1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
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
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
|
// Copyright 2012 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
// This example demonstrates decoding a JPEG image and examining its pixels.
package image_test
import (
"encoding/base64"
"fmt"
"image"
"log"
"strings"
// Package image/jpeg is not used explicitly in the code below,
// but is imported for its initialization side-effect, which allows
// image.Decode to understand JPEG formatted images. Uncomment these
// two lines to also understand GIF and PNG images:
// _ "image/gif"
// _ "image/png"
_ "image/jpeg"
)
func Example() {
// Decode the JPEG data. If reading from file, create a reader with
//
// reader, err := os.Open("testdata/video-001.q50.420.jpeg")
// if err != nil {
// log.Fatal(err)
// }
// defer reader.Close()
reader := base64.NewDecoder(base64.StdEncoding, strings.NewReader(data))
m, _, err := image.Decode(reader)
if err != nil {
log.Fatal(err)
}
bounds := m.Bounds()
// Calculate a 16-bin histogram for m's red, green, blue and alpha components.
//
// An image's bounds do not necessarily start at (0, 0), so the two loops start
// at bounds.Min.Y and bounds.Min.X. Looping over Y first and X second is more
// likely to result in better memory access patterns than X first and Y second.
var histogram [16][4]int
for y := bounds.Min.Y; y < bounds.Max.Y; y++ {
for x := bounds.Min.X; x < bounds.Max.X; x++ {
r, g, b, a := m.At(x, y).RGBA()
// A color's RGBA method returns values in the range [0, 65535].
// Shifting by 12 reduces this to the range [0, 15].
histogram[r>>12][0]++
histogram[g>>12][1]++
histogram[b>>12][2]++
histogram[a>>12][3]++
}
}
// Print the results.
fmt.Printf("%-14s %6s %6s %6s %6s\n", "bin", "red", "green", "blue", "alpha")
for i, x := range histogram {
fmt.Printf("0x%04x-0x%04x: %6d %6d %6d %6d\n", i<<12, (i+1)<<12-1, x[0], x[1], x[2], x[3])
}
// Output:
// bin red green blue alpha
// 0x0000-0x0fff: 353 759 7228 0
// 0x1000-0x1fff: 629 2944 1036 0
// 0x2000-0x2fff: 1075 2319 984 0
// 0x3000-0x3fff: 838 2291 988 0
// 0x4000-0x4fff: 540 1302 542 0
// 0x5000-0x5fff: 319 971 263 0
// 0x6000-0x6fff: 316 377 178 0
// 0x7000-0x7fff: 581 280 216 0
// 0x8000-0x8fff: 3457 228 274 0
// 0x9000-0x9fff: 2294 237 334 0
// 0xa000-0xafff: 938 283 370 0
