{"id":29574,"date":"2024-10-28T01:55:31","date_gmt":"2024-10-28T01:55:31","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=29574"},"modified":"2024-11-26T06:52:14","modified_gmt":"2024-11-26T06:52:14","slug":"%ed%97%88%ea%b9%85%ed%8e%98%ec%9d%b4%ec%8a%a4-%ed%8a%b8%eb%a0%8c%ec%8a%a4%ed%8f%ac%eb%a8%b8-%ed%99%9c%ec%9a%a9%ea%b0%95%ec%a2%8c-clip-%ec%b6%94%eb%a1%a0%ec%97%90%ec%84%9c-%eb%a1%9c%ec%a7%93-%ec%b6%94","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/29574\/","title":{"rendered":"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, CLIP \ucd94\ub860\uc5d0\uc11c \ub85c\uc9d3 \ucd94\ucd9c"},"content":{"rendered":"<p>\ub525\ub7ec\ub2dd\uacfc \uc790\uc5f0\uc5b4 \ucc98\ub9ac, \ucef4\ud4e8\ud130 \ube44\uc804 \ubd84\uc57c\uac00 \ubc1c\uc804\ud568\uc5d0 \ub530\ub77c \ub2e4\uc591\ud55c \ubaa8\ub378\ub4e4\uc774 \ub4f1\uc7a5\ud558\uc600\uc2b5\ub2c8\ub2e4. \uadf8 \uc911\uc5d0\uc11c\ub3c4 OpenAI\uc758 CLIP(Contrastive Language-Image Pretraining)\uc740 \ud14d\uc2a4\ud2b8\uc640 \uc774\ubbf8\uc9c0\ub97c \ub3d9\uc2dc\uc5d0 \uc774\ud574\ud558\uace0 \ud65c\uc6a9\ud560 \uc218 \uc788\ub294 \uac15\ub825\ud55c \ubaa8\ub378\uc785\ub2c8\ub2e4. \uc774 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec CLIP \ubaa8\ub378\uc744 \ud65c\uc6a9\ud558\uace0, \uadf8\ub85c\ubd80\ud130 \ub85c\uc9d3(logits)\uc744 \ucd94\ucd9c\ud558\ub294 \uacfc\uc815\uc744 \uc790\uc138\ud788 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>1. CLIP \ubaa8\ub378 \uac1c\uc694<\/h2>\n<p>CLIP\uc740 \ub2e4\uc591\ud55c \uc774\ubbf8\uc9c0\uc640 \ud14d\uc2a4\ud2b8 \uc30d\uc73c\ub85c \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc785\ub2c8\ub2e4. \uc774 \ubaa8\ub378\uc740 \uc8fc\uc5b4\uc9c4 \ud14d\uc2a4\ud2b8 \uc124\uba85\uc5d0 \uac00\uc7a5 \uc798 \ub9de\ub294 \uc774\ubbf8\uc9c0\ub97c \ucc3e\uac70\ub098, \uc8fc\uc5b4\uc9c4 \uc774\ubbf8\uc9c0\uc5d0 \ub300\ud574 \uac00\uc7a5 \uc801\ud569\ud55c \ud14d\uc2a4\ud2b8 \uc124\uba85\uc744 \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. CLIP \ubaa8\ub378\uc740 \uc8fc\ub85c \ub450 \uac00\uc9c0 \uc785\ub825\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4: \uc774\ubbf8\uc9c0\uc640 \ud14d\uc2a4\ud2b8.<\/p>\n<h3>1.1 CLIP\uc758 \uad6c\uc870<\/h3>\n<p>CLIP\uc740 \uc774\ubbf8\uc9c0 \uc778\ucf54\ub354\uc640 \ud14d\uc2a4\ud2b8 \uc778\ucf54\ub354\ub85c \uad6c\uc131\ub429\ub2c8\ub2e4. \uc774\ubbf8\uc9c0 \uc778\ucf54\ub354\ub294 CNN(Convolutional Neural Network) \ub610\ub294 Vision Transformer\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774\ubbf8\uc9c0\ub97c \ud53c\ucc98 \ubca1\ud130\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4. \ubc18\uba74 \ud14d\uc2a4\ud2b8 \uc778\ucf54\ub354\ub294 