{"id":13222,"date":"2024-01-27T23:04:45","date_gmt":"2024-01-27T15:04:45","guid":{"rendered":"https:\/\/blog.iyatt.com\/?p=13222"},"modified":"2024-05-05T12:30:53","modified_gmt":"2024-05-05T04:30:53","slug":"python-%e4%b8%ad%e5%b8%b8%e7%94%a8%e5%9b%be%e5%83%8f%e6%95%b0%e6%8d%ae%e7%bb%93%e6%9e%84%ef%bc%88%e9%87%8d%e5%86%99%e4%b8%ad%ef%bc%89","status":"publish","type":"post","link":"https:\/\/blog.iyatt.com\/?p=13222","title":{"rendered":"Python \u4e2d\u5e38\u7528\u56fe\u50cf\u6570\u636e\u7ed3\u6784"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 ez-toc-wrap-center counter-hierarchy ez-toc-counter ez-toc-light-blue ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title ez-toc-toggle\" style=\"cursor:pointer\">\u76ee\u5f55<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#1_%E6%B5%8B%E8%AF%95%E7%8E%AF%E5%A2%83\" >1 \u6d4b\u8bd5\u73af\u5883<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#2_%E5%9B%BE%E5%83%8F%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84\" >2 \u56fe\u50cf\u6570\u636e\u7ed3\u6784<\/a><ul class='ez-toc-list-level-2' ><li class='ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#21_OpenCV_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E5%B9%B6%E6%98%BE%E7%A4%BA\" >2.1 OpenCV \u6253\u5f00\u56fe\u7247\u5e76\u663e\u793a<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#22_Matplotlib_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E5%B9%B6%E6%98%BE%E7%A4%BA\" >2.2 Matplotlib \u6253\u5f00\u56fe\u7247\u5e76\u663e\u793a<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#23_Pillow_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E7%94%A8_OpenCV_%E6%98%BE%E7%A4%BA\" >2.3 Pillow \u6253\u5f00\u56fe\u7247\u7528 OpenCV \u663e\u793a<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#24_OpenCV_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E7%94%A8_Tkinter_%E6%98%BE%E7%A4%BA%EF%BC%88OpenCV_%E8%BD%AC_Pillow%EF%BC%89\" >2.4 OpenCV \u6253\u5f00\u56fe\u7247\u7528 Tkinter \u663e\u793a\uff08OpenCV \u8f6c Pillow\uff09<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#25_Pillow_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E5%B9%B6%E4%BD%BF%E7%94%A8_Tkinter_%E6%98%BE%E7%A4%BA\" >2.5 Pillow \u6253\u5f00\u56fe\u7247\u5e76\u4f7f\u7528 Tkinter \u663e\u793a<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#26_Matplotlib_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E7%94%A8_OpenCV_%E6%98%BE%E7%A4%BA\" >2.6 Matplotlib \u6253\u5f00\u56fe\u7247\u7528 OpenCV \u663e\u793a<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#27_OpenCV_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E7%94%A8_Matplotlib_%E6%98%BE%E7%A4%BA\" >2.7 OpenCV \u6253\u5f00\u56fe\u7247\u7528 Matplotlib \u663e\u793a<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#28_Matplotlib_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E7%94%A8_Tkinter_%E6%98%BE%E7%A4%BA\" >2.8 Matplotlib \u6253\u5f00\u56fe\u7247\u7528 Tkinter \u663e\u793a<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#3_%E5%9F%BA%E4%BA%8E_NumPy_%E6%95%B0%E7%BB%84%E7%9A%84%E5%9B%BE%E5%83%8F%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84%E6%93%8D%E4%BD%9C\" >3 \u57fa\u4e8e NumPy \u6570\u7ec4\u7684\u56fe\u50cf\u6570\u636e\u7ed3\u6784\u64cd\u4f5c<\/a><ul class='ez-toc-list-level-2' ><li class='ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#31_%E9%A2%9C%E8%89%B2%E9%80%9A%E9%81%93%E9%A1%BA%E5%BA%8F%E8%BD%AC%E6%8D%A2\" >3.1 \u989c\u8272\u901a\u9053\u987a\u5e8f\u8f6c\u6362<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#32_%E5%9B%BE%E5%83%8F%E9%83%A8%E5%88%86%E6%88%AA%E5%8F%96\" >3.2 \u56fe\u50cf\u90e8\u5206\u622a\u53d6<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#33_%E9%A2%9C%E8%89%B2%E9%80%9A%E9%81%93%E5%88%86%E7%A6%BB\" >3.3 \u989c\u8272\u901a\u9053\u5206\u79bb<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#331_OpenCV\" >3.3.1 OpenCV<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#332_Matplotlib\" >3.3.2 Matplotlib<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#34_%E6%B7%B1%E6%8B%B7%E8%B4%9D%E5%92%8C%E6%B5%85%E6%8B%B7%E8%B4%9D\" >3.4 \u6df1\u62f7\u8d1d\u548c\u6d45\u62f7\u8d1d<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#35_%E8%B4%B4%E5%9B%BE\" >3.5 \u8d34\u56fe<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#351_%E9%80%8F%E6%98%8E%E5%BA%A6%E9%80%9A%E9%81%93\" >3.5.1 \u900f\u660e\u5ea6\u901a\u9053<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-20\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#36_%E8%AF%BB%E5%9B%BE%E9%BB%98%E8%AE%A4%E6%95%B0%E6%8D%AE%E7%B1%BB%E5%9E%8B\" >3.6 \u8bfb\u56fe\u9ed8\u8ba4\u6570\u636e\u7c7b\u578b<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-21\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#361_OpenCV\" >3.6.1 OpenCV<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-22\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#362_Matplotlib\" >3.6.2 Matplotlib<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-23\" href=\"https:\/\/blog.iyatt.com\/?p=13222\/#363_Pillow\" >3.6.3 Pillow<\/a><\/li><\/ul><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h1><span class=\"ez-toc-section\" id=\"1_%E6%B5%8B%E8%AF%95%E7%8E%AF%E5%A2%83\"><\/span>1 \u6d4b\u8bd5\u73af\u5883<span class=\"ez-toc-section-end\"><\/span><\/h1>\n<p>Python 3.12.1<\/p>\n<p>numpy 1.26.3<br \/>\nopencv-python 4.9.0.80<br \/>\npillow 10.2.0<br \/>\nmatplotlib 3.8.2<\/p>\n<p>\u6ce8\uff1a<\/p>\n<ul>\n<li>\u57fa\u4e8e 2022.1.16 \u548c 2022.4.9 \u7684\u4e09\u7bc7\u535a\u6587\u518d\u6b21\u9a8c\u8bc1\u5e76\u91cd\u5199\uff0c\u539f\u6587\u5df2\u5220\u9664<\/li>\n<li>\u6d4b\u8bd5\u4f7f\u7528\u7684\u56fe\u7247\u6587\u4ef6\u4e3a AI \u7ed8\u5236<\/li>\n<\/ul>\n<h1><span class=\"ez-toc-section\" id=\"2_%E5%9B%BE%E5%83%8F%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84\"><\/span>2 \u56fe\u50cf\u6570\u636e\u7ed3\u6784<span class=\"ez-toc-section-end\"><\/span><\/h1>\n<h2><span class=\"ez-toc-section\" id=\"21_OpenCV_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E5%B9%B6%E6%98%BE%E7%A4%BA\"><\/span>2.1 OpenCV \u6253\u5f00\u56fe\u7247\u5e76\u663e\u793a<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Python \u7248 OpenCV \u4e2d\u56fe\u50cf\u6570\u636e\u662f\u7528\u7684 NumPy \u6570\u7ec4\u5b58\u50a8\uff0c\u901a\u9053\u987a\u5e8f\u4e3a BGRA\uff08\u84dd \u7eff \u7ea2 \u900f\u660e\u5ea6\uff09\uff0c\u4e09\u901a\u9053\u5219\u4e3a BGR\u3002<\/p>\n<pre><code class=\"language-py\">import cv2\n\nimage_path = &#039;demo.png&#039; # \u56fe\u7247\u8def\u5f84\n\nimg = cv2.imread(image_path) # \u6253\u5f00\u56fe\u7247\u6587\u4ef6\ncv2.imshow(&#039;my image&#039;, # \u7a97\u53e3\u6807\u9898\n           img) # \u56fe\u50cf\u6570\u636e\ncv2.waitKey(0) # \u963b\u585e\u7a97\u53e3\uff0c\u6309\u4efb\u610f\u952e\u7ee7\u7eed\ncv2.destroyAllWindows() # \u5173\u95ed\u6240\u6709\u7a97\u53e3<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706362769723.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 561px; --smush-placeholder-aspect-ratio: 561\/800;\" \/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"22_Matplotlib_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E5%B9%B6%E6%98%BE%E7%A4%BA\"><\/span>2.2 Matplotlib \u6253\u5f00\u56fe\u7247\u5e76\u663e\u793a<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Matplotlib \u548c OpenCV \u4e00\u6837\u90fd\u662f\u91c7\u7528\u7684 NumPy \u6570\u7ec4\u5b58\u50a8\u56fe\u50cf\u6570\u636e\uff0c\u53ea\u662f\u901a\u9053\u987a\u5e8f\u4e3a RGB\u3002<\/p>\n<pre><code class=\"language-py\">import matplotlib.pyplot as plt\n\nimage_path = &#039;demo.png&#039;\n\nimage = plt.imread(image_path)\nplt.axis(&#039;off&#039;) # \u4e0d\u663e\u793a\u5750\u6807\u8f74\nplt.imshow(image)\nplt.show()<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706365655255.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 802px; --smush-placeholder-aspect-ratio: 802\/683;\" \/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"23_Pillow_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E7%94%A8_OpenCV_%E6%98%BE%E7%A4%BA\"><\/span>2.3 Pillow \u6253\u5f00\u56fe\u7247\u7528 OpenCV \u663e\u793a<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Pillow \u662f Python \u4e2d\u8f83\u4e3a\u5e38\u7528\u7684\u56fe\u50cf\u5e93\u3002<\/p>\n<pre><code class=\"language-py\">from PIL import Image\nimport cv2\nimport numpy as np\n\nimage_path = &#039;demo.png&#039;\n\npillow_image = Image.open(image_path)\nopencv_image = cv2.cvtColor(\n    np.array(pillow_image), # Pillow \u56fe\u50cf\u6570\u636e\u7ed3\u6784\u8f6c NumPy\n    cv2.COLOR_RGB2BGR # \u901a\u9053\u987a\u5e8f\u7531 