// 0xb000-0xbfff: 322 338 401 0
// 0xc000-0xcfff: 229 386 295 0
// 0xd000-0xdfff: 263 416 281 0
// 0xe000-0xefff: 538 433 312 0
// 0xf000-0xffff: 2758 1886 1748 15450
}
const data = `
/9j/4AAQSkZJRgABAQIAHAAcAAD/2wBDABALDA4MChAODQ4SERATGCgaGBYWGDEjJR0oOjM9PDkzODdA
SFxOQERXRTc4UG1RV19iZ2hnPk1xeXBkeFxlZ2P/2wBDARESEhgVGC8aGi9jQjhCY2NjY2NjY2NjY2Nj
Y2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2NjY2P/wAARCABnAJYDASIAAhEBAxEB/8QA
HwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQAAAF9AQIDAAQRBRIh
MUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVW
V1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXG
x8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEAAwEBAQEBAQEBAQAAAAAAAAECAwQF
BgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSExBhJBUQdhcRMiMoEIFEKRobHBCSMzUvAV
YnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOE
hYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq
8vP09fb3+Pn6/9oADAMBAAIRAxEAPwDlwKMD0pwzSiuK57QzGDxS7D6in8Y5ximnAPUfSlcq4m3ilUYp
2OKXHvRcVxnTtS7c07HNFK4DQPakC4PNOA+tOx70XAjK/So5gBGP94fzqfvUVx/qxx/EP51UXqRP4WSE
cmgjilP3jSEZqS0IO/NGDnpUiocDg/McDjvV6HTPOdVWYgsM5KcfzzQ2JySM2jp6VYu7SWzmMUwG4cgj
kMPUVBjjtTGtRu0Zopw+lFFxhinrGzuqqMsxAA9yaXFSRv5cqSEcIwYj6GpuZ30O30fSLKzhUpbpNMv3
5XGTn29BV28jt7pPLuIVljPBBFVreYx+VbqAjycgt3x14zRcNOxGyVFHQkIc/wA61exyKLbuzjdZ046d
ftEuTEw3Rk9SPT8P8Kpbea3tchbyVae4JkjbbGpGdwOM89Af6ViFTWUtGdcXoM2+woK1JtpNtTcoZt+l
Jt7ZqTbRtouFyPFRXI/c9D94fzqzioLsfuD/ALw/nVReqIn8LJCOTSY+tSMOTmkIpXLRu+F0t5pJxPHG
wjjUAuBjJJz1+laD6Pai+WaK9SBX6puzn6ZP+NV/Dkdtc6ZNbyAFwxLAHDYPv6VoQ21nPNEEiQGEFRtk
Gf0NaWTOeW7Of8QwGG4MRZnEbYXPJwRnOR0zWNXW+KrqBLUWi5EjbWCgcAA9c/gRXKYqZaGlK/LqMH0F
FLtHvRSNiYD2pSDTgpp6p0ywUHoTULXYxcktzrdCf7Xo8LP/AKyEmMNjJ46dfbFWJ5TDGNwB9lFUvDV9
YrbfYGbyrjcWG88S57g+vtV26ZIvMlumKwwjLZ6V0WfU54yTvYwtbubea2WNWbzg4bYQeBgj8OtYeKhj
u4y2HQxqxOD1xzxmrWAQCCGB6EGsaikndmsJxeiYzBo280/Z7UbayuaXGY5oIp+2lx9KLjIsVDeD/Rj/
ALy/zq1t96r3y4tT/vL/ADq4P3kRP4WSleTSFKkkKoCW4GaqNcMxIjXj1pxjKT0FKrGC1Nrw3vGrKkYz
5kTAr6455/HH510UdwPtRgWCbzF5+YYUf4Vwun39xpmoR3qASMmQUJwGU9Rnt/8AWrpbrxhb8/ZdOmaQ
gAGZwFH5ZJrpVKVlY5ZYhN6kXiu2eO/ikZlIljAAB5yM549OawSOOlPuLqe+umuLqTfM4OSOAo7ADsKh
hl/cRsTuJHPv7mlKi3sVTxNtGP20VJhThgSQaK52mnZnUqsWrpkyeUrr5pABOAPU1AGaXUCWJISHGPfP
P8qL7BiKnsMg46H3qrbzupbj5mPTPTpXVSglG551SpzSsXJ4/MBUgYIxyKpySyGBYJriV1D7kRpCVH4V
bSeNJ4xchni3DeqnBI+td7F4b0mKIRjT45VbktJlzk455+n6VtYzv2PNwFZWBHBGKVJDGVC54/nXQeMN