Transformer \uc544\ud0a4\ud14d\ucc98\ub97c \uc0ac\uc6a9\ud558\uc5ec \ud14d\uc2a4\ud2b8\ub97c \ud53c\ucc98 \ubca1\ud130\ub85c \ubcc0\ud658\ud569\ub2c8\ub2e4. \uc774 \ub450 \uc778\ucf54\ub354\uc758 \ucd9c\ub825\uc740 \uac19\uc740 \ubca1\ud130 \uacf5\uac04\uc5d0 \uc704\uce58\ud558\ub3c4\ub85d \uad50\uc721\ub418\uc5b4, \ub450 \ub3c4\uba54\uc778 \uac04\uc758 \uc720\uc0ac\ub3c4 \uce21\uc815\uc774 \uac00\ub2a5\ud558\ub3c4\ub85d \ud569\ub2c8\ub2e4.<\/p>\n<h2>2. \ud658\uacbd \uc124\uc815<\/h2>\n<p>CLIP \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\uae30 \uc704\ud574\uc11c\ub294 \uba3c\uc800 Hugging Face Transformers\uc640 \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub4e4\uc744 \uc124\uce58\ud574\uc57c \ud569\ub2c8\ub2e4. \ub2e4\uc74c\uacfc \uac19\uc740 \ud328\ud0a4\uc9c0\ub4e4\uc774 \ud544\uc694\ud569\ub2c8\ub2e4:<\/p>\n<ul>\n<li>transformers<\/li>\n<li>torch<\/li>\n<li>PIL (Python Imaging Library)<\/li>\n<\/ul>\n<p>\ub2e4\uc74c\uacfc \uac19\uc774 \ud544\uc694\ud55c \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc124\uce58\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4:<\/p>\n<pre><code>pip install torch torchvision transformers pillow<\/code><\/pre>\n<h2>3. CLIP \ubaa8\ub378 \ub85c\ub4dc \ubc0f \uc774\ubbf8\uc9c0\/\ud14d\uc2a4\ud2b8 \uc804\ucc98\ub9ac<\/h2>\n<p>\uc774\uc81c Hugging Face\uc758 Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec CLIP \ubaa8\ub378\uc744 \ub85c\ub4dc\ud558\uace0, \uc774\ubbf8\uc9c0\uc640 \ud14d\uc2a4\ud2b8\ub97c \uc804\ucc98\ub9ac\ud558\ub294 \ubc29\ubc95\uc744 \uc0b4\ud3b4\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n<pre><code>import torch\nfrom transformers import CLIPProcessor, CLIPModel\nfrom PIL import Image\n\n# CLIP \ubaa8\ub378\uacfc \ud504\ub85c\uc138\uc11c \ub85c\ub4dc\ud558\uae30\nmodel = CLIPModel.from_pretrained(\"openai\/clip-vit-base-patch16\")\nprocessor = CLIPProcessor.from_pretrained(\"openai\/clip-vit-base-patch16\")\n\n# \uc774\ubbf8\uc9c0\ub97c \ub85c\ub4dc\ud558\uace0 \uc804\ucc98\ub9ac\ud558\uae30\nimage = Image.open(\"path\/to\/your\/image.jpg\")\n\n# \ud14d\uc2a4\ud2b8\ub97c \uc900\ube44\ud558\uae30\ntexts = [\"a photo of a cat\", \"a photo of a dog\", \"a photo of a bird\"]\n\n# \ud14d\uc2a4\ud2b8\uc640 \uc774\ubbf8\uc9c0\ub97c CLIP \ud504\ub85c\uc138\uc11c\ub85c \uc804\ucc98\ub9ac\ud558\uae30\ninputs = processor(text=texts, images=image, return_tensors=\"pt\", padding=True)<\/code><\/pre>\n<h3>3.1 \ud14d\uc2a4\ud2b8\uc640 \uc774\ubbf8\uc9c0 \uc804\ucc98\ub9ac \uc124\uba85<\/h3>\n<p>\uc704 \ucf54\ub4dc\uc5d0\uc11c\ub294 \uc774\ubbf8\uc9c0\ub97c \ub85c\ub4dc\ud558\uace0, \uc8fc\uc5b4\uc9c4 \ud14d\uc2a4\ud2b8 \ub9ac\uc2a4\ud2b8\uc5d0 \ub300\ud574 CLIP \ud504\ub85c\uc138\uc11c\ub85c \uc804\ucc98\ub9ac\ub97c \uc9c4\ud589\ud569\ub2c8\ub2e4. \uc774 \ub2e8\uacc4\uc5d0\uc11c \ud14d\uc2a4\ud2b8\uc640 \uc774\ubbf8\uc9c0\uac00 CLIP \ubaa8\ub378\uc5d0 \ub9de\ub294 \ud615\uc2dd\uc73c\ub85c \ubcc0\ud658\ub429\ub2c8\ub2e4.