RGB \u8f6c\u4e3a BGR\n)\ncv2.imshow(&#039;Pillow Image To OpenCV Image&#039;, opencv_image)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<h2><span class=\"ez-toc-section\" id=\"24_OpenCV_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E7%94%A8_Tkinter_%E6%98%BE%E7%A4%BA%EF%BC%88OpenCV_%E8%BD%AC_Pillow%EF%BC%89\"><\/span>2.4 OpenCV \u6253\u5f00\u56fe\u7247\u7528 Tkinter \u663e\u793a\uff08OpenCV \u8f6c Pillow\uff09<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Tkinter \u662f Python \u7684\u5b98\u65b9 GUI \u5e93\uff0cPillow \u7684\u56fe\u50cf\u6570\u636e\u652f\u6301\u76f4\u63a5\u5728 Tkinter \u4e2d\u663e\u793a\uff0c\u56e0\u6b64\u8fd9\u91cc\u628a OpenCV \u56fe\u50cf\u8f6c\u4e3a Pillow \u518d\u5230 Tkinter \u4e2d\u663e\u793a\u3002<\/p>\n<pre><code class=\"language-py\">import cv2\nimport tkinter as tk\nfrom PIL import Image, ImageTk\n\nimage_path = &#039;demo.png&#039;\n\nclass Application(tk.Frame):\n    def __init__(self, master):\n        super().__init__(master)\n        self.master = master\n\n    def interface(self):\n        global pillow_image # \u6ce8\u610f Tkinter \u663e\u793a\u7684\u56fe\u7247\u8981\u4f7f\u7528\u5168\u5c40\u53d8\u91cf\n\n        opencv_image = cv2.imread(image_path)\n        pillow_image = ImageTk.PhotoImage(\n            Image.fromarray(\n                cv2.cvtColor(\n                    opencv_image,\n                    cv2.COLOR_BGR2RGB\n                )\n            )\n        )\n\n        tk.Label(self.master, image=pillow_image).pack()\n\nif __name__ == &#039;__main__&#039;:\n    root = tk.Tk()\n    root.title(&#039;OpenCV \u6253\u5f00\u56fe\u7247\u5e76\u5728 Tkinter \u4e2d\u663e\u793a&#039;) # \u7a97\u53e3\u6807\u9898\n    app = Application(root)\n    app.interface()\n    root.mainloop()<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706366053285.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 537px; --smush-placeholder-aspect-ratio: 537\/800;\" \/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"25_Pillow_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E5%B9%B6%E4%BD%BF%E7%94%A8_Tkinter_%E6%98%BE%E7%A4%BA\"><\/span>2.5 Pillow \u6253\u5f00\u56fe\u7247\u5e76\u4f7f\u7528 Tkinter \u663e\u793a<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<pre><code class=\"language-py\">import tkinter as tk\nfrom PIL import Image, ImageTk\n\nimage_path = &#039;demo.png&#039;\n\nclass Application(tk.Frame):\n    def __init__(self, master):\n        super().__init__(master)\n        self.master = master\n\n    def interface(self):\n        global pillow_image # \u6ce8\u610f Tkinter \u663e\u793a\u7684\u56fe\u7247\u8981\u4f7f\u7528\u5168\u5c40\u53d8\u91cf\n\n        pillow_image = ImageTk.PhotoImage(\n            Image.open(image_path)\n        )\n\n        tk.Label(self.master, image=pillow_image).pack()\n\nif __name__ == &#039;__main__&#039;:\n    root = tk.Tk()\n    root.title(&#039;Pillow \u6253\u5f00\u56fe\u7247\u5e76\u5728 Tkinter \u4e2d\u663e\u793a&#039;)\n    app = Application(root)\n    app.interface()\n    root.mainloop()<\/code><\/pre>\n<h2><span class=\"ez-toc-section\" id=\"26_Matplotlib_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E7%94%A8_OpenCV_%E6%98%BE%E7%A4%BA\"><\/span>2.6 Matplotlib \u6253\u5f00\u56fe\u7247\u7528 OpenCV \u663e\u793a<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Matplotlib \u548c OpenCV \u90fd\u662f\u4f7f\u7528 NumPy \u6570\u7ec4\u4fdd\u5b58\u56fe\u50cf\u6570\u636e\uff0c\u4e24\u8005\u8f6c\u6362\u53ea\u9700\u8981\u4fee\u6539\u901a\u9053\u987a\u5e8f\u5373\u53ef\uff0c\u975e\u5e38\u65b9\u4fbf\u3002<\/p>\n<pre><code class=\"language-py\">import matplotlib.pyplot as plt\nimport cv2\n\nimage_path = &#039;demo.png&#039;\n\nmatplotlib_image = plt.imread(image_path)\nopencv_image = cv2.cvtColor(\n    matplotlib_image,\n    cv2.COLOR_RGB2BGR\n)\n\ncv2.imshow(\n    &#039;Matplotlib To OpenCV&#039;,\n    opencv_image    \n)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<h2><span class=\"ez-toc-section\" id=\"27_OpenCV_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E7%94%A8_Matplotlib_%E6%98%BE%E7%A4%BA\"><\/span>2.7 OpenCV \u6253\u5f00\u56fe\u7247\u7528 Matplotlib \u663e\u793a<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<pre><code class=\"language-py\">import