{"id":3993,"date":"2022-09-16T14:36:57","date_gmt":"2022-09-16T22:36:57","guid":{"rendered":"https:\/\/live-cometml.pantheonsite.io\/?p=3993"},"modified":"2025-04-29T14:08:40","modified_gmt":"2025-04-29T14:08:40","slug":"introducing-comets-new-image-panel","status":"publish","type":"post","link":"https:\/\/www.comet.com\/site\/blog\/introducing-comets-new-image-panel\/","title":{"rendered":"Introducing Comet&#8217;s New Image Panel"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\"><b>The Need for Visualization&nbsp;<\/b><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400;\">For computer vision tasks such as segmentation, reconstruction, or object detection, it is imperative to visualize the model\u2019s performance on your data. While tracking metrics such as loss and mAP are important , those values do not tell the whole story.&nbsp;<\/span><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400;\">Comet has long provided its users the ability to log all relevant images to the graphics tab. The tab makes it easy to visualize model performance on your image data for a single experiment. Now, with our new feature, one can compare their model visualizations across multiple experiments!<\/span><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Visualizing Autoencoders<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400;\">Auto-encoders are powerful feature extractors and can be applied to anomaly detection use-cases and state space dimensionality reduction in Reinforcement Learning. When building an Auto-encoder model, there are a&nbsp; myriad of architectures, learning rates, loss calculations and other hyper-parameters to choose from.&nbsp;<\/span><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400;\">I see that in my new experiment, my reconstruction loss decreased when compared to my past two experiments. But to what extent did that make my reconstructed image similar to the original image?&nbsp;<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter\"><img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"152\" src=\"https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Metrics-for-Auto-Encoder-Image-Panel-300x152.png\" alt=\"\" class=\"wp-image-3995\" srcset=\"https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Metrics-for-Auto-Encoder-Image-Panel-300x152.png 300w, https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Metrics-for-Auto-Encoder-Image-Panel-1024x518.png 1024w, https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Metrics-for-Auto-Encoder-Image-Panel-768x389.png 768w, https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Metrics-for-Auto-Encoder-Image-Panel-1536x777.png 1536w, https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Metrics-for-Auto-Encoder-Image-Panel-2048x1037.png 2048w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400;\">With the new Image Panel, engineers can visualize how their choices affect the autoencoder model\u2019s ability to reconstruct the original side-by-side. In the image panel, search for your unique image names across your experiments, and create a grid spanning your different experiments in seconds. <\/span><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400;\">The Image Panel not only enables users to visualize model predictions across experiments, but also to visualize their predictions throughout the training process. Using the stepper&nbsp; within the Image Panel allows one to see how multiple models are improving over time.<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image\"><img loading=\"lazy\" decoding=\"async\" width=\"1125\" height=\"778\" src=\"https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Blog_img_panel.gif\" alt=\"\" class=\"wp-image-4006\"\/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><b>Where to find the Image Panel?<\/b><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400;\">The Image Panel is a Built-in Panel! They can be found easily by clicking on the <strong>Add+<\/strong> button and then selecting the <strong>New Panel<\/strong> option.<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image aligncenter\"><img loading=\"lazy\" decoding=\"async\" width=\"2438\" height=\"1614\" src=\"https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Image-panel.png\" alt=\"\" class=\"wp-image-4009\" srcset=\"https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Image-panel.png 2438w, https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Image-panel-300x199.png 300w, https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Image-panel-1024x678.png 1024w, https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Image-panel-768x508.png 768w, https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Image-panel-1536x1017.png 1536w, https:\/\/www.comet.com\/site\/wp-content\/uploads\/2022\/09\/Image-panel-2048x1356.png 2048w\" sizes=\"auto, (max-width: 2438px) 100vw, 2438px\" \/><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><span style=\"font-weight: 400;\">&nbsp;&nbsp;<\/span><\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span style=\"font-weight: 400;\">Want to see the new Image Panel?&nbsp;<\/span><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">You can check it out for yourself in the public project.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/www.comet.com\/sherpan\/autoencoder?shareable=PQ8BP8ppwzwU6lLp40M3G0UzA\" target=\"_blank\" rel=\"noreferrer noopener\">View the public Comet project<\/a><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>The Need for Visualization&nbsp; For computer vision tasks such as segmentation, reconstruction, or object detection, it is imperative to visualize the model\u2019s performance on your data. While tracking metrics such as loss and mAP are important , those values do not tell the whole story.&nbsp; Comet has long provided its users the ability to log [&hellip;]<\/p>\n","protected":false},"author":21,"featured_media":4015,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"customer_name":"","customer_description":"","customer_industry":"","customer_technologies":"","customer_logo":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[8,9],"tags":[],"coauthors":[134],"class_list":["post-3993","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-comet-community-hub","category-product"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Introducing Comet&#039;s New Image Panel - Comet<\/title>\n<meta name=\"description\" content=\"This feature makes it easy to visualize model performance on your image data. 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