* optimize tic tac toe

projects/demo_tic_tac_toe/main.py

@@ -10,6 +10,7 @@
 import cv2
 import numpy as np
 import gc
+from utils import rgb888_to_lab
 
 # 80 fps or 60fps
 disp = display.Display()
@@ -233,61 +234,93 @@ def find_qipan():
     del cam
     gc.collect()
 
+def blob_is_valid(b):
+    is_valid = True
+    if b.area() > 3000: # 认为面积大于3000时无效,受距离影响
+        is_valid = False
+    if b.w() > 55 or b.h() > 55: # 过滤过大的宽高
+        is_valid = False
+    return is_valid
+
 def find_qizi():
-    debug = True
-    black_area_max_th = 6000
+    cam = camera.Camera(320, 320, fps = 60) # fps can set to 80
     area_threshold = 300
     pixels_threshold = 300
-    threshold_red = [[40, 60, 33, 53, -10, 10]]
-    threshold_black = [[0, 20, -128, 127, -128, 127]]
-    threshold_white = [[60, 100, -11, 21, -43, -13]]
-
-    cam = camera.Camera(320, 320, fps = 60) # fps can set to 80
-    # cam.constrast(50)
-    # cam.saturation(0)
+    last_pointer = [0, 0]
+    last_string = ""
+    # 1. 点击触摸屏获取棋子的LAB值，根据LAB值获取一个合适的阈值
+    # 2. 在white_thresholds（白棋阈值）或white_thresholds（黑棋阈值）中增加、或者合并新的阈值。阈值越多执行越慢，也可以自行编写逻辑记录上次的阈值来提高速度
+    # 3. 设置area_threshold和pixels_threshold过滤一些较小的色块
+    # 4. 自定义blob_is_valid来添加其他过滤规则
+    # 5. 添加roi来过滤不需要检测的部分，降低环境复杂程度
+    # 注意：环境太暗时无法识别黑棋有可能是因为棋子离黑线过近，棋子的影子和黑线连在一起被认为时一个色块，导致该棋子被过滤了。建议保证室内有均匀的光线
+    white_thresholds = [[63,96,-13,17,8,56], [60,94,-16,14,-25,23]]
+    black_thresholds = [[9,45,-15,18,-20,19], [16,46,3,33,3,33], [14,44,-16,25,-13,36], [0,33,-15,16,-19,13]]
+    white_blobs = None
+    black_blobs = None
+    roi = [5, 5, cam.width() - 10, cam.height() - 10] # 配置roi范围
     while mode == 3:
         img = cam.read()
-
-        # 软件畸变矫正，速度比较慢，建议直接买无畸变摄像头（Sipeed 官方淘宝点询问）
-        # img = img.lens_corr(strength=1.5)
-
-        blobs = img.find_blobs(threshold_red, roi=[1,1,img.width()-1, img.height()-1], x_stride=2, y_stride=1, area_threshold=area_threshold, pixels_threshold=pixels_threshold)
-        for b in blobs:
-            corners = b.mini_corners()
-            for i in range(4):
-                img.draw_line(corners[i][0], corners[i][1], corners[(i + 1) % 4][0], corners[(i + 1) % 4][1], image.COLOR_YELLOW, 2)
-        blobs = img.find_blobs(threshold_black, roi=[1,1,img.width()-1, img.height()-1], x_stride=2, y_stride=1, area_threshold=area_threshold, pixels_threshold=pixels_threshold)
-        for b in blobs:
-            corners = b.mini_corners()
-            if b.area() < black_area_max_th:      # 过滤掉棋盘，认为area大于800时是棋盘，根据实际值调节
-                enclosing_circle = b.enclosing_circle()
-                img.draw_circle(enclosing_circle[0], enclosing_circle[1], enclosing_circle[2], image.COLOR_GREEN, 2)
-            else:
-                print("black area:", b.area())
-        blobs = img.find_blobs(threshold_white, roi=[1,1,img.width()-1, img.height()-1], x_stride=2, y_stride=1, area_threshold=area_threshold, pixels_threshold=pixels_threshold)