matplotlib.pyplot as plt\nimport cv2\n\nimage_path = &#039;demo.png&#039;\n\nopencv_image = cv2.imread(image_path)\nmatplotlib_image = cv2.cvtColor(\n    opencv_image,\n    cv2.COLOR_RGB2BGR\n)\n\nplt.imshow(matplotlib_image)\nplt.axis(&#039;off&#039;)\nplt.show()<\/code><\/pre>\n<h2><span class=\"ez-toc-section\" id=\"28_Matplotlib_%E6%89%93%E5%BC%80%E5%9B%BE%E7%89%87%E7%94%A8_Tkinter_%E6%98%BE%E7%A4%BA\"><\/span>2.8 Matplotlib \u6253\u5f00\u56fe\u7247\u7528 Tkinter \u663e\u793a<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<pre><code class=\"language-py\">import matplotlib.pyplot as plt\nimport tkinter as tk\nfrom PIL import Image, ImageTk\n\nimage_path = &#039;demo.png&#039;\n\nclass Application(tk.Frame):\n    def __init__(self, master):\n        super().__init__(master)\n        self.master = master\n\n    def interface(self):\n        global pillow_image # \u6ce8\u610f Tkinter \u663e\u793a\u7684\u56fe\u7247\u8981\u4f7f\u7528\u5168\u5c40\u53d8\u91cf\n\n        matplotlib_image = plt.imread(image_path)\n        pillow_image = ImageTk.PhotoImage(\n            Image.fromarray(\n                (matplotlib_image * 255).astype(&#039;uint8&#039;) # \u628a float32 \u8f6c\u4e3a uint8\n            )\n        )\n\n        tk.Label(self.master, image=pillow_image).pack()\n\nif __name__ == &#039;__main__&#039;:\n    root = tk.Tk()\n    root.title(&#039;Matplotlib \u6253\u5f00\u56fe\u7247\u5e76\u5728 Tkinter \u4e2d\u663e\u793a&#039;) # \u7a97\u53e3\u6807\u9898\n    app = Application(root)\n    app.interface()\n    root.mainloop()<\/code><\/pre>\n<h1><span class=\"ez-toc-section\" id=\"3_%E5%9F%BA%E4%BA%8E_NumPy_%E6%95%B0%E7%BB%84%E7%9A%84%E5%9B%BE%E5%83%8F%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84%E6%93%8D%E4%BD%9C\"><\/span>3 \u57fa\u4e8e NumPy \u6570\u7ec4\u7684\u56fe\u50cf\u6570\u636e\u7ed3\u6784\u64cd\u4f5c<span class=\"ez-toc-section-end\"><\/span><\/h1>\n<p>OpenCV \u548c Matplotlib \u4e2d\u56fe\u50cf\u6570\u636e\u90fd\u662f\u4f7f\u7528 NumPy\uff0c\u8fd9\u91cc\u8bd5\u7740\u521b\u5efa\u4e00\u4e2a NumPy \u6570\u7ec4\u6765\u64cd\u4f5c\uff0c\u66f4\u597d\u7406\u89e3\u5176\u7ed3\u6784\u3002<\/p>\n<p>\u8fd9\u91cc\u521b\u5efa\u4e00\u4e2a 2&#215;2 \u5206\u8fa8\u7387\u7684\u56fe\u7247\uff0c4 \u4e2a\u70b9\u5206\u522b\u5b9a\u4e49\u4e3a\u9ed1\u8272RGB(0,0,0)\uff0c\u767d\u8272RGB(255,255,255)\uff0c\u7ea2\u8272RGB(255,0,0)\uff0c\u7d2b\u8272RGB(255,0,255)\uff0c\u5148\u7528 Matplotlib \u793a\u4f8b\uff0c\u901a\u9053\u987a\u5e8f\u5c31\u662f RGB<\/p>\n<pre><code class=\"language-py\">import matplotlib.pyplot as plt\nimport numpy as np\n\ndata = np.array([\n    [[0, 0, 0], [255, 255, 25]],\n    [[255, 0, 0], [255, 0, 255]]\n])\n\nprint(&#039;\u5f62\u72b6\uff1a&#039;, data.shape)\nplt.imshow(data)\nplt.show()<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706403062715.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 802px; --smush-placeholder-aspect-ratio: 802\/683;\" \/><br \/>\n\u5f62\u72b6\u662f 2&#215;2 \u5206\u8fa8\u7387\uff0c3 \u901a\u9053\uff08RGB)<br \/>\n<img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706403076991.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 157px; --smush-placeholder-aspect-ratio: 157\/47;\" \/><\/p>\n<p>\u5bf9\u8fd9\u79cd\u56fe\u50cf\u6570\u636e\u7ed3\u6784\u7684\u5207\u7247\u64cd\u4f5c\u683c\u5f0f\u5982\u4e0b<\/p>\n<pre><code class=\"language-py\">image[y1:y2:ys, x1:x2:xs, c1:c2:cs]<\/code><\/pre>\n<p>\u9017\u53f7\u5206\u9694\u7684\u4e09\u90e8\u5206\u5206\u522b\u662f\u64cd\u4f5c y \u8f74\u3001x \u8f74\u3001\u989c\u8272\u901a\u9053\uff0c\u6bcf\u90e8\u5206\u5192\u53f7\u5206\u9694\u7684 1 \u548c 2 \u5bf9\u5e94\u8d77\u59cb\u548c\u7ed3\u675f\uff0cs \u5bf9\u5e94\u6b65\u957f\uff0c\u53ef\u4ee5\u7701\u7565\u3002<\/p>\n<h2><span class=\"ez-toc-section\" id=\"31_%E9%A2%9C%E8%89%B2%E9%80%9A%E9%81%93%E9%A1%BA%E5%BA%8F%E8%BD%AC%E6%8D%A2\"><\/span>3.1 \u989c\u8272\u901a\u9053\u987a\u5e8f\u8f6c\u6362<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u524d\u9762 Matplotlib \u548c OpenCV \u56fe\u50cf\u6570\u636e\u4e92\u76f8\u8f6c\u6362\u662f\u4f7f\u7528\u7684 OpenCV \u7684 cvtColor \u51fd\u6570\uff0c\u8fd9\u91cc\u53ef\u4ee5\u5c1d\u8bd5\u57fa\u4e8e NumPy \u6570\u7ec4\u64cd\u4f5c\uff0c\u5c06 cs \u8bbe\u4e3a -1\uff0c\u5219\u4f1a\u9006\u5411\u901a\u9053\u987a\u5e8f\u3002<br \/>\nMatplotlib \u663e\u793a\u56fe\u50cf\u4f1a\u81ea\u52a8\u8c03\u6574\u6bd4\u4f8b\uff0c\u4f46\u662f OpenCV \u4f1a\u539f\u6bd4\u4f8b\u663e\u793a\uff0c\u6240\u4ee5\u8fd9\u91cc\u9700\u8981\u653e\u5927\u56fe\u50cf\u518d\u663e\u793a\u3002<\/p>\n<pre><code class=\"language-py\">import cv2\nimport numpy as np\n\ndata = np.array([\n    [[0, 0, 0], [255, 255, 25]],\n    [[255, 0, 0], [255, 0, 255]]\n], dtype=np.uint8)\n\nnew_data = data[:,:,::-1] # \u901a\u9053\u987a\u5e8f\u9006\u5411\nnew_data = cv2.resize(\n    new_data,\n    (255, 255), # \u653e\u5927\u540e\u7684\u5206\u8fa8\u7387\n    interpolation=cv2.INTER_NEAREST # \u6700\u8fd1\u90bb\u63d2\u503c\u6cd5\uff0c\u76f4\u63a5\u590d\u5236\u539f\u56fe\u50cf\u50cf\u7d20\uff0c\u4e0d\u8ba1\u7b97\u8854\u63a5\u8fb9\u7f18\n)\ncv2.imshow(&#039;my data&#039;, new_data)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706405790862.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 321px; --smush-placeholder-aspect-ratio: 321\/359;\" \/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"32_%E5%9B%BE%E5%83%8F%E9%83%A8%E5%88%86%E6%88%AA%E5%8F%96\"><\/span>3.2 \u56fe\u50cf\u90e8\u5206\u622a\u53d6<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<pre><code class=\"language-py\">import matplotlib.pyplot as plt\n\nimage_path = &#039;demo.png&#039;\n\nimg = plt.imread(image_path)\nplt.axis(&#039;off&#039;)\n\nroi = img[14:556, 219:633] # \u622a\u53d6 y \u53d6\u503c 14~556\uff0cx \u53d6\u503c\u5230 219~633 \u7684\u90e8\u5206\nplt.imshow(roi)\nplt.show()<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706407360917.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 802px; --smush-placeholder-aspect-ratio: 802\/683;\" \/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"33_%E9%A2%9C%E8%89%B2%E9%80%9A%E9%81%93%E5%88%86%E7%A6%BB\"><\/span>3.3 \u989c\u8272\u901a\u9053\u5206\u79bb<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3><span class=\"ez-toc-section\" id=\"331_OpenCV\"><\/span>3.3.1 OpenCV<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u4e0b\u9762\u7684\u793a\u4f8b\u4e2d\u4ece\u56fe\u7247\u6587\u4ef6\u8bfb\u53d6\uff0c\u7136\u540e\u5c06\u56fe\u50cf\u6570\u636e\u7684\u4e09\u8272\u901a\u9053\u5206\u79bb\uff0c\u53e6\u5916\u521b\u5efa\u4e00\u4e2a\u7b49\u5927\u5c0f\u7684\u7a7a\u6570\u636e\u901a\u9053\uff0c\u7136\u540e\u518d\u5c1d\u8bd5\u7528\u7a7a\u6570\u636e\u586b\u5145 G\u3001B \u901a\u9053\u548c\u5206\u79bb\u51fa\u6765\u7684 R \u901a\u9053\u5408\u5e76\u751f\u6210\u4e00\u4e2a\u65b0\u7684\u5f69\u8272\u56fe\u7247\uff0c\u65b0\u751f\u6210\u7684\u56fe\u7247\u4e2d\u7f3a\u5931\u4e86\u7eff\u8272\u548c\u84dd\u8272\u901a\u9053\u5219\u53d8\u4e3a\u4e86\u201c\u9ed1\u7ea2\u201d\u56fe\u7247\u3002<\/p>\n<pre><code class=\"language-py\">import cv2\nimport numpy as np\n\nimage_path = &#039;demo.png&#039;\n\nimage = cv2.imread(image_path)\nB = image[:, :, 0:1] # \u622a\u53d6 0 \u901a\u9053[0,1)\uff0c\u524d\u5f00\u540e\u95ed\uff0c\u5373\u84dd\u8272\nG = image[:, :, 1:2] # \u622a\u53d6 1 \u901a\u9053\uff0c\u7eff\u8272\nR = image[:, :, 2:3] # \u622a\u53d6 2 \u901a\u9053\uff0c\u7ea2\u8272\nZERO = np.zeros(B.shape, dtype=B.dtype) # \u521b\u5efa\u4e00\u4e2a\u7a7a\u6570\u636e\u7684\u901a\u9053\n\nR_image = cv2.merge([ZERO, ZERO, R])\ncv2.imshow(&#039;R image&#039;, R_image)\ncv2.waitKey(0)\ncv2.destroyAllWindows()<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706411763699.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 959px; --smush-placeholder-aspect-ratio: 959\/786;\" \/><\/p>\n<h3><span class=\"ez-toc-section\" id=\"332_Matplotlib\"><\/span>3.3.2 Matplotlib<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<pre><code class=\"language-py\">import matplotlib.pyplot as plt\nimport numpy as np\n\nimage_path = &#039;demo.png&#039;\n\nimage = plt.imread(image_path)\nR = image[:, :, 0] # \u76f4\u63a5\u622a\u53d6\u5355\u4e2a\u901a\u9053\uff0c\u6216\u8005 0:1 \u4e5f\u884c\nG = image[:, :, 1]\nB = image[:, :, 2]\nZERO = np.zeros(B.shape, dtype=R.dtype) # \u521b\u5efa\u4e00\u4e2a\u7a7a\u6570\u636e\u7684\u901a\u9053\n\nB_image = np.dstack((ZERO, ZERO, B))\nplt.imshow(B_image)\nplt.axis(&#039;off&#039;)\nplt.show()<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706413234230.