{"id":14121,"date":"2024-01-04T04:25:11","date_gmt":"2024-01-04T00:55:11","guid":{"rendered":"https:\/\/rasanegar.com\/blog\/retinanet-object-detection-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-pytorch-%d9%88-torchvision\/"},"modified":"2024-01-04T04:25:11","modified_gmt":"2024-01-04T00:55:11","slug":"retinanet-object-detection-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-pytorch-%d9%88-torchvision","status":"publish","type":"post","link":"https:\/\/rasanegaar.com\/blog\/retinanet-object-detection-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-pytorch-%d9%88-torchvision\/","title":{"rendered":"RetinaNet Object Detection \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 PyTorch \u0648 Torchvision"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_85 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\"><p class=\"ez-toc-title\" style=\"cursor:inherit\">\u0633\u0631\u0641\u0635\u0644\u0647\u0627\u06cc \u0645\u0637\u0644\u0628<\/p>\n<\/div><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/rasanegaar.com\/blog\/retinanet-object-detection-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-pytorch-%d9%88-torchvision\/#%d9%85%d8%b9%d8%b1%d9%81%db%8c\" >\u0645\u0639\u0631\u0641\u06cc<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/rasanegaar.com\/blog\/retinanet-object-detection-%d8%af%d8%b1-%d9%be%d8%a7%db%8c%d8%aa%d9%88%d9%86-%d8%a8%d8%a7-pytorch-%d9%88-torchvision\/#%d8%aa%d8%b4%d8%ae%db%8c%d8%b5_%d8%a7%d8%b4%db%8c%d8%a7_%d8%a8%d8%a7_pytorchtorchvisions_retinanet\" >\u062a\u0634\u062e\u06cc\u0635 \u0627\u0634\u06cc\u0627 \u0628\u0627 PyTorch\/TorchVision&#8217;s RetinaNet<\/a><\/li><\/ul><\/nav><\/div>\n<span class=\"span-reading-time rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">\u0632\u0645\u0627\u0646 \u0644\u0627\u0632\u0645 \u0628\u0631\u0627\u06cc \u0645\u0637\u0627\u0644\u0639\u0647: <\/span> <span class=\"rt-time\"> 3<\/span> <span class=\"rt-label rt-postfix\">\u062f\u0642\u06cc\u0642\u0647<\/span><\/span><p> <br \/>\n<\/p>\n<div><noscript><\/noscript><\/p>\n<h2 id=\"introduction\"><span class=\"ez-toc-section\" id=\"%d9%85%d8%b9%d8%b1%d9%81%db%8c\"><\/span>\u0645\u0639\u0631\u0641\u06cc<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u062a\u0634\u062e\u06cc\u0635 \u0627\u0634\u06cc\u0627 \u0645\u06cc\u062f\u0627\u0646 \u0628\u0632\u0631\u06af\u06cc \u062f\u0631 \u0628\u06cc\u0646\u0627\u06cc\u06cc \u06a9\u0627\u0645\u067e\u06cc\u0648\u062a\u0631\u06cc \u0627\u0633\u062a \u0648 \u06cc\u06a9\u06cc \u0627\u0632 \u0645\u0647\u0645\u200c\u062a\u0631\u06cc\u0646 \u06a9\u0627\u0631\u0628\u0631\u062f\u0647\u0627\u06cc \u0628\u06cc\u0646\u0627\u06cc\u06cc \u06a9\u0627\u0645\u067e\u06cc\u0648\u062a\u0631 \u062f\u0631 \u0637\u0628\u06cc\u0639\u062a \u0627\u0633\u062a.  \u0627\u0632 \u06cc\u06a9 \u0637\u0631\u0641\u060c \u0645\u06cc\u200c\u062a\u0648\u0627\u0646 \u0627\u0632 \u0622\u0646 \u0628\u0631\u0627\u06cc \u0633\u0627\u062e\u062a \u0633\u06cc\u0633\u062a\u0645\u200c\u0647\u0627\u06cc \u0645\u0633\u062a\u0642\u0644\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f \u06a9\u0647 \u0639\u0648\u0627\u0645\u0644 \u0631\u0627 \u062f\u0631 \u0645\u062d\u06cc\u0637\u200c\u0647\u0627 \u0647\u062f\u0627\u06cc\u062a \u0645\u06cc\u200c\u06a9\u0646\u0646\u062f &#8211; \u0686\u0647 \u0631\u0648\u0628\u0627\u062a\u200c\u0647\u0627\u06cc\u06cc \u06a9\u0647 \u0648\u0638\u0627\u06cc\u0641 \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u0645\u06cc\u200c\u062f\u0647\u0646\u062f \u06cc\u0627 \u0645\u0627\u0634\u06cc\u0646\u200c\u0647\u0627\u06cc \u062e\u0648\u062f\u0631\u0627\u0646\u060c \u0627\u0645\u0627 \u0627\u06cc\u0646 \u0646\u06cc\u0627\u0632 \u0628\u0647 \u062a\u0642\u0627\u0637\u0639 \u0628\u0627 \u0632\u0645\u06cc\u0646\u0647\u200c\u0647\u0627\u06cc \u062f\u06cc\u06af\u0631 \u062f\u0627\u0631\u062f.  \u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u062a\u0634\u062e\u06cc\u0635 \u0646\u0627\u0647\u0646\u062c\u0627\u0631\u06cc (\u0645\u0627\u0646\u0646\u062f \u0645\u062d\u0635\u0648\u0644\u0627\u062a \u0645\u0639\u06cc\u0648\u0628 \u0631\u0648\u06cc \u06cc\u06a9 \u062e\u0637)\u060c \u0645\u06a9\u0627\u0646 \u06cc\u0627\u0628\u06cc \u0627\u0634\u06cc\u0627\u0621 \u062f\u0631\u0648\u0646 \u062a\u0635\u0627\u0648\u06cc\u0631\u060c \u062a\u0634\u062e\u06cc\u0635 \u0686\u0647\u0631\u0647 \u0648 \u06a9\u0627\u0631\u0628\u0631\u062f\u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641 \u062f\u06cc\u06af\u0631 \u062a\u0634\u062e\u06cc\u0635 \u0627\u0634\u06cc\u0627 \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0628\u062f\u0648\u0646 \u062a\u0644\u0627\u0642\u06cc \u0641\u06cc\u0644\u062f\u0647\u0627\u06cc \u062f\u06cc\u06af\u0631 \u0627\u0646\u062c\u0627\u0645 \u062f\u0627\u062f.<\/p>\n<p>\u062a\u0634\u062e\u06cc\u0635 \u0627\u0634\u06cc\u0627 \u0628\u0647 \u0627\u0646\u062f\u0627\u0632\u0647 \u0637\u0628\u0642\u0647\u200c\u0628\u0646\u062f\u06cc \u062a\u0635\u0648\u06cc\u0631 \u0627\u0633\u062a\u0627\u0646\u062f\u0627\u0631\u062f \u0646\u06cc\u0633\u062a\u060c \u0639\u0645\u062f\u062a\u0627\u064b \u0628\u0647 \u0627\u06cc\u0646 \u062f\u0644\u06cc\u0644 \u06a9\u0647 \u0628\u06cc\u0634\u062a\u0631 \u067e\u06cc\u0634\u0631\u0641\u062a\u200c\u0647\u0627\u06cc \u062c\u062f\u06cc\u062f \u0628\u0647\u200c\u062c\u0627\u06cc \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647\u200c\u0647\u0627 \u0648 \u0686\u0627\u0631\u0686\u0648\u0628\u200c\u0647\u0627\u06cc \u0628\u0632\u0631\u06af\u060c \u0645\u0639\u0645\u0648\u0644\u0627\u064b \u062a\u0648\u0633\u0637 \u0645\u062d\u0642\u0642\u0627\u0646\u060c \u0646\u06af\u0647\u062f\u0627\u0631\u06cc\u200c\u06a9\u0646\u0646\u062f\u06af\u0627\u0646 \u0648 \u062a\u0648\u0633\u0639\u0647\u200c\u062f\u0647\u0646\u062f\u06af\u0627\u0646 \u0645\u0646\u0641\u0631\u062f \u0627\u0646\u062c\u0627\u0645 \u0645\u06cc\u200c\u0634\u0648\u062f.  \u0628\u0633\u062a\u0647\u200c\u0628\u0646\u062f\u06cc \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a\u200c\u0647\u0627\u06cc \u06a9\u0627\u0631\u0628\u0631\u062f\u06cc \u0636\u0631\u0648\u0631\u06cc \u062f\u0631 \u0686\u0627\u0631\u0686\u0648\u0628\u06cc \u0645\u0627\u0646\u0646\u062f TensorFlow \u06cc\u0627 PyTorch \u0648 \u062d\u0641\u0638 \u062f\u0633\u062a\u0648\u0631\u0627\u0644\u0639\u0645\u0644\u200c\u0647\u0627\u06cc API \u06a9\u0647 \u062a\u0627\u06a9\u0646\u0648\u0646 \u062a\u0648\u0633\u0639\u0647 \u0631\u0627 \u0647\u062f\u0627\u06cc\u062a \u06a9\u0631\u062f\u0647\u200c\u0627\u0646\u062f\u060c \u062f\u0634\u0648\u0627\u0631 \u0627\u0633\u062a.<\/p>\n<p>\u0627\u06cc\u0646 \u0627\u0645\u0631 \u062a\u0634\u062e\u06cc\u0635 \u0627\u0634\u06cc\u0627\u0621 \u0631\u0627 \u062a\u0627 \u062d\u062f\u0648\u062f\u06cc \u067e\u06cc\u0686\u06cc\u062f\u0647\u200c\u062a\u0631\u060c \u0645\u0639\u0645\u0648\u0644\u0627\u064b \u067e\u0631\u0645\u062e\u0627\u0637\u0628\u200c\u062a\u0631 (\u0627\u0645\u0627 \u0646\u0647 \u0647\u0645\u06cc\u0634\u0647) \u0648 \u06a9\u0645\u062a\u0631 \u0627\u0632 \u0637\u0628\u0642\u0647\u200c\u0628\u0646\u062f\u06cc \u062a\u0635\u0648\u06cc\u0631 \u0645\u06cc\u200c\u0633\u0627\u0632\u062f.  \u06cc\u06a9\u06cc \u0627\u0632 \u0645\u0647\u0645\u062a\u0631\u06cc\u0646 \u0645\u0632\u0627\u06cc\u0627\u06cc \u062d\u0636\u0648\u0631 \u062f\u0631 \u06cc\u06a9 \u0627\u06a9\u0648\u0633\u06cc\u0633\u062a\u0645 \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0631\u0627\u0647\u06cc \u0628\u0631\u0627\u06cc \u062c\u0633\u062a\u062c\u0648 \u0646\u06a9\u0631\u062f\u0646 \u0627\u0637\u0644\u0627\u0639\u0627\u062a \u0645\u0641\u06cc\u062f \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u0645\u06cc \u062f\u0647\u062f. \u0631\u0648\u06cc \u0634\u06cc\u0648\u0647 \u0647\u0627\u060c \u0627\u0628\u0632\u0627\u0631\u0647\u0627 \u0648 \u0631\u0648\u06cc\u06a9\u0631\u062f\u0647\u0627\u06cc \u062e\u0648\u0628 \u0628\u0631\u0627\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647.  \u0628\u0627 \u062a\u0634\u062e\u06cc\u0635 \u0634\u06cc &#8211; \u0628\u06cc\u0634\u062a\u0631 \u0622\u0646\u0647\u0627 \u0628\u0627\u06cc\u062f \u062a\u062d\u0642\u06cc\u0642\u0627\u062a \u0628\u06cc\u0634\u062a\u0631\u06cc \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u0646\u062f \u0631\u0648\u06cc \u0686\u0634\u0645 \u0627\u0646\u062f\u0627\u0632 \u0645\u06cc\u062f\u0627\u0646 \u0631\u0627 \u0628\u0647 \u062e\u0648\u0628\u06cc \u062f\u0631 \u062f\u0633\u062a \u0628\u06af\u06cc\u0631\u06cc\u062f.<\/p>\n<h2 id=\"objectdetectionwithpytorchtorchvisionsretinanet\"><span class=\"ez-toc-section\" id=\"%d8%aa%d8%b4%d8%ae%db%8c%d8%b5_%d8%a7%d8%b4%db%8c%d8%a7_%d8%a8%d8%a7_pytorchtorchvisions_retinanet\"><\/span>\u062a\u0634\u062e\u06cc\u0635 \u0627\u0634\u06cc\u0627 \u0628\u0627 PyTorch\/TorchVision&#8217;s RetinaNet<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><code>torchvision<\/code>  \u067e\u0631\u0648\u0698\u0647 \u0686\u0634\u0645 \u0627\u0646\u062f\u0627\u0632 \u0631\u0627\u06cc\u0627\u0646\u0647 \u0627\u06cc PyTorch \u0627\u0633\u062a \u0648 \u0628\u0627 \u0627\u0631\u0627\u0626\u0647 \u0627\u0633\u06a9\u0631\u06cc\u067e\u062a \u0647\u0627\u06cc \u062a\u0628\u062f\u06cc\u0644 \u0648 \u062a\u0642\u0648\u06cc\u062a\u060c \u06cc\u06a9 \u0628\u0627\u063a \u0648\u062d\u0634 \u0645\u062f\u0644 \u0628\u0627 \u0648\u0632\u0646 \u0647\u0627\u060c \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0648 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u0627\u0632 \u067e\u06cc\u0634 \u0622\u0645\u0648\u0632\u0634 \u062f\u06cc\u062f\u0647 \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0628\u0631\u0627\u06cc \u06cc\u06a9 \u067e\u0632\u0634\u06a9 \u0645\u0641\u06cc\u062f \u0628\u0627\u0634\u062f\u060c \u062a\u0648\u0633\u0639\u0647 \u0645\u062f\u0644 \u0647\u0627\u06cc CV \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 PyTorch \u0631\u0627 \u0622\u0633\u0627\u0646 \u062a\u0631 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n<p>\u062f\u0631 \u062d\u0627\u0644\u06cc \u06a9\u0647 \u0647\u0646\u0648\u0632 \u062f\u0631 \u0646\u0633\u062e\u0647 \u0628\u062a\u0627 \u0648 \u0628\u0633\u06cc\u0627\u0631 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u0627\u0633\u062a &#8211; <code>torchvision<\/code> \u06cc\u06a9 API \u0646\u0633\u0628\u062a\u0627\u064b \u0633\u0627\u062f\u0647 Object Detection \u0631\u0627 \u0628\u0627 \u0686\u0646\u062f \u0645\u062f\u0644 \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc \u062f\u0647\u062f:<\/p>\n<ul>\n<li>R-CNN \u0633\u0631\u06cc\u0639\u062a\u0631<\/li>\n<li>\u0631\u062a\u06cc\u0646\u0627 \u0646\u062a<\/li>\n<li>FCOS (RetinaNet \u06a9\u0627\u0645\u0644\u0627 \u06a9\u0627\u0646\u0648\u0644\u0648\u0634\u0646\u0627\u0644)<\/li>\n<li>SSD (VGG16 backbone&#8230; ykes)<\/li>\n<li>SSDLite (\u0633\u062a\u0648\u0646 \u0627\u0635\u0644\u06cc MobileNetV3)<\/li>\n<\/ul>\n<p>\u062f\u0631 \u062d\u0627\u0644\u06cc \u06a9\u0647 API \u0628\u0647 \u0627\u0646\u062f\u0627\u0632\u0647 \u0628\u0631\u062e\u06cc \u062f\u06cc\u06af\u0631 \u0627\u0632 API \u0647\u0627\u06cc \u0634\u062e\u0635 \u062b\u0627\u0644\u062b \u0635\u06cc\u0642\u0644\u06cc \u06cc\u0627 \u0633\u0627\u062f\u0647 \u0646\u06cc\u0633\u062a\u060c \u0646\u0642\u0637\u0647 \u0634\u0631\u0648\u0639 \u0628\u0633\u06cc\u0627\u0631 \u0645\u0646\u0627\u0633\u0628\u06cc \u0628\u0631\u0627\u06cc \u06a9\u0633\u0627\u0646\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0647\u0646\u0648\u0632 \u0627\u0645\u0646\u06cc\u062a \u0628\u0648\u062f\u0646 \u062f\u0631 \u0627\u06a9\u0648\u0633\u06cc\u0633\u062a\u0645\u06cc \u0631\u0627 \u06a9\u0647 \u0628\u0627 \u0622\u0646 \u0622\u0634\u0646\u0627 \u0647\u0633\u062a\u0646\u062f \u062a\u0631\u062c\u06cc\u062d \u0645\u06cc \u062f\u0647\u0646\u062f.  \u0642\u0628\u0644 \u0627\u0632 \u0631\u0641\u062a\u0646 \u0628\u0647 \u062c\u0644\u0648\u060c \u0645\u0637\u0645\u0626\u0646 \u0634\u0648\u06cc\u062f \u06a9\u0647 PyTorch \u0648 Torchvision \u0631\u0627 \u0646\u0635\u0628 \u06a9\u0631\u062f\u0647 \u0627\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-meta\">$<\/span><span class=\"bash\"> pip install torch torchvision<\/span>\n<\/code><\/pre>\n<p>\u0627\u062c\u0627\u0632\u0647 \u062f\u0647\u06cc\u062f \u0628\u0631\u062e\u06cc \u0627\u0632 \u062a\u0648\u0627\u0628\u0639 \u0627\u0628\u0632\u0627\u0631\u060c \u0645\u0627\u0646\u0646\u062f <code>read_image()<\/code>\u060c <code>draw_bounding_boxes()<\/code> \u0648 <code>to_pil_image()<\/code> \u0628\u0631\u0627\u06cc \u0633\u0647\u0648\u0644\u062a \u062f\u0631 \u062e\u0648\u0627\u0646\u062f\u0646\u060c \u0646\u0642\u0627\u0634\u06cc \u06a9\u0646\u06cc\u062f \u0631\u0648\u06cc \u0648 \u062e\u0631\u0648\u062c\u06cc \u062a\u0635\u0627\u0648\u06cc\u0631 \u0648 \u0628\u0647 \u062f\u0646\u0628\u0627\u0644 \u0622\u0646 \u0648\u0627\u0631\u062f \u06a9\u0631\u062f\u0646 RetinaNet \u0648 \u0648\u0632\u0646\u0647 \u0647\u0627\u06cc \u0627\u0632 \u067e\u06cc\u0634 \u0622\u0645\u0648\u0632\u0634 \u062f\u0627\u062f\u0647 \u0634\u062f\u0647 \u0622\u0646 (MS COCO):<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> torchvision.io.image <span class=\"hljs-keyword\">import<\/span> read_image\n<span class=\"hljs-keyword\">from<\/span> torchvision.utils <span class=\"hljs-keyword\">import<\/span> draw_bounding_boxes\n<span class=\"hljs-keyword\">from<\/span> torchvision.transforms.functional <span class=\"hljs-keyword\">import<\/span> to_pil_image\n<span class=\"hljs-keyword\">from<\/span> torchvision.models.detection <span class=\"hljs-keyword\">import<\/span> retinanet_resnet50_fpn_v2, RetinaNet_ResNet50_FPN_V2_Weights\n\n<span class=\"hljs-keyword\">import<\/span> matplotlib.pyplot <span class=\"hljs-keyword\">as<\/span> plt\n<\/code><\/pre>\n<p>RetinaNet \u0627\u0632 \u06cc\u06a9 \u0633\u062a\u0648\u0646 \u0641\u0642\u0631\u0627\u062a ResNet50 \u0648 \u06cc\u06a9 \u0634\u0628\u06a9\u0647 \u0647\u0631\u0645\u06cc \u0648\u06cc\u0698\u06af\u06cc (FPN) \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u062f. \u0631\u0648\u06cc \u0628\u0627\u0644\u0627\u06cc \u0622\u0646  \u062f\u0631 \u062d\u0627\u0644\u06cc \u06a9\u0647 \u0646\u0627\u0645 \u06a9\u0644\u0627\u0633 \u067e\u0631\u0645\u062e\u0627\u0637\u0628 \u0627\u0633\u062a\u060c \u0646\u0634\u0627\u0646 \u062f\u0647\u0646\u062f\u0647 \u0645\u0639\u0645\u0627\u0631\u06cc \u0627\u0633\u062a.  \u0628\u06cc\u0627\u06cc\u06cc\u062f \u06cc\u06a9 \u062a\u0635\u0648\u06cc\u0631 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 <code>requests<\/code> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0648 \u0630\u062e\u06cc\u0631\u0647 \u0622\u0646 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u06cc\u06a9 \u0641\u0627\u06cc\u0644 \u0631\u0648\u06cc \u062f\u0631\u0627\u06cc\u0648 \u0645\u062d\u0644\u06cc \u0645\u0627:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> requests\nresponse = requests.get(<span class=\"hljs-string\">'https:\/\/i.ytimg.com\/vi\/q71MCWAEfL8\/maxresdefault.jpg'<\/span>)\n<span class=\"hljs-built_in\">open<\/span>(<span class=\"hljs-string\">\"obj_det.jpeg\"<\/span>, <span class=\"hljs-string\">\"wb\"<\/span>).write(response.content)\n\nimg = read_image(<span class=\"hljs-string\">\"obj_det.jpeg\"<\/span>)\n<\/code><\/pre>\n<p>\u0628\u0627 \u06cc\u06a9 \u062a\u0635\u0648\u06cc\u0631 \u062f\u0631 \u062c\u0627\u06cc \u062e\u0648\u062f &#8211; \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0645\u062f\u0644 \u0648 \u0648\u0632\u0646 \u0647\u0627\u06cc \u062e\u0648\u062f \u0631\u0627 \u0646\u0645\u0648\u0646\u0647 \u0633\u0627\u0632\u06cc \u06a9\u0646\u06cc\u0645:<\/p>\n<pre><code class=\"hljs\">weights = RetinaNet_ResNet50_FPN_V2_Weights.DEFAULT\nmodel = retinanet_resnet50_fpn_v2(weights=weights, score_thresh=<span class=\"hljs-number\">0.35<\/span>)\n\nmodel.<span class=\"hljs-built_in\">eval<\/span>()\n\npreprocess = weights.transforms()\n<\/code><\/pre>\n<p>\u0627\u06cc\u0646 <code>score_thresh<\/code> \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u0622\u0633\u062a\u0627\u0646\u0647 \u0627\u06cc \u0631\u0627 \u062a\u0639\u0631\u06cc\u0641 \u0645\u06cc \u06a9\u0646\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u06cc\u06a9 \u0634\u06cc \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u06cc\u06a9 \u0634\u06cc \u0627\u0632 \u06cc\u06a9 \u06a9\u0644\u0627\u0633 \u0634\u0646\u0627\u0633\u0627\u06cc\u06cc \u0645\u06cc \u0634\u0648\u062f.  \u0628\u0647 \u0637\u0648\u0631 \u0634\u0647\u0648\u062f\u06cc\u060c \u0622\u0633\u062a\u0627\u0646\u0647 \u0627\u0637\u0645\u06cc\u0646\u0627\u0646 \u0627\u0633\u062a\u060c \u0648 \u0627\u06af\u0631 \u0645\u062f\u0644 \u06a9\u0645\u062a\u0631 \u0627\u0632 35\u066a \u0645\u0637\u0645\u0626\u0646 \u0628\u0627\u0634\u062f \u06a9\u0647 \u0628\u0647 \u06cc\u06a9 \u06a9\u0644\u0627\u0633 \u062a\u0639\u0644\u0642 \u062f\u0627\u0631\u062f\u060c \u0645\u0627 \u06cc\u06a9 \u0634\u06cc \u0631\u0627 \u0628\u0647 \u06cc\u06a9 \u06a9\u0644\u0627\u0633 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0646\u0645\u06cc \u06a9\u0646\u06cc\u0645.<\/p>\n<p>\u0628\u06cc\u0627\u06cc\u06cc\u062f \u062a\u0635\u0648\u06cc\u0631 \u0631\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062a\u0628\u062f\u06cc\u0644\u200c\u0647\u0627\u06cc \u0648\u0632\u0646\u200c\u0647\u0627\u06cc\u0645\u0627\u0646 \u0627\u0632 \u0642\u0628\u0644 \u067e\u0631\u062f\u0627\u0632\u0634 \u06a9\u0646\u06cc\u0645\u060c \u06cc\u06a9 \u062f\u0633\u062a\u0647 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u0645 \u0648 \u0627\u0633\u062a\u0646\u062a\u0627\u062c \u0631\u0627 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u0645:<\/p>\n<pre><code class=\"hljs\">batch = (preprocess(img))\nprediction = model(batch)(<span class=\"hljs-number\">0<\/span>)\n<\/code><\/pre>\n<p>\u0647\u0645\u06cc\u0646 \u0627\u0633\u062a\u060c \u0645\u0627 <code>prediction<\/code> \u0641\u0631\u0647\u0646\u06af \u0644\u063a\u062a \u062f\u0627\u0631\u0627\u06cc \u06a9\u0644\u0627\u0633\u200c\u0647\u0627 \u0648 \u0645\u06a9\u0627\u0646\u200c\u0647\u0627\u06cc \u0634\u06cc \u0627\u0633\u062a\u0646\u062a\u0627\u062c \u0634\u062f\u0647 \u0627\u0633\u062a!  \u0627\u06a9\u0646\u0648\u0646\u060c \u0646\u062a\u0627\u06cc\u062c \u062f\u0631 \u0627\u06cc\u0646 \u0641\u0631\u0645 \u0628\u0631\u0627\u06cc \u0645\u0627 \u0686\u0646\u062f\u0627\u0646 \u0645\u0641\u06cc\u062f \u0646\u06cc\u0633\u062a\u0646\u062f &#8211; \u0645\u06cc\u200c\u062e\u0648\u0627\u0647\u06cc\u0645 \u0628\u0631\u0686\u0633\u0628\u200c\u0647\u0627 \u0631\u0627 \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0627\u0628\u0631\u062f\u0627\u062f\u0647\u200c\u0647\u0627 \u0627\u0632 \u0648\u0632\u0646\u200c\u0647\u0627 \u0627\u0633\u062a\u062e\u0631\u0627\u062c \u06a9\u0646\u06cc\u0645 \u0648 \u062c\u0639\u0628\u0647\u200c\u0647\u0627\u06cc \u0645\u0631\u0632\u0628\u0646\u062f\u06cc \u0631\u0627 \u062a\u0631\u0633\u06cc\u0645 \u06a9\u0646\u06cc\u0645\u060c \u06a9\u0647 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646 \u0627\u0632 \u0637\u0631\u06cc\u0642 \u0627\u06cc\u0646 \u06a9\u0627\u0631 \u0627\u0646\u062c\u0627\u0645 \u062f\u0627\u062f. <code>draw_bounding_boxes()<\/code>:<\/p>\n<pre><code class=\"hljs\">labels = (weights.meta(<span class=\"hljs-string\">\"categories\"<\/span>)(i) <span class=\"hljs-keyword\">for<\/span> i <span class=\"hljs-keyword\">in<\/span> prediction(<span class=\"hljs-string\">\"labels\"<\/span>))\n\nbox = draw_bounding_boxes(img, boxes=prediction(<span class=\"hljs-string\">\"boxes\"<\/span>),\n                          labels=labels,\n                          colors=<span class=\"hljs-string\">\"cyan\"<\/span>,\n                          width=<span class=\"hljs-number\">2<\/span>, \n                          font_size=<span class=\"hljs-number\">30<\/span>,\n                          font=<span class=\"hljs-string\">'Arial'<\/span>)\n\nim = to_pil_image(box.detach())\n\nfig, ax = plt.subplots(figsize=(<span class=\"hljs-number\">16<\/span>, <span class=\"hljs-number\">12<\/span>))\nax.imshow(im)\nplt.show()\n<\/code><\/pre>\n<p>\u0627\u06cc\u0646 \u0646\u062a\u06cc\u062c\u0647 \u062f\u0631:<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/rasanegar.com\/blog\/wp-content\/uploads\/2024\/01\/object-detection-4.png\" alt=\"\" title=\"\"><\/p>\n<p>\u0631\u062a\u06cc\u0646\u0627 \u0646\u062a \u062f\u0631 \u0648\u0627\u0642\u0639 \u0641\u0631\u062f\u06cc \u0631\u0627 \u06a9\u0647 \u067e\u0634\u062a \u0645\u0627\u0634\u06cc\u0646 \u0646\u06af\u0627\u0647 \u0645\u06cc \u06a9\u0646\u062f \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u06a9\u0631\u062f!  \u0627\u06cc\u0646 \u06cc\u06a9 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0628\u0633\u06cc\u0627\u0631 \u062f\u0634\u0648\u0627\u0631 \u0627\u0633\u062a.<\/p>\n<p>\u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f RetinaNet \u0631\u0627 \u0628\u0647 \u06cc\u06a9 FCOS (RetinaNet \u06a9\u0627\u0645\u0644\u0627\u064b \u06a9\u0627\u0646\u0648\u0644\u0648\u0634\u0646\u0627\u0644) \u0628\u0627 \u062c\u0627\u06cc\u06af\u0632\u06cc\u0646\u06cc \u062a\u063a\u06cc\u06cc\u0631 \u062f\u0647\u06cc\u062f <code>retinanet_resnet50_fpn_v2<\/code> \u0628\u0627 <code>fcos_resnet50_fpn<\/code>\u060c \u0648 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f <code>FCOS_ResNet50_FPN_Weights<\/code> \u0648\u0632\u0646 \u0647\u0627:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> torchvision.io.image <span class=\"hljs-keyword\">import<\/span> read_image\n<span class=\"hljs-keyword\">from<\/span> torchvision.utils <span class=\"hljs-keyword\">import<\/span> draw_bounding_boxes\n<span class=\"hljs-keyword\">from<\/span> torchvision.transforms.functional <span class=\"hljs-keyword\">import<\/span> to_pil_image\n<span class=\"hljs-keyword\">from<\/span> torchvision.models.detection <span class=\"hljs-keyword\">import<\/span> fcos_resnet50_fpn, FCOS_ResNet50_FPN_Weights\n\n<span class=\"hljs-keyword\">import<\/span> matplotlib.pyplot <span class=\"hljs-keyword\">as<\/span> plt\n<span class=\"hljs-keyword\">import<\/span> requests\nresponse = requests.get(<span class=\"hljs-string\">'https:\/\/i.ytimg.com\/vi\/q71MCWAEfL8\/maxresdefault.jpg'<\/span>)\n<span class=\"hljs-built_in\">open<\/span>(<span class=\"hljs-string\">\"obj_det.jpeg\"<\/span>, <span class=\"hljs-string\">\"wb\"<\/span>).write(response.content)\n\nimg = read_image(<span class=\"hljs-string\">\"obj_det.jpeg\"<\/span>)\nweights = FCOS_ResNet50_FPN_Weights.DEFAULT\nmodel = fcos_resnet50_fpn(weights=weights, score_thresh=<span class=\"hljs-number\">0.35<\/span>)\nmodel.