Anurag1734/cuda-error-resolution-analysis
07
1[2 {3 "post_stream": {4 "posts": [5 {6 "id": 186071,7 "name": "Haemin Jung",8 "username": "haeminjung",9 "avatar_template": "/user_avatar/discuss.pytorch.org/haeminjung/{size}/22573_2.png",10 "created_at": "2020-04-25T08:12:52.191Z",11 "cooked": "<p>I have posted a question about the normalized image seems to be a bit “off”</p><aside class=\"quote quote-modified\" data-post=\"1\" data-topic=\"76138\">\n <div class=\"title\">\n <div class=\"quote-controls\"></div>\n <img loading=\"lazy\" alt=\"\" width=\"24\" height=\"24\" src=\"https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/haeminjung/48/22573_2.png\" class=\"avatar\">\n <a href=\"https://discuss.pytorch.org/t/dataloader-loading-color-distorted-image/76138\">Dataloader loading color distorted image</a> <a class=\"badge-category__wrapper \" href=\"/c/vision/5\"><span data-category-id=\"5\" style=\"--category-badge-color: #AB9364; --category-badge-text-color: #FFFFFF;\" data-drop-close=\"true\" class=\"badge-category \" title=\"Topics related to either pytorch/vision or vision research related topics\"><span class=\"badge-category__name\">vision</span></span></a>\n </div>\n <blockquote>\n Quick show and tell will be the easiest way to tell you the problem. \n# Define the dataset and the loader as usual\ndataset = dset.ImageFolder(root=datapath,\n transform=transforms.Compose([\n transforms.Resize(image_size),\n #transforms.CenterCrop(image_size),\n transforms.ToTensor(),\n transforms.Normalize((0.5414, 0.5333, 0.5338),(0.1897, 0.1911, 0.19…\n </blockquote>\n</aside>\n\n<p>Relating to the problem, the output of the image compared to the input seems rather color distorted.<br>\n<div class=\"lightbox-wrapper\"><a class=\"lightbox\" href=\"https://discuss.pytorch.org/uploads/default/original/3X/f/8/f88846b4b7d7b1d3182b5e90bf8cee9b0b0c2445.jpeg\" data-download-href=\"https://discuss.pytorch.org/uploads/default/f88846b4b7d7b1d3182b5e90bf8cee9b0b0c2445\" title=\"download (2)\"><img src=\"https://discuss.pytorch.org/uploads/default/optimized/3X/f/8/f88846b4b7d7b1d3182b5e90bf8cee9b0b0c2445_2_690x319.jpeg\" alt=\"download (2)\" data-base62-sha1=\"zsCnKwWHP71m90xQ687EiTs61RX\" width=\"690\" height=\"319\" srcset=\"https://discuss.pytorch.org/uploads/default/optimized/3X/f/8/f88846b4b7d7b1d3182b5e90bf8cee9b0b0c2445_2_690x319.jpeg, https://discuss.pytorch.org/uploads/default/optimized/3X/f/8/f88846b4b7d7b1d3182b5e90bf8cee9b0b0c2445_2_1035x478.jpeg 1.5x, https://discuss.pytorch.org/uploads/default/optimized/3X/f/8/f88846b4b7d7b1d3182b5e90bf8cee9b0b0c2445_2_1380x638.jpeg 2x\" data-dominant-color=\"8D8C8C\"><div class=\"meta\"><svg class=\"fa d-icon d-icon-far-image svg-icon\" aria-hidden=\"true\"><use href=\"#far-image\"></use></svg><span class=\"filename\">download (2)</span><span class=\"informations\">2836×1315 1.63 MB</span><svg class=\"fa d-icon d-icon-discourse-expand svg-icon\" aria-hidden=\"true\"><use href=\"#discourse-expand\"></use></svg></div></a></div></p>\n<p>I just one someone to point out if this is a problem that convT faces in definition, or if it’s me that’s doing something wrong?</p>\n<p>The papers that I had seen on GANs, and Autoencoders never seemed to have such problems.</p>",12 "post_number": 1,13 "post_type": 1,14 "posts_count": 1,15 "updated_at": "2020-04-25T08:12:52.191Z",16 "reply_count": 0,17 "reply_to_post_number": null,18 "quote_count": 0,19 "incoming_link_count": 86,20 "reads": 5,21 "readers_count": 4,22 "score": 431.0,23 "yours": false,24 "topic_id": 78350,25 "topic_slug": "autoencoder-result-color-distortion",26 "display_username": "Haemin Jung",27 "primary_group_name": null,28 "flair_name": null,29 "flair_url": null,30 "flair_bg_color": null,31 "flair_color": null,32 "flair_group_id": null,33 "badges_granted": [],34 "version": 1,35 "can_edit": false,36 "can_delete": false,37 "can_recover": false,38 "can_see_hidden_post": false,39 "can_wiki": false,40 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Thanks</p>",458 "post_number": 1,459 "post_type": 1,460 "posts_count": 1,461 "updated_at": "2020-04-25T07:23:09.441Z",462 "reply_count": 0,463 "reply_to_post_number": null,464 "quote_count": 0,465 "incoming_link_count": 