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 802px; --smush-placeholder-aspect-ratio: 802\/683;\" \/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"34_%E6%B7%B1%E6%8B%B7%E8%B4%9D%E5%92%8C%E6%B5%85%E6%8B%B7%E8%B4%9D\"><\/span>3.4 \u6df1\u62f7\u8d1d\u548c\u6d45\u62f7\u8d1d<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u56fe\u50cf\u6570\u636e\u7684\u6df1\u62f7\u8d1d\u548c\u6d45\u62f7\u8d1d\uff0c\u5728\u57fa\u4e8e NumPy \u6570\u7ec4\u7684\u524d\u63d0\u4e0b\uff0c\u4e5f\u5c31\u662f NumPy \u6570\u7ec4\u7684\u6df1\u62f7\u8d1d\u548c\u6d45\u62f7\u8d1d\u3002\u76f4\u63a5\u7528\u7b49\u53f7\u8d4b\u503c\u5b9e\u9645\u5f97\u5230\u7684\u662f\u4e3a\u539f\u6570\u7ec4\u8d77\u7684\u4e00\u4e2a\u522b\u540d\uff0c\u901a\u8fc7\u539f\u6765\u7684\u6570\u7ec4\u540d\u548c\u65b0\u8d77\u7684\u540d\u5b57\u64cd\u4f5c\u7684\u90fd\u662f\u540c\u4e00\u5757\u5730\u5740\uff0c\u5b9e\u9645\u5c31\u662f\u6d45\u62f7\u8d1d\u3002\u4f7f\u7528 copy \u65b9\u6cd5\u62f7\u8d1d\u5219\u662f\u6df1\u62f7\u8d1d\uff0c\u6df1\u62f7\u8d1d\u4e0d\u662f\u521b\u5efa\u4e00\u4e2a\u522b\u540d\uff0c\u800c\u662f\u65b0\u5f00\u8f9f\u7a7a\u95f4\uff0c\u5e76\u590d\u5236\u539f\u6765\u6570\u7ec4\u7684\u6570\u636e\u5230\u65b0\u7a7a\u95f4\uff0c\u65b0\u65e7\u6570\u7ec4\u662f\u72ec\u7acb\u7684\u7a7a\u95f4\u3002<\/p>\n<pre><code class=\"language-py\">import numpy as np\n\narray = np.array([\n    [[0, 0, 255]]\n])\n\narray1 = array\narray2 = array.copy()\n\nprint(&#039;array \u5730\u5740\/\u662f\u5426\u53ea\u8bfb\uff1a&#039;, array.__array_interface__[&#039;data&#039;])\nprint(&#039;array1 \u5730\u5740\/\u662f\u5426\u53ea\u8bfb\uff1a&#039;, array1.__array_interface__[&#039;data&#039;])\nprint(&#039;array2 \u5730\u5740\/\u662f\u5426\u53ea\u8bfb\uff1a&#039;, array2.__array_interface__[&#039;data&#039;])<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706429427527.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 435px; --smush-placeholder-aspect-ratio: 435\/78;\" \/><\/p>\n<h2><span class=\"ez-toc-section\" id=\"35_%E8%B4%B4%E5%9B%BE\"><\/span>3.5 \u8d34\u56fe<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<pre><code class=\"language-py\">import matplotlib.pyplot as plt\n\nimage_path = &#039;demo.png&#039;\nsrc = plt.imread(image_path)\n\ncopy_image = src.copy() # \u6df1\u62f7\u8d1d\ncopy_image[628:810, 194:548] = [255, 255, 255] # x\uff1a194~548\u3002y\uff1a628~810 \u586b\u5145\u4e3a\u767d\u8272RGB(255,255,255)\ncopy_image[713:1017, 239:478] = src[104:408, 289:528] # \u622a\u53d6\u539f\u56fe\u4eba\u8138\u90e8\u5206 x\uff1a289~528\uff0cy\uff1a104~408\uff0c\u8d34\u5230\u62f7\u8d1d\u56fe\u50cf\u7684 x\uff1a239~478\uff0cy\uff1a713~1017\n\nplt.axis(&#039;off&#039;)\nplt.imshow(copy_image)\nplt.show()<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706431496872.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 802px; --smush-placeholder-aspect-ratio: 802\/683;\" \/><\/p>\n<h3><span class=\"ez-toc-section\" id=\"351_%E9%80%8F%E6%98%8E%E5%BA%A6%E9%80%9A%E9%81%93\"><\/span>3.5.1 \u900f\u660e\u5ea6\u901a\u9053<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u524d\u9762\u7684\u64cd\u4f5c\u90fd\u662f\u524d\u4e09\u4e2a\u57fa\u8272\u7684\u901a\u9053\uff0c\u6ca1\u6709\u6d89\u53ca\u7b2c 4 \u4e2a\u901a\u9053\u900f\u660e\u5ea6\uff0c\u4e0b\u9762\u8fd9\u5f20\u80e1\u5b50\u56fe\u7247\u5c31\u662f\u5177\u6709 4 \u901a\u9053\u7684\u56fe\u7247\uff0c\u53ef\u4ee5\u53f3\u952e\u53e6\u5b58\u4e3a\u7528\u4e8e\u6d4b\u8bd5\u3002<br \/>\n<img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2022\/04\/huzi-1.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 640px; --smush-placeholder-aspect-ratio: 640\/320;\" \/><\/p>\n<pre><code class=\"language-py\">import matplotlib.pyplot as plt\nimport numpy as np\n\nimage_path = &#039;demo.png&#039;\nbeard_path = &#039;demo1.png&#039; # \u80e1\u5b50\u56fe\u7247\u6587\u4ef6\n\nsrc = plt.imread(image_path)\nbeard = plt.imread(beard_path)\n\n# \u4e3a\u539f\u56fe\u6dfb\u52a0 alpha \u901a\u9053\uff08\u900f\u660e\u5ea6\uff09\nimage_with_alpha = np.dstack([\n    src,\n    np.ones((src.shape[0], src.shape[1]), dtype=src.dtype)\n])\n\nbeard_h, beard_w = beard.shape[:2] # \u83b7\u53d6\u80e1\u5b50\u56fe\u7247\u7684\u5c3a\u5bf8\nmask_boolean = beard[:, :, 3] == 1 # alpha \u503c\u4e3a 1 \u7684\u50cf\u7d20\u70b9\u5373\u4e3a\u5b8c\u5168\u4e0d\u900f\u660e\u7684\u503c\nimage_with_alpha[523:523+beard_h, 94:94+beard_w][mask_boolean] = beard[mask_boolean] # \u5c06\u80e1\u5b50\u4e0d\u900f\u660e\u7684\u90e8\u5206\u50cf\u7d20\u503c\u5d4c\u5165\u56fe\u50cf\u4e2d\n\nplt.axis(&#039;off&#039;)\nplt.imshow(image_with_alpha)\nplt.show()<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1706444271976.