嗨我有黑色背景，有一个白点。我有白色像素的所有坐标。
points = np.where(image==255)
“print points”给了我这个输出，我看到元组列表中有两个数组：
(array([119, 119, 119, 119, 120, 120, 120, 120, 120, 120, 120, 120, 120,
120, 120, 120, 121, 121, 121, 121, 121, 121, 121, 121, 121, 121,
121, 121, 121, 121, 121, 121, 122, 122, 122, 122, 122, 122, 122,
122, 122, 122, 122, 122, 122, 122, 122, 122, 122, 122, 122, 122,
123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123, 123,
123, 123, 123, 123, 123, 123, 123, 123, 123, 124, 124, 124, 124,
124, 124, 124, 124, 124, 124, 124, 124, 124, 124, 124, 124, 124,
124, 124, 124, 124, 124, 124, 124, 125, 125, 125, 125, 125, 125,
125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125, 125,
125, 125, 125, 125, 125, 125, 125, 126, 126, 126, 126, 126, 126,
126, 126, 126, 126, 126, 126, 126, 126, 126, 126, 126, 126, 126,
126, 126, 126, 126, 126, 126, 126, 126, 126, 127, 127, 127, 127,
127, 127, 127, 127, 127, 127, 127, 127, 127, 127, 127, 127, 127,
127, 127, 127, 127, 127, 127, 127, 127, 127, 127, 127, 127, 127,
128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128,
128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128, 128,
128, 128, 128, 128, 129, 129, 129, 129, 129, 129, 129, 129, 129,
129, 129, 129, 129, 129, 129, 129, 129, 129, 129, 129, 129, 129,
129, 129, 129, 129, 129, 129, 129, 129, 129, 129, 130, 130, 130,
130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130,
130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130,
130, 130, 130, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131,
131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131,
131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 131, 132, 132,
132, 132, 132, 132, 132, 132, 132, 132, 132, 132, 132, 132, 132,
132, 132, 132, 132, 132, 132, 132, 132, 132, 132, 132, 132, 132,
132, 132, 132, 132, 132, 132, 133, 133, 133, 133, 133, 133, 133,
133, 133, 133, 133, 133, 133, 133, 133, 133, 133, 133, 133, 133,
133, 133, 133, 133, 133, 133, 133, 133, 133, 133, 133, 133, 133,
133, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134,
134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 134,
134, 134, 134, 134, 134, 134, 134, 134, 134, 134, 135, 135, 135,
135, 135, 135, 135, 135, 135, 135, 135, 135, 135, 135, 135, 135,
135, 135, 135, 135, 135, 135, 135, 135, 135, 135, 135, 135, 135,
135, 135, 135, 135, 135, 135, 136, 136, 136, 136, 136, 136, 136,
136, 136, 136, 136, 136, 136, 136, 136, 136, 136, 136, 136, 136,
136, 136, 136, 136, 136, 136, 136, 136, 136, 136, 136, 136, 136,
136, 136, 136, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137,
137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137,
137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137, 137,
138, 138, 138, 138, 138, 138, 138, 138, 138, 138, 138, 138, 138,
138, 138, 138, 138, 138, 138, 138, 138, 138, 138, 138, 138, 138,
138, 138, 138, 138, 138, 138, 138, 138, 138, 139, 139, 139, 139,
139, 139, 139, 139, 139, 139, 139, 139, 139, 139, 139, 139, 139,
139, 139, 139, 139, 139, 139, 139, 139, 139, 139, 139, 139, 139,
139, 139, 139, 139, 139, 140, 140, 140, 140, 140, 140, 140, 140,
140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140,
140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140, 140,
141, 141, 141, 141, 141, 141, 141, 141, 141, 141, 141, 141, 141,
141, 141, 141, 141, 141, 141, 141, 141, 141, 141, 141, 141, 141,
141, 141, 141, 141, 141, 141, 141, 141, 142, 142, 142, 142, 142,
142, 142, 142, 142, 142, 142, 142, 142, 142, 142, 142, 142, 142,
142, 142, 142, 142, 142, 142, 142, 142, 142, 142, 142, 142, 142,
142, 142, 142, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143,
143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 143,
143, 143, 143, 143, 143, 143, 143, 143, 143, 143, 144, 144, 144,
144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144,
144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144, 144,
144, 144, 144, 145, 145, 145, 145, 145, 145, 145, 145, 145, 145,
145, 145, 145, 145, 145, 145, 145, 145, 145, 145, 145, 145, 145,
145, 145, 145, 145, 145, 145, 145, 145, 146, 146, 146, 146, 146,
146, 146, 146, 146, 146, 146, 146, 146, 146, 146, 146, 146, 146,
146, 146, 146, 146, 146, 146, 146, 146, 146, 146, 146, 146, 147,
147, 147, 147, 147, 147, 147, 147, 147, 147, 147, 147, 147, 147,