-        for b in blobs:
-            corners = b.mini_corners()
-            enclosing_circle = b.enclosing_circle()
-            img.draw_circle(enclosing_circle[0], enclosing_circle[1], enclosing_circle[2], image.COLOR_RED, 2)
-
-        if debug:
-            # 左下画红色二值化图
-            binary = img.binary(threshold_red, copy=True)
-            binary1 = binary.resize(img.width() // 4, img.height() // 4)
-
-            # 右下画黑色二值化图
-            binary = img.binary(threshold_black, copy=True)
-            binary2 = binary.resize(img.width() // 4, img.height() // 4)
-
-
-            # 右上画白色二值化图
-            binary = img.binary(threshold_white, copy=True)
-            binary3 = binary.resize(img.width() // 4, img.height() // 4)
-
-            img.draw_image(0, img.height() - binary1.height(), binary1)
-            img.draw_image(img.width() - binary2.width(), img.height() - binary2.height(), binary2)
-            img.draw_image(img.width() - binary3.width(), 0, binary3)
-
+        # 检测黑/白棋子
+        for threshold in black_thresholds:
+            black_blobs = img.find_blobs([threshold], roi = roi, area_threshold = area_threshold, pixels_threshold = pixels_threshold)
+            valid_cnt = 0
+            # 检查有效数量大于等于5,则认为阈值有效,否则使用下一个阈值
+            for b in black_blobs:
+                if blob_is_valid(b):
+                    valid_cnt += 1
+            if valid_cnt >= 5:
+                break
+
+        for threshold in white_thresholds:
+            white_blobs = img.find_blobs([threshold], area_threshold = area_threshold, pixels_threshold = pixels_threshold)
+            valid_cnt = 0
+            # 检查有效数量大于等于5,则认为阈值有效,否则使用下一个阈值
+            for b in white_blobs:
+                if blob_is_valid(b):
+                    valid_cnt += 1
+            if valid_cnt >= 5:
+                break
+
+        # 检测完成后打印黑/白棋子位置，在这里做逻辑处理
+        if black_blobs:
+            for b in black_blobs:
+                if blob_is_valid(b):
+                    corners = b.mini_corners()
+                    for i in range(4):
+                        img.draw_line(corners[i][0], corners[i][1], corners[(i + 1) % 4][0], corners[(i + 1) % 4][1], image.COLOR_GREEN, 2)
+
+        if white_blobs:
+            for b in white_blobs:
+                if blob_is_valid(b):
+                    corners = b.mini_corners()
+                    for i in range(4):
+                        img.draw_line(corners[i][0], corners[i][1], corners[(i + 1) % 4][0], corners[(i + 1) % 4][1], image.COLOR_BLUE, 2)
+
+        # 点击屏幕，获取当前lab值，并给出一个预测值。TODO:坐标映射有BUG，以屏幕绿点位置为准
+        t = ts.read()
+        x, y, touch = t[0], t[1], t[2]
+        if touch:
+            cam_w = cam.width()
+            cam_h = cam.height()
+            disp_w = disp.width()
+            disp_h = disp.height()
+            x += ((cam_w - img.width()) / 2)
+            y += ((cam_h - img.height()) / 2)