NttLNkba1jgWVWDmM8bhg4/nzXLSSbXVj6fyNKUdNRp21RtIRJGrjuM0u3FQ2DbodvcEkfQmrW2vLqLl
k0ejCXNFMj2/jQV9qkxSYNRcsZiq2oI32N2CkhWXJxwOe9XMcVt6hoPn6dFaW0wgRpNzvKDlz6+/0rai
ryv2Jm9LHJai+ZRGCBjnr71ErdAxAY9B611t1Y2cunbbaOQ3FvKZI3UqGlZMbiWwfcfhV231iwvLSM3U
lt5Uq52TuZG+hGMA12xXJGxxzjzybOQtNOvb5j9ktZJhnBIHyg+5PFX38JayqK/2eLJIBUTgkDA9q7ex
itrSHFpGsUbndhRgc+g7VNIyfZJAoJZUbb3I46CtFJMylBo8sdWhmYMuCnylc9wef5VUT7+1chc5NS7h
sUZO5RtIPUH3pkBDOxxxmqM9TQtn+WilhHfHaik43KTG3Z4IyPyrNVjGCsZ+dmwv6V3cXhSG8sYpJLud
JJIwxChdoJGcYx/Wkg8DafA4knvLiQr/ALqj+VQpKw3FtnFFfvbiSMgZJ6/jXp2n3d9cQRBTFsKD96EP
oOxPU/8A68VVtbbRtMVntbePKDLTSHJH/Aj/AEqHTvE66rq72VugMMcbSGTnL4wMAfjT5n0HyW3L+s6b
baxaJBdzN+7bcrxkAhun0rz3VNCv7e7lgigknWI43xLu6jjIHTjtXqfkpPGVYsBkghTikgsYIN/lhgXb
cxLkknp/ShczQ7xtY8vtEmhkj8yGRBuCnehUcnHcVtmwfJ/fQ8e7f/E12txZW91C0U6b42xlST2OR/Ko
Bo1gM/uW55/1jf41nOipu7LhV5FZHIGzI6zwj/vr/Ck+yr3uYf8Ax7/CutbQdMb71tn/ALaN/jSf8I/p
X/PoP++2/wAan6rAr6wzkWt0II+1Rc/7Lf4Vd1eeCSKBbdZDdShYoiZNoyfY10P/AAj2lf8APmP++2/x
oPh/SjKspsozIuNrZORjp3qo0FHYPb3OZt7ae3SzjuItsiRSAgnccl/UA+3Q1yNjKLR4ZZYY5VD7tkv3
WwO/+e1evPp9nI257aJm6bioz1z1+tY+s6Hplnot9PbWMMcqwOFcLyOO1bJWMZSTOPHi+9w3mosrlyd2
9lCj02g9P/1e9a3hzxAbl2ikZRcdQueHHt7j864Y8Z4I4oRzG6urFWU5BHBB7HNJxTFGbR6he6Vpmtgm
eLy5zwZI/lb8fX8azIvBUUTHdfSFP4QsYB/HNZ+k+KEnRY75hHOvAk6K/v7H9K6yyvlnQBmDZ6GsnzR0
N0oy1RzOtaN/Y1tHNFO06u+zYy4I4Jzx9KKveJblXuordSGES5b6n/62PzorKVdp2LjQTVyWz8UWEWlq
jSgyxfJt6EgdDzWTdeLIZGO7zHI/hVajGmWWP+PWL8qwlAIURrhpMAHHJA71pRcZrToZzcoEuo6heakA
GHk245CZ6/X1qPTLq40q+W5t2QybSpDAkEEc55/zilk5k2r91eKhLDzWz2rpsczbbuemeD76fUNG865I
MiysmQMZAAwa3a5j4ftu0ByP+fh/5CulkLLG7INzhSVHqe1Fh3uOoqn9qQQxyhndmHIxwOmSR2xQ13KD
KoiBZOV9JBnt707MVy5RWdNdy7wRGf3bfMinnO1jg+vY03WXLaJO3mhQ20b0zwpYf0qlG7S7icrJs08U
VwumgC+YiQyeVtZH567hzj8aSL949oGhE/2v5pJCDkksQwBHC4/+vXQ8LZ2uYxxCavY7us/xCcaBfn0h
b+VP0bnSrb94ZMJgOecj1rl/GfidUE2k2gy5+SeQjgA/wj3rlas2jdao48qrjLAGkSKPk4Gc1WMj92I+
lIJnU8OfxPWo5inBokmtQTmM4OOh71b0q6vbFmWCbaxHyqQGAP0PT8KhSTzVyo5ocSKA5VfTOTmqsmRd
pl99XjPzThzK3zOeOSeveirNmkgg/fIpYsTkYORxRXmzlTjJqx6EVUcU7mhkKCzdAK59QI9zYxtG1fYU
UVtgtmY4nZEa8Ak9aqFv3rfSiiu1nMeifDv/AJF+T/r4f+QrqqKKQwzQenNFFMCOKFIgNuThdoJ5OPSk
ubeK6t3gnXdG4wwziiii/UTKMOg6dbzJLFE4dSCP3rEdeOM8805tDsGMvySgSsS6rM6gk9eAcUUVftZt
3uyVGNthuq3Eei6DK8H7sRR7YuMgHtXkc8rzTNLM26RyWY+p70UVnLY0iEsUipG7rhZBlDkc1HgYoorM
0HwyBXGeRjmrcUhMg2ghezd//rUUVcTKW5s2jZtY/QDaOKKKK8ip8bPRj8KP/9k=
`
|