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 802px; --smush-placeholder-aspect-ratio: 802\/683;\" \/><\/p>\n<p>\u7ed3\u5408\u900f\u660e\u5ea6\u4fe1\u606f\u540e\uff0c\u5c31\u4e0d\u4f1a\u5b8c\u5168\u7167\u642c\u628a\u8d34\u7684\u56fe\u7247\u62ff\u4e0a\u53bb\u6321\u4f4f\uff0c\u4e0d\u900f\u660e\u7684\u90e8\u5206\u5c31\u663e\u793a\u539f\u56fe\u7684\u5185\u5bb9\u3002\u8fd9\u91cc\u4f7f\u7528 Matplotlib \u8bfb\u53d6\u7684\u56fe\u7247\u6570\u636e\u7c7b\u578b\u4e3a float32\uff08OpenCV \u662f uint8\uff0c\u4e3a 0-255 \u7684\u6574\u6570\uff09\uff0c\u6bcf\u4e2a\u901a\u9053\u7684\u50cf\u7d20\u70b9\u6570\u636e\u4e3a 0-1 \u7684\u5c0f\u6570\uff0calpha \u901a\u9053\u4e3a 1 \u5c31\u662f\u5b8c\u5168\u5448\u73b0 RGB \u7684\u503c\uff0calpha \u4e3a 0 \u5c31\u662f\u5b8c\u5168\u4e0d\u5448\u73b0 RGB \u503c\uff0c\u4e2d\u95f4\u5c31\u662f\u8fc7\u6e21\u3002<br \/>\n\u4e0a\u9762\u5199\u7684\u4f8b\u5b50\u5176\u5b9e\u5f88\u6709\u5c40\u9650\u6027\uff0c\u7528\u7684\u80e1\u5b50\u56fe\u7247\u6bd4\u8f83\u7279\u6b8a\uff0c\u900f\u660e\u5ea6\u7684\u503c\u662f\u6781\u5316\u7684\uff0c\u8981\u4e48\u5b8c\u5168\u900f\u660e\uff0c\u8981\u4e48\u5b8c\u5168\u4e0d\u900f\u660e\uff0c\u6240\u4ee5\u53ef\u4ee5\u91c7\u7528\u4e0a\u9762\u7684\u65b9\u6cd5\u5224\u65ad\u4e0d\u900f\u660e\u7684\u5c31\u76f4\u63a5\u590d\u5236\u66ff\u6362\u539f\u56fe\u7684\u90e8\u5206\uff0c\u4f46\u662f\u5982\u679c\u900f\u660e\u5ea6\u662f 0-1 \u4e4b\u95f4\u7684\u4e0d\u5b8c\u5168\u900f\u660e\uff0c\u4e5f\u4e0d\u662f\u5b8c\u5168\u4e0d\u900f\u660e\uff0c\u5c31\u4e0d\u80fd\u7528\u8fd9\u79cd\u65b9\u6cd5\u5904\u7406\u3002\u4e0d\u5b8c\u5168\u900f\u660e\u7684\u60c5\u51b5\u4e0b\uff0c\u8d34\u4e0a\u53bb\u7684\u56fe\u4e0d\u80fd\u5b8c\u5168\u906e\u6321\u539f\u56fe\uff0c\u4e5f\u5c31\u662f\u539f\u56fe\u548c\u8d34\u4e0a\u53bb\u7684\u56fe\u7684\u50cf\u7d20\u503c\u4fe1\u606f\u90fd\u8981\u663e\u793a\u51fa\u6765\u3002<\/p>\n<p>\u8981\u89e3\u51b3\u4e0a\u9762\u63d0\u5230\u7684\u95ee\u9898\u5c31\u5f97\u4ece\u900f\u660e\u5ea6\u672c\u8eab\u7684\u6027\u8d28\u7740\u624b\uff0c\u5148\u53ea\u8003\u8651\u4e00\u4e2a\u50cf\u7d20\u70b9\u7684\u60c5\u51b5\uff0c\u5047\u5982\u539f\u56fe\u7684\u50cf\u7d20\u70b9\u503c\u4e3a[1, 0, 0, 1]\uff0c\u5c31\u662f\u5b8c\u5168\u663e\u793a\u7ea2\u8272\u7684\u70b9\uff0c\u7136\u540e\u6211\u8981\u5c06\u4e00\u4e2a [0, 0, 1, 0.6] \u7684\u70b9\u8d34\u4e0a\u53bb\uff0c\u8fd9\u4e2a\u70b9\u672c\u8eab\u662f\u7eaf\u84dd\u8272\uff0c\u4f46\u662f\u900f\u660e\u5ea6\u4e3a 0.6\uff0c\u5373\u53ea\u5448\u73b0\u84dd\u8272\u7684 60%\uff0c\u90a3\u4e48\u5269\u4e0b\u7684 40% \u5c31\u663e\u793a\u80cc\u666f\uff08\u5373\u539f\u56fe\uff09\uff0c\u90a3\u4e48\u6700\u7ec8\u663e\u793a\u7684\u5c31\u5e94\u8be5\u662f<code class=\"katex-inline\">[1 \\times 0.4 + 0 \\times 0.6, 0 \\times 0.4 + 0 \\times 0.6, 0 \\times 0.4 + 1 \\times 0.6, 1 \\times 0.4 + 0.6 \\times 0.6]<\/code>\uff0c\u5c31\u6709\u4e0b\u9762\u7684\u4ee3\u7801\uff1a<\/p>\n<pre><code class=\"language-py\">import matplotlib.pyplot as plt\nimport numpy as np\n\nimage_path = &#039;demo.png&#039;\nbeard_path = &#039;demo1.png&#039; # \u80e1\u5b50\u56fe\u7247\u6587\u4ef6\n\nsrc = plt.imread(image_path)\nbeard = plt.imread(beard_path)\n\n# \u4e3a\u539f\u56fe\u6dfb\u52a0 alpha \u901a\u9053\uff08\u900f\u660e\u5ea6\uff09\nimage_with_alpha = np.dstack([\n    src,\n    np.ones((src.shape[0], src.shape[1]), dtype=src.dtype)\n])\n\nbeard_h, beard_w = beard.shape[:2] # \u83b7\u53d6\u80e1\u5b50\u56fe\u7247\u7684\u5c3a\u5bf8\n\nbeard_alpha1 = beard[:, :, 3] # \u53d6\u51fa\u80e1\u5b50\u56fe\u7247\u7684\u900f\u660e\u5ea6\nbeard_alpha2 = 1 - beard_alpha1 # \u8ba1\u7b97\u51fa\u539f\u56fe\u88ab\u8d34\u56fe\u4f4d\u7f6e\u5e94\u8be5\u5177\u6709\u7684\u900f\u660e\u5ea6\nfor c in range(4):\n    image_with_alpha[523:523+beard_h, 94:94+beard_w, c] = beard_alpha2 * image_with_alpha[523:523+beard_h, 94:94+beard_w, c] + beard_alpha1 * beard[:, :, c]\nplt.axis(&#039;off&#039;)\nplt.imshow(image_with_alpha)\nplt.show()<\/code><\/pre>\n<p>\u8fd9\u91cc\u6211\u4e5f\u4e0d\u80fd\u4fdd\u8bc1\u6211\u7684\u601d\u8def\u662f\u5bf9\u7684\uff0c\u53ea\u662f\u4f7f\u7528\u80e1\u5b50\u56fe\u7247\u9a8c\u8bc1\u6ca1\u95ee\u9898\u3002<\/p>\n<h2><span class=\"ez-toc-section\" id=\"36_%E8%AF%BB%E5%9B%BE%E9%BB%98%E8%AE%A4%E6%95%B0%E6%8D%AE%E7%B1%BB%E5%9E%8B\"><\/span>3.6 \u8bfb\u56fe\u9ed8\u8ba4\u6570\u636e\u7c7b\u578b<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3><span class=\"ez-toc-section\" id=\"361_OpenCV\"><\/span>3.6.1 OpenCV<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<pre><code class=\"language-py\">import cv2\n\nimg = cv2.imread(&#039;test.png&#039;)\nprint(img.dtype)<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1709993091884.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 301px; --smush-placeholder-aspect-ratio: 301\/153;\" \/><\/p>\n<p>OpenCV \u9ed8\u8ba4\u7684\u6570\u636e\u7c7b\u578b\u4e3a uint8\uff0c\u5373\u6bcf\u4e2a\u50cf\u7d20\u70b9\u7684\u53d6\u503c\u90fd\u662f 0-255<\/p>\n<h3><span class=\"ez-toc-section\" id=\"362_Matplotlib\"><\/span>3.6.2 Matplotlib<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<pre><code class=\"language-py\">import matplotlib.pyplot as plt\n\nimg = plt.imread(&#039;test.png&#039;)\nprint(img.dtype)<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1709993274825.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 309px; --smush-placeholder-aspect-ratio: 309\/151;\" \/><\/p>\n<p>Matplotlib \u9ed8\u8ba4\u7684\u6570\u636e\u7c7b\u578b\u4e3a float32\uff0c\u5373\u6bcf\u4e2a\u50cf\u7d20\u70b9\u7684\u53d6\u503c\u662f 0-1 \u7684\u5c0f\u6570<\/p>\n<h3><span class=\"ez-toc-section\" id=\"363_Pillow\"><\/span>3.6.3 Pillow<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<pre><code class=\"language-py\">from PIL import Image\nimport numpy as np\n\nimg = Image.open(&#039;test.png&#039;)\nprint(np.array(img).dtype)<\/code><\/pre>\n<p><img decoding=\"async\" data-src=\"https:\/\/blog.iyatt.com\/wp-content\/uploads\/2024\/01\/image-1709993669088.png\" alt=\"file\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" class=\"lazyload\" style=\"--smush-placeholder-width: 301px; --smush-placeholder-aspect-ratio: 301\/159;\" \/><br \/>\nPillow \u4e0d\u662f\u4f7f\u7528\u7684 NumPy \u6570\u7ec4\u5b58\u50a8\u56fe\u50cf\u6570\u636e\uff0c\u8f6c\u5316\u4e3a NumPy \u65f6\uff0cNumPy \u4f1a\u6839\u636e\u6570\u636e\u8fdb\u884c\u63a8\u65ad\uff0c\u53ef\u4ee5\u770b\u5230 Pillow \u9ed8\u8ba4\u5b58\u50a8\u7684\u56fe\u50cf\u6570\u636e\u7c7b\u578b\u662f\u5951\u5408 uint8 \u7684<\/p>\n","protected":false},"excerpt":{"rendered":"<p>1 \u6d4b\u8bd5\u73af\u5883 Python 3.12.1 numpy 1.26.3 opencv-python 4.9.0.8 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"zakra_page_container_layout":"customizer","zakra_page_sidebar_layout":"customizer","zakra_remove_content_margin":false,"zakra_sidebar":"customizer","zakra_transparent_header":"customizer","zakra_logo":0,"zakra_main_header_style":"default","zakra_menu_item_color":"","zakra_menu_item_hover_color":"","zakra_menu_item_active_color":"","zakra_menu_active_style":"","zakra_page_header":true,"_lmt_disableupdate":"no","_lmt_disable":"no","footnotes":""},"categories":[1,592],"tags":[],"class_list":["post-13222","post","type-post","status-publish","format-standard","hentry","category-all","category-python"],"modified_by":"IYATT-yx","_links":{"self":[{"href":"https:\/\/blog.iyatt.com\/index.php?rest_route=\/wp\/v2\/posts\/13222","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.iyatt.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.iyatt.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.iyatt.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.iyatt.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=13222"}],"version-history":[{"count":0,"href":"https:\/\/blog.iyatt.com\/index.php?rest_route=\/wp\/v2\/posts\/13222\/revisions"}],"wp:attachment":[{"href":"https:\/\/blog.iyatt.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=13222"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.iyatt.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=13222"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.iyatt.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=13222"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}