diff options
Diffstat (limited to 'src/image/decode_example_test.go')
| -rw-r--r-- | src/image/decode_example_test.go | 140 |
1 files changed, 140 insertions, 0 deletions
diff --git a/src/image/decode_example_test.go b/src/image/decode_example_test.go new file mode 100644 index 000000000..21e90fea4 --- /dev/null +++ b/src/image/decode_example_test.go @@ -0,0 +1,140 @@ +// 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= +` |