+            real_x = int(x * cam_w / disp_w)
+            real_y = int(y * cam_h / disp_h)
+            last_pointer[0] = real_x
+            last_pointer[1] = real_y
+            rgb = img.get_pixel(real_x, real_y, True)
+            l, a, b = rgb888_to_lab(rgb[0], rgb[1], rgb[2])
+            last_string = f"l:{l}, a:{a}, b:{b}, try [{max(l-15, 0)},{min(l+15, 100)},{max(a-15, -128)},{min(a+15, 127)},{max(b-15, -128)},{min(b+15, 127)}]"
+            print(last_string)
+        img.draw_circle(last_pointer[0], last_pointer[1], 3, image.COLOR_GREEN, -1)
+        img.draw_string(0, 10, last_string, image.COLOR_RED)
+
+        # 画出roi区域
+        img.draw_rect(roi[0], roi[1], roi[2], roi[3], image.COLOR_YELLOW, 2)
+        disp.show(img)
         check_mode_switch(img, disp.width(), disp.height())
         disp.show(img)
     del cam

projects/demo_tic_tac_toe/utils.py

@@ -0,0 +1,118 @@
+import math
+
+COLOR_L_MAX = 100
+COLOR_L_MIN = 0
+COLOR_A_MAX = 127
+COLOR_A_MIN = -128
+COLOR_B_MAX = 127
+COLOR_B_MIN = -128
+
+xyz_table = [
+    0.000000,  0.030353,  0.060705,  0.091058,  0.121411,  0.151763,  0.182116,  0.212469,
+    0.242822,  0.273174,  0.303527,  0.334654,  0.367651,  0.402472,  0.439144,  0.477695,
+    0.518152,  0.560539,  0.604883,  0.651209,  0.699541,  0.749903,  0.802319,  0.856813,
+    0.913406,  0.972122,  1.032982,  1.096009,  1.161225,  1.228649,  1.298303,  1.370208,
+    1.444384,  1.520851,  1.599629,  1.680738,  1.764195,  1.850022,  1.938236,  2.028856,
+    2.121901,  2.217388,  2.315337,  2.415763,  2.518686,  2.624122,  2.732089,  2.842604,
+    2.955683,  3.071344,  3.189603,  3.310477,  3.433981,  3.560131,  3.688945,  3.820437,
+    3.954624,  4.091520,  4.231141,  4.373503,  4.518620,  4.666509,  4.817182,  4.970657,
+    5.126946,  5.286065,  5.448028,  5.612849,  5.780543,  5.951124,  6.124605,  6.301002,
+    6.480327,  6.662594,  6.847817,  7.036010,  7.227185,  7.421357,  7.618538,  7.818742,
+    8.021982,  8.228271,  8.437621,  8.650046,  8.865559,  9.084171,  9.305896,  9.530747,
+    9.758735,  9.989873, 10.224173, 10.461648, 10.702310, 10.946171, 11.193243, 11.443537,
+    11.697067, 11.953843, 12.213877, 12.477182, 12.743768, 13.013648, 13.286832, 13.563333,
+    13.843162, 14.126329, 14.412847, 14.702727, 14.995979, 15.292615, 15.592646, 15.896084,
+    16.202938, 16.513219, 16.826940, 17.144110, 17.464740, 17.788842, 18.116424, 18.447499,
+    18.782077, 19.120168, 19.461783, 19.806932, 20.155625, 20.507874, 20.863687, 21.223076,
+    21.586050, 21.952620, 22.322796, 22.696587, 23.074005, 23.455058, 23.839757, 24.228112,
+    24.620133, 25.015828, 25.415209, 25.818285, 26.225066, 26.635560, 27.049779, 27.467731,
+    27.889426, 28.314874, 28.744084, 29.177065, 29.613827, 30.054379, 30.498731, 30.946892,
+    31.398871, 31.854678, 32.314321, 32.777810, 33.245154, 33.716362, 34.191442, 34.670406,