<span class=\"hljs-built_in\">eval<\/span>()\n\npreprocess = weights.transforms()\nbatch = (preprocess(img))\nprediction = model(batch)(<span class=\"hljs-number\">0<\/span>)\n\nlabels = (weights.meta(<span class=\"hljs-string\">\"categories\"<\/span>)(i) <span class=\"hljs-keyword\">for<\/span> i <span class=\"hljs-keyword\">in<\/span> prediction(<span class=\"hljs-string\">\"labels\"<\/span>))\n\nbox = draw_bounding_boxes(img, boxes=prediction(<span class=\"hljs-string\">\"boxes\"<\/span>),\n                          labels=labels,\n                          colors=<span class=\"hljs-string\">\"cyan\"<\/span>,\n                          width=<span class=\"hljs-number\">2<\/span>, \n                          font_size=<span class=\"hljs-number\">30<\/span>,\n                          font=<span class=\"hljs-string\">'Arial'<\/span>)\n\nim = to_pil_image(box.detach())\n\nfig, ax = plt.subplots(figsize=(<span class=\"hljs-number\">16<\/span>, <span class=\"hljs-number\">12<\/span>))\nax.imshow(im)\nplt.show()\n<\/code><\/pre>\n<\/div>\n<p><script>\n                        !function(f,b,e,v,n,t,s)\n                        {if(f.fbq)return;n=f.fbq=function(){n.callMethod?\n                        n.callMethod.apply(n,arguments):n.queue.push(arguments)};\n                        if(!f._fbq)f._fbq=n;n.push=n;n.loaded=!0;n.version='2.0';\n                        n.queue=();t=b.createElement(e);t.async=!0;\n                        t.src=v;s=b.getElementsByTagName(e)(0);\n                        s.parentNode.insertBefore(t,s)}(window, document,'script',\n                        'https:\/\/connect.facebook.net\/en_US\/fbevents.js');\n                        fbq('init', '525232124909042');\n                        fbq('track', 'PageView');\n                    <\/script>    (\u0628\u0631\u0686\u0633\u0628\u200c\u0647\u0627 \u0628\u0647 \u062a\u0631\u062c\u0645\u0647)# python<br \/>\n<br \/><br \/>\n<br \/>\u0645\u0646\u062a\u0634\u0631 \u0634\u062f\u0647 \u062f\u0631 1403-01-04 04:25:05<br \/>\n<\/p>\n\n\n<div class=\"kk-star-ratings kksr-auto kksr-align-center kksr-valign-bottom\"\n    data-payload='{&quot;align&quot;:&quot;center&quot;,&quot;id&quot;:&quot;14121&quot;,&quot;slug&quot;:&quot;default&quot;,&quot;valign&quot;:&quot;bottom&quot;,&quot;ignore&quot;:&quot;&quot;,&quot;reference&quot;:&quot;auto&quot;,&quot;class&quot;:&quot;&quot;,&quot;count&quot;:&quot;0&quot;,&quot;legendonly&quot;:&quot;&quot;,&quot;readonly&quot;:&quot;&quot;,&quot;score&quot;:&quot;0&quot;,&quot;starsonly&quot;:&quot;&quot;,&quot;best&quot;:&quot;5&quot;,&quot;gap&quot;:&quot;5&quot;,&quot;greet&quot;:&quot;\u0627\u0645\u062a\u06cc\u0627\u0632 \u0634\u0645\u0627 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0637\u0644\u0628&quot;,&quot;legend&quot;:&quot;0\\\/5 (0 \u0631\u0627\u06cc)&quot;,&quot;size&quot;:&quot;30&quot;,&quot;title&quot;:&quot;RetinaNet Object Detection \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0627 PyTorch \u0648 Torchvision&quot;,&quot;width&quot;:&quot;0&quot;,&quot;_legend&quot;:&quot;{score}\\\/{best} ({count} \u0631\u0627\u06cc)&quot;,&quot;font_factor&quot;:&quot;1.25&quot;}'>\n            \n<div class=\"kksr-stars\">\n    \n<div class=\"kksr-stars-inactive\">\n            <div class=\"kksr-star\" data-star=\"1\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"2\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"3\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"4\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"5\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n    <\/div>\n    \n<div class=\"kksr-stars-active\" style=\"width: 0px;\">\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n    <\/div>\n<\/div>\n                \n\n<div class=\"kksr-legend\" style=\"font-size: 24px;\">\n            <span class=\"kksr-muted\">\u0627\u0645\u062a\u06cc\u0627\u0632 \u0634\u0645\u0627 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0637\u0644\u0628<\/span>\n    <\/div>\n    <\/div>\n","protected":false},"excerpt":{"rendered":"<p><span class=\"span-reading-time rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">\u0632\u0645\u0627\u0646 \u0644\u0627\u0632\u0645 \u0628\u0631\u0627\u06cc \u0645\u0637\u0627\u0644\u0639\u0647: <\/span> <span class=\"rt-time\"> 3<\/span> <span class=\"rt-label rt-postfix\">\u062f\u0642\u06cc\u0642\u0647<\/span><\/span>\u0645\u0639\u0631\u0641\u06cc \u062a\u0634\u062e\u06cc\u0635 \u0627\u0634\u06cc\u0627 \u0645\u06cc\u062f\u0627\u0646 \u0628\u0632\u0631\u06af\u06cc \u062f\u0631 \u0628\u06cc\u0646\u0627\u06cc\u06cc \u06a9\u0627\u0645\u067e\u06cc\u0648\u062a\u0631\u06cc \u0627\u0633\u062a \u0648 \u06cc\u06a9\u06cc \u0627\u0632 \u0645\u0647\u0645\u200c\u062a\u0631\u06cc\u0646 \u06a9\u0627\u0631\u0628\u0631\u062f\u0647\u0627\u06cc \u0628\u06cc\u0646\u0627\u06cc\u06cc \u06a9\u0627\u0645\u067e\u06cc\u0648\u062a\u0631 \u062f\u0631 \u0637\u0628\u06cc\u0639\u062a \u0627\u0633\u062a. \u0627\u0632 \u06cc\u06a9 \u0637\u0631\u0641\u060c \u0645\u06cc\u200c\u062a\u0648\u0627\u0646 \u0627\u0632 \u0622\u0646 \u0628\u0631\u0627\u06cc \u0633\u0627\u062e\u062a \u0633\u06cc\u0633\u062a\u0645\u200c\u0647\u0627\u06cc \u0645\u0633\u062a\u0642\u0644\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f \u06a9\u0647 \u0639\u0648\u0627\u0645\u0644 \u0631\u0627 \u062f\u0631 \u0645\u062d\u06cc\u0637\u200c\u0647\u0627 \u0647\u062f\u0627\u06cc\u062a \u0645\u06cc\u200c\u06a9\u0646\u0646\u062f &#8211; \u0686\u0647 \u0631\u0648\u0628\u0627\u062a\u200c\u0647\u0627\u06cc\u06cc \u06a9\u0647 \u0648\u0638\u0627\u06cc\u0641 \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u0645\u06cc\u200c\u062f\u0647\u0646\u062f \u06cc\u0627 \u0645\u0627\u0634\u06cc\u0646\u200c\u0647\u0627\u06cc \u062e\u0648\u062f\u0631\u0627\u0646\u060c \u0627\u0645\u0627 \u0627\u06cc\u0646 \u0646\u06cc\u0627\u0632 \u0628\u0647 \u062a\u0642\u0627\u0637\u0639 \u0628\u0627 [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":14122,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1743,620],"tags":[],"class_list":["post-14121","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python","category-programming"],"acf":[],"_links":{"self":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts\/14121","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/comments?post=14121"}],"version-history":[{"count":0,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts\/14121\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/media\/14122"}],"wp:attachment":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/media?parent=14121"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/categories?post=14121"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/tags?post=14121"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}