7,466 "reads": 5,467 "readers_count": 4,468 "score": 36.0,469 "yours": false,470 "topic_id": 78345,471 "topic_slug": "advice-for-model-in-transfer-learning",472 "display_username": "Jaeho Kim",473 "primary_group_name": null,474 "flair_name": null,475 "flair_url": null,476 "flair_bg_color": null,477 "flair_color": null,478 "flair_group_id": null,479 "badges_granted": [],480 "version": 1,481 "can_edit": false,482 "can_delete": false,483 "can_recover": false,484 "can_see_hidden_post": false,485 "can_wiki": false,486 "read": true,487 "user_title": null,488 "bookmarked": false,489 "actions_summary": [],490 "moderator": false,491 "admin": false,492 "staff": false,493 "user_id": 28767,494 "hidden": false,495 "trust_level": 1,496 "deleted_at": null,497 "user_deleted": false,498 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"username": "Jay_Super",874 "name": "Jaeho Kim",875 "avatar_template": "/user_avatar/discuss.pytorch.org/jay_super/{size}/30626_2.png"876 },877 "last_poster": {878 "id": 28767,879 "username": "Jay_Super",880 "name": "Jaeho Kim",881 "avatar_template": "/user_avatar/discuss.pytorch.org/jay_super/{size}/30626_2.png"882 }883 },884 "bookmarks": []885 },886 {887 "post_stream": {888 "posts": [889 {890 "id": 185849,891 "name": "ratan",892 "username": "Ratan",893 "avatar_template": "/user_avatar/discuss.pytorch.org/ratan/{size}/12876_2.png",894 "created_at": "2020-04-24T15:36:00.168Z",895 "cooked": "<p>uppose I have to design a 3 class classifier with following things in mind:</p>\n<p>I have 3 folders as datasets such as:</p>\n<ul>\n<li>…/data/cat/ …/data/dog/ …/data/man/</li>\n</ul>\n<p>Each folder has images for that particular class only.</p>\n<p>We divide the images into train,test,val using the following:</p>\n<p>train_data = datasets.ImageFolder(train_dir, transform=data_transforms[‘train’])</p>\n<p>test_data = datasets.ImageFolder(test_dir, transform=data_transforms[‘test’])</p>\n<p>My question is how will ImageFolder() divide the images into train,test from EACH class folder as given above??</p>\n<p>Also,</p>\n<p>img,target = netx(iter(…))</p>\n<p>gives the target or label. 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Ratan:</div>\n<blockquote>\n<p>My question is how will ImageFolder() divide the images into train,test from EACH class folder as given above??</p>\n</blockquote>\n</aside>\n<p>It won’t divide the folders automatically. <code>ImageFolder</code> takes the root folder as an argument and will use all images from all subfolders as data samples.</p>\n<p>To split the dataset, you could use <code>torch.utils.data.random_split</code>, <code>torch.utils.data.Subset</code> passing the indices, or <code>torch.utils.data.sampler.SubsetRandomSampler</code> also passing the indices.</p>\n<aside class=\"quote no-group\" data-username=\"Ratan\" data-post=\"1\" data-topic=\"78247\">\n<div class=\"title\">\n<div class=\"quote-controls\"></div>\n<img loading=\"lazy\" alt=\"\" width=\"24\" height=\"24\" src=\"https://discuss.pytorch.org/user_avatar/discuss.pytorch.org/ratan/48/12876_2.png\" class=\"avatar\"> Ratan:</div>\n<blockquote>\n<p>My question is how will ImageFolder() divide the images into train,test from EACH class folder as given above??</p>\n</blockquote>\n</aside>\n<p><code>ImageFolder</code> will sort all subfolders and assign a class label to each of them as seen in <a href=\"https://github.com/pytorch/vision/blob/3e60fb29986ad74d9e4dc5715479d7bd3d8b59ba/torchvision/datasets/folder.py#L108-L144\">these lines of code</a>.</p>",953 "post_number": 2,954 "post_type": 1,955 "posts_count": 2,956 "updated_at": "2020-04-25T07:09:22.547Z",957 "reply_count": 0,958 "reply_to_post_number": null,959 "quote_count": 1,960 "incoming_link_count": 55,961 "reads": 44,962 "readers_count": 43,963 "score": 283.8,964 "yours": false,965 "topic_id": 78247,966 "topic_slug": "how-to-use-datasets-imagefolder-for-custom-datasets",967 "display_username": "",968 "primary_group_name": null,969 "flair_name": null,970 "flair_url": null,971 "flair_bg_color": null,972 "flair_color": null,973 "flair_group_id": null,974 "badges_granted": [],975 "version": 1,976 "can_edit": false,977 "can_delete": 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