+    35.153260, 35.640014, 36.130678, 36.625260, 37.123768, 37.626212, 38.132601, 38.642943,
+    39.157248, 39.675523, 40.197778, 40.724021, 41.254261, 41.788507, 42.326767, 42.869050,
+    43.415364, 43.965717, 44.520119, 45.078578, 45.641102, 46.207700, 46.778380, 47.353150,
+    47.932018, 48.514994, 49.102085, 49.693300, 50.288646, 50.888132, 51.491767, 52.099557,
+    52.711513, 53.327640, 53.947949, 54.572446, 55.201140, 55.834039, 56.471151, 57.112483,
+    57.758044, 58.407842, 59.061884, 59.720179, 60.382734, 61.049557, 61.720656, 62.396039,
+    63.075714, 63.759687, 64.447968, 65.140564, 65.837482, 66.538730, 67.244316, 67.954247,
+    68.668531, 69.387176, 70.110189, 70.837578, 71.569350, 72.305513, 73.046074, 73.791041,
+    74.540421, 75.294222, 76.052450, 76.815115, 77.582222, 78.353779, 79.129794, 79.910274,
+    80.695226, 81.484657, 82.278575, 83.076988, 83.879901, 84.687323, 85.499261, 86.315721,
+    87.136712, 87.962240, 88.792312, 89.626935, 90.466117, 91.309865, 92.158186, 93.011086,
+    93.868573, 94.730654, 95.597335, 96.468625, 97.344529, 98.225055, 99.110210, 100.000000
+]
+
+def fast_cbrtf(x):
+    return x ** (1.0 / 3.0)
+
+def fast_floorf(x):
+    return math.floor(x)
+
+def rgb888_to_l(r, g, b):
+    r_lin = xyz_table[r]
+    g_lin = xyz_table[g]
+    b_lin = xyz_table[b]
+
+    y = ((r_lin * 0.2126) + (g_lin * 0.7152) + (b_lin * 0.0722)) * (1.0 / 100.0)
+
+    if y > 0.008856:
+        y = fast_cbrtf(y)
+    else:
+        y = (y * 7.787037) + 0.137931
+
+    L = fast_floorf(116 * y) - 16
+    L = max(min(L, COLOR_L_MAX), COLOR_L_MIN)
+
+    return int(L)
+
+def rgb888_to_a(r, g, b):
+    r_lin = xyz_table[r]
+    g_lin = xyz_table[g]
+    b_lin = xyz_table[b]
+
+    x = ((r_lin * 0.4124) + (g_lin * 0.3576) + (b_lin * 0.1805)) * (1.0 / 95.047)
+    y = ((r_lin * 0.2126) + (g_lin * 0.7152) + (b_lin * 0.0722)) * (1.0 / 100.0)
+
+    if x > 0.008856:
+        x = fast_cbrtf(x)
+    else:
+        x = (x * 7.787037) + 0.137931
+
+    if y > 0.008856:
+        y = fast_cbrtf(y)
+    else:
+        y = (y * 7.787037) + 0.137931
+
+    a = fast_floorf(500 * (x - y))
+    a = max(min(a, COLOR_A_MAX), COLOR_A_MIN)
+
+    return int(a)
+
+def rgb888_to_b(r, g, b):
+    r_lin = xyz_table[r]
+    g_lin = xyz_table[g]
+    b_lin = xyz_table[b]
+
+    y = ((r_lin * 0.2126) + (g_lin * 0.7152) + (b_lin * 0.0722)) * (1.0 / 100.0)
+    z = ((r_lin * 0.0193) + (g_lin * 0.1192) + (b_lin * 0.9505)) * (1.0 / 108.883)
+
+    if y > 0.008856:
+        y = fast_cbrtf(y)
+    else:
+        y = (y * 7.787037) + 0.137931
+
+    if z > 0.008856:
+        z = fast_cbrtf(z)
+    else:
+        z = (z * 7.787037) + 0.137931
+
+    b = fast_floorf(200 * (y - z))
+    b = max(min(b, COLOR_B_MAX), COLOR_B_MIN)
+
+    return int(b)
+
+def rgb888_to_lab(r, g, b):
+    l = rgb888_to_l(r, g, b)
+    a = rgb888_to_a(r, g, b)
+    b = rgb888_to_b(r, g, b)
+    return l, a, b