147, 147, 147, 147, 147, 147, 147, 147, 147, 147, 147, 147, 147,
147, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148,
148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148, 148,
148, 148, 149, 149, 149, 149, 149, 149, 149, 149, 149, 149, 149,
149, 149, 149, 149, 149, 149, 149, 149, 149, 149, 149, 149, 149,
149, 150, 150, 150, 150, 150, 150, 150, 150, 150, 150, 150, 150,
150, 150, 150, 150, 150, 150, 150, 150, 150, 150, 150, 151, 151,
151, 151, 151, 151, 151, 151, 151, 151, 151, 151, 151, 151, 151,
151, 151, 151, 151, 151, 152, 152, 152, 152, 152, 152, 152, 152,
152, 152, 152, 152, 152, 152, 152, 152, 152, 153, 153, 153, 153,
153, 153, 153, 153, 153, 153, 153, 153, 153, 154, 154, 154, 154, 154]), array([77, 78, 79, 80, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 71,
72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 69, 70,
71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87,
88, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77,
78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 66, 67, 68, 69,
70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86,
87, 88, 89, 90, 91, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76,
77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 64,
65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81,
82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 64, 65, 66, 67, 68,
69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85,
86, 87, 88, 89, 90, 91, 92, 93, 63, 64, 65, 66, 67, 68, 69, 70, 71,
72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88,
89, 90, 91, 92, 93, 94, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73,
74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91,
92, 93, 94, 95, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91,
92, 93, 94, 95, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91,
92, 93, 94, 95, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73,
74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 95, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,
73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
90, 91, 92, 93, 94, 95, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88,
89, 90, 91, 92, 93, 94, 95, 96, 61, 62, 63, 64, 65, 66, 67, 68, 69,
70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86,
87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 61, 62, 63, 64, 65, 66, 67,
68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84,
85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 61, 62, 63, 64, 65, 66,
67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 62, 63, 64, 65, 66,
67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 62, 63, 64, 65, 66,
67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 62, 63, 64, 65, 66,
67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 62, 63, 64, 65, 66,
67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 63, 64, 65, 66, 67, 68,
69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85,
86, 87, 88, 89, 90, 91, 92, 93, 94, 63, 64, 65, 66, 67, 68, 69, 70,
71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87,
88, 89, 90, 91, 92, 93, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74,
75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91,
92, 93, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 65, 66, 67, 68,
69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85,
86, 87, 88, 89, 90, 91, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76,
77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 67, 68, 69,
70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86,
87, 88, 89, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82,
83, 84, 85, 86, 87, 88, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
81, 82, 83, 84, 85, 86, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82,
83, 84, 76, 77, 78, 79, 80]))
我想找到平均坐标。看起来像（x，y）。
我该怎么做？
答案 0 :(得分：0)
您已经可以使用python的内置函数来计算每个元组部分的总和。不要忘记检查len（points [n]）＆gt; 0以避免除以零的异常。
myAvgPoint = (sum(points[0])/len(points[0]),sum(points[1])/len(points[1]))
答案 1 :(得分：0)
np.where返回一个与2, N数组同构的元组，您想要在N白点上计算平均值，即在第二轴上计算，计数来自0，axis=1 ---最终你的计算只是一个单一的
np.average(np.where(image==255), axis=1)
答案 2 :(得分：0)
np.average（np.where（image == 255），axis = 1）
这是真正的解决方案。
我的结果是： [136.6045082 78.33913934]