sumTimes: break else: met.draw(pred, toDraw) if sumTimes is None: self.show_function(x) avgs = [x / times for x in sum] strgSum = '' strgAvgs = '' for val in sum: strgSum += str(val) + ', ' for val in avgs: strgAvgs += str(val) + ', ' globals = [] if globalCount: globals = met.globals(confusion_matrix) print("Global Jaccard: " + str(globals[0]) + ", Global Dice: " + str(globals[1])) print("Times: " + str(times) + ", sums: " + strgSum + "Average metrics: " + strgAvgs) self.validate_to_csv(metrics, avgs + globals, validName) return avgs + globals