From be7942c3c75a64979e60b50cf76aa1000ec57413 Mon Sep 17 00:00:00 2001 From: Tomas Musil Date: Fri, 18 Jul 2014 19:29:56 +0200 Subject: [PATCH] faster gridf, cancel scaling --- src/gridf3.py | 15 +++++++++++++-- src/intrsc.py | 22 +++++++++++----------- 2 files changed, 24 insertions(+), 13 deletions(-) diff --git a/src/gridf3.py b/src/gridf3.py index 8a1a216..6f6f386 100644 --- a/src/gridf3.py +++ b/src/gridf3.py @@ -127,7 +127,7 @@ class Line: elif key == 2: return self.c -def gen_corners(d1, d2): +def gen_corners(d1, d2, min_size): for c1 in d1.points: if c1 in d2.points: continue @@ -136,6 +136,15 @@ def gen_corners(d1, d2): c2 = [p for p in d2.points if p in c1.l1.points][0] c3 = [p for p in d1.points if p in c2.l2.points][0] c4 = [p for p in d2.points if p in c3.l1.points][0] + x_min = min([c1[0], c2[0], c3[0], c4[0]]) + x_max = max([c1[0], c2[0], c3[0], c4[0]]) + if x_max - x_min < min_size: + continue + y_min = min([c1[1], c2[1], c3[1], c4[1]]) + y_max = max([c1[1], c2[1], c3[1], c4[1]]) + if y_max - y_min < min_size: + continue + except IndexError: continue # there is not a corresponding intersection @@ -152,6 +161,8 @@ def dst(p, l): return abs(a * x + b * y + c) / sqrt(a*a+b*b) def score(lines, points): + # TODO find whether the point actualy lies on the line or just in the same + # direction score = 0 for p in points: s = min(map(lambda l: dst(p, l), lines)) @@ -227,7 +238,7 @@ def find(lines, size, l1, l2, bounds, hough, show_all, do_something, logger): diag2.points = ransac.filter_near(data, diag2, 2) - grids = list(gen_corners(diag1, diag2)) + grids = list(gen_corners(diag1, diag2, min(size) / 3)) try: new_sc, new_grid = min(map(lambda g: (score(sum(g, []), data), g), grids)) diff --git a/src/intrsc.py b/src/intrsc.py index 546d0f2..7455d0c 100644 --- a/src/intrsc.py +++ b/src/intrsc.py @@ -75,16 +75,17 @@ def board(image, lines, show_all, do_something): image_p = Image.fromstring('RGB', size, buff, 'raw') do_something(image_p, "color distribution") - max_s0 = max(s[0] for s in board_raw) - min_s0 = min(s[0] for s in board_raw) - norm_s0 = lambda x: (x - min_s0) / (max_s0 - min_s0) - max_s1 = max(s[1] for s in board_raw) - min_s1 = min(s[1] for s in board_raw) - norm_s1 = lambda x: (x - min_s1) / (max_s1 - min_s1) - max_s1 = max(s[1] for s in board_raw) - min_s1 = min(s[1] for s in board_raw) - norm_s1 = lambda x: (x - min_s1) / (max_s1 - min_s1) - color_data = [(norm_s0(s[0]), norm_s1(s[1])) for s in board_raw] + #max_s0 = max(s[0] for s in board_raw) + #min_s0 = min(s[0] for s in board_raw) + #norm_s0 = lambda x: (x - min_s0) / (max_s0 - min_s0) + #max_s1 = max(s[1] for s in board_raw) + #min_s1 = min(s[1] for s in board_raw) + #norm_s1 = lambda x: (x - min_s1) / (max_s1 - min_s1) + #max_s1 = max(s[1] for s in board_raw) + #min_s1 = min(s[1] for s in board_raw) + #norm_s1 = lambda x: (x - min_s1) / (max_s1 - min_s1) + #color_data = [(norm_s0(s[0]), norm_s1(s[1])) for s in board_raw] + color_data = [(s[0], s[1]) for s in board_raw] clusters = k_means.cluster(3, 2,zip(color_data, range(len(color_data))), [[0., 0.5], [0.5, 0.5], [1., 0.5]]) @@ -194,5 +195,4 @@ def stone_color_raw(image, (x, y)): sum(p[2] for p in points) / norm) hue, luma, saturation = colorsys.rgb_to_hls(*color) color = colorsys.hls_to_rgb(hue, 0.5, 1.) - print color return luma, saturation, color, hue -- 2.4.2