def on_touch_up(self, touch): global letter1 global letter2 global turn if touch.is_double_tap: if turn: letter1.downsampleShape(150) self.canvas.clear() else: letter2.downsampleShape(150) self.canvas.clear() # distance (letter1, letter2) #strokes1 = letter1.split_non_differentiable_points(1.2) #strokes2 = letter2.split_non_differentiable_points(1.2) #print len(strokes1) #print len(strokes2) #dist = stroke.compare(strokes1, strokes2) letter1.normalize_wrt_max() letter2.normalize_wrt_max() dist = stroke.cloud_dist(letter1,letter2) print dist letter1.reset() letter2.reset() turn = not turn
def on_touch_up(self, touch): global letter1 global letter2 global turn if touch.is_double_tap: if turn: letter1.downsampleShape(150) self.canvas.clear() else: letter2.downsampleShape(150) self.canvas.clear() # distance (letter1, letter2) #strokes1 = letter1.split_non_differentiable_points(1.2) #strokes2 = letter2.split_non_differentiable_points(1.2) #print len(strokes1) #print len(strokes2) #dist = stroke.compare(strokes1, strokes2) letter1.normalize_wrt_max() letter2.normalize_wrt_max() dist = stroke.cloud_dist(letter1, letter2) print dist letter1.reset() letter2.reset() turn = not turn
def minScore(data, draw, name): try: score_min = stroke.cloud_dist(data[name][0],draw) except IndexError: draw.downsampleShape(70) score_min = stroke.cloud_dist(data[name][0],draw) #print data[name][0].get_len() #print draw.get_len() for ref in data[name]: try: score_new = stroke.cloud_dist(ref,draw) except IndexError: draw.downsampleShape(70) score_new = stroke.cloud_dist(ref,draw) #print ref.get_len() #print draw.get_len() if score_new<score_min: score_min = score_new return score_min
def minScore(data, draw, name): try: score_min = stroke.cloud_dist(data[name][0], draw) except IndexError: draw.downsampleShape(70) score_min = stroke.cloud_dist(data[name][0], draw) #print data[name][0].get_len() #print draw.get_len() for ref in data[name]: try: score_new = stroke.cloud_dist(ref, draw) except IndexError: draw.downsampleShape(70) score_new = stroke.cloud_dist(ref, draw) #print ref.get_len() #print draw.get_len() if score_new < score_min: score_min = score_new return score_min