<\/p>\n<h2>4. CLIP \ubaa8\ub378 \ucd94\ub860 \ubc0f \ub85c\uc9d3 \ucd94\ucd9c<\/h2>\n<p>\ubaa8\ub378\uc744 \uc900\ube44\ud55c \ud6c4, \uc6b0\ub9ac\ub294 \uc774\ubbf8\uc9c0\ub97c \ubaa8\ub378\uc5d0 \uc785\ub825\ud558\uace0 \ub85c\uc9d3(logits)\uc744 \ucd94\ucd9c\ud558\ub294 \uacfc\uc815\uc744 \uc218\ud589\ud569\ub2c8\ub2e4.<\/p>\n<pre><code># \ubaa8\ub378\uc744 \ucd94\ub860 \ubaa8\ub4dc\ub85c \uc804\ud658\ud558\uae30\nmodel.eval()\n\n# \ubaa8\ub378\uc5d0 \uc785\ub825\ud558\uc5ec \ucd9c\ub825 \ub85c\uc9d3\uc744 \uc5bb\uae30\nwith torch.no_grad():\n    outputs = model(**inputs)\n\n# \ub85c\uc9d3 \ucd94\ucd9c\ud558\uae30\nlogits_per_image = outputs.logits_per_image  # Image to Text Logits\nlogits_per_text = outputs.logits_per_text      # Text to Image Logits\n<\/code><\/pre>\n<h3>4.1 \ub85c\uc9d3 \uc124\uba85<\/h3>\n<p>\uc704 \ucf54\ub4dc\uc5d0\uc11c \ub85c\uc9d3\uc740 \uc774\ubbf8\uc9c0\uc640 \ud14d\uc2a4\ud2b8 \uac04\uc758 \uc720\uc0ac\ub3c4\ub97c \ub098\ud0c0\ub0b4\ub294 \uc810\uc218\uc785\ub2c8\ub2e4. \ub85c\uc9d3 \uac12\uc774 \ub192\uc744\uc218\ub85d \ud574\ub2f9 \uc774\ubbf8\uc9c0\uc640 \ud14d\uc2a4\ud2b8\uac00 \uc798 \uc77c\uce58\ud55c\ub2e4\uace0 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4. <code>logits_per_image<\/code>\ub294 \uc774\ubbf8\uc9c0\uac00 \uac01 \ud14d\uc2a4\ud2b8\uc640 \uc5bc\ub9c8\ub098 \uc798 \ub9e4\uce58\ub418\ub294\uc9c0\ub97c \ub098\ud0c0\ub0b4\uace0, <code>logits_per_text<\/code>\ub294 \ud14d\uc2a4\ud2b8\uac00 \uac01 \uc774\ubbf8\uc9c0\uc640 \uc5bc\ub9c8\ub098 \uc798 \ub9e4\uce58\ub418\ub294\uc9c0\ub97c \ub098\ud0c0\ub0c5\ub2c8\ub2e4.<\/p>\n<h2>5. \uacb0\uacfc \ud574\uc11d<\/h2>\n<p>\uc774\uc81c \ucd94\ucd9c\ud55c \ub85c\uc9d3\uc744 \ud574\uc11d\ud574\ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \ub85c\uc9d3 \uac12\uc740 \uc18c\ud504\ud2b8\ub9e5\uc2a4 \ud568\uc218\ub97c \ud1b5\uacfc\uc2dc\ucf1c \uac01 \uc30d\uc758 \ud655\ub960\ub85c \ubcc0\ud658\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 \uac01 \ud14d\uc2a4\ud2b8\uc5d0 \ub300\ud55c \uc774\ubbf8\uc9c0\uc758 \ub9e4\uce6d \ud655\ub960\uc744 \uc2dc\uac01\ud654 \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<pre><code>import torch.nn.functional as F\n\n# \uc18c\ud504\ud2b8\ub9e5\uc2a4\ub97c \uc774\uc6a9\ud55c \ud655\ub960 \uacc4\uc0b0\nprobs = F.softmax(logits_per_image, dim=1)\n\n# \uac01 \ud14d\uc2a4\ud2b8\uc5d0 \ub300\ud55c \uc774\ubbf8\uc9c0\uc758 \ud655\ub960 \ucd9c\ub825\ud558\uae30\nfor i, text in enumerate(texts):\n    print(f\"'{text}': {probs[0][i].item():.4f}\") # \ud655\ub960 \ucd9c\ub825<\/code><\/pre>\n<h3>5.1 \ud655\ub960 \ud574\uc11d<\/h3>\n<p>\ud655\ub960 \uac12\uc740 \uac01 \ud14d\uc2a4\ud2b8 \uc124\uba85\uc774 \uc81c\uacf5\ub41c \uc774\ubbf8\uc9c0\uc640 \uc5bc\ub9c8\ub098 \uc720\uc0ac\ud55c\uc9c0\uc5d0 \ub300\ud55c \ucc99\ub3c4\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. \ud655\ub960\uc774 1\uc5d0 \uac00\uae4c\uc6b8\uc218\ub85d \ud574\ub2f9 \ud14d\uc2a4\ud2b8\uac00 \uc774\ubbf8\uc9c0\uc640 \uc798 \uc5b4\uc6b8\ub9b0\ub2e4\uace0 \ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub97c \ud1b5\ud574 CLIP \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud3c9\uac00\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n<h2>6. CLIP\uc758 \ud65c\uc6a9 \uc608\uc2dc<\/h2>\n<p>CLIP\uc744 \uc774\uc6a9\ud574 \uc5ec\ub7ec \ub2e4\uc591\ud55c \uc560\ud50c\ub9ac\ucf00\uc774\uc158\uc744 \ub9cc\ub4e4 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4:<\/p>\n<ul>\n<li>\uc774\ubbf8\uc9c0 \ud0dc\uae45: \uc774\ubbf8\uc9c0\uc5d0 \ub300\ud55c \uc801\uc808\ud55c \ud0dc\uadf8\ub97c \uc0dd\uc131.<\/li>\n<li>\uc774\ubbf8\uc9c0 \uac80\uc0c9: \ud14d\uc2a4\ud2b8 \ucffc\ub9ac\ub97c \uae30\ubc18\uc73c\ub85c\ud55c \uc774\ubbf8\uc9c0 \uac80\uc0c9.<\/li>\n<li>\ucf58\ud150\uce20 \uae30\ubc18 \ucd94\ucc9c \uc2dc\uc2a4\ud15c: \uc0ac\uc6a9\uc790 \uc120\ud638\ub3c4\uc5d0 \ub9de\ucd98 \uc774\ubbf8\uc9c0 \ucd94\ucc9c.<\/li>\n<\/ul>\n<h2>7. \uacb0\ub860<\/h2>\n<p>\uc774 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec CLIP \ubaa8\ub378\uc744 \ub85c\ub4dc\ud558\uace0, \uc774\ubbf8\uc9c0\uc640 \ud14d\uc2a4\ud2b8\ub97c \ucc98\ub9ac \ud6c4 \ub85c\uc9d3\uc744 \ucd94\ucd9c\ud558\ub294 \uacfc\uc815\uc744 \ubc30\uc6e0\uc2b5\ub2c8\ub2e4. CLIP \ubaa8\ub378\uc740 \ub2e4\uc591\ud55c \uc774\ubbf8\uc9c0\uc640 \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130 \uc30d \uae30\ubc18\uc758 \ubb38\uc81c\ub97c \ud574\uacb0\ud558\ub294 \ub370 \ub9e4\uc6b0 \uc720\uc6a9\ud55c \ub3c4\uad6c\uc785\ub2c8\ub2e4. \uc55e\uc73c\ub85c\ub3c4 CLIP \ubaa8\ub378\uc744 \ud65c\uc6a9\ud55c \ub2e4\uc591\ud55c \ub354 \ub098\uc544\uac04 \uc608\uc81c\ub97c \uc2dc\ub3c4\ud574\ubcf4\uc2dc\uae38 \ubc14\ub78d\ub2c8\ub2e4!<\/p>\n<h2>8. \ucc38\uace0\uc790\ub8cc<\/h2>\n<ul>\n<li><a href=\"https:\/\/huggingface.co\/docs\/transformers\/model_doc\/clip\">Hugging Face CLIP Documentation<\/a><\/li>\n<li><a href=\"https:\/\/https:\/\/openai.com\/research\/clip\">OpenAI CLIP Paper<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/openai\/CLIP\">OpenAI CLIP GitHub Repository<\/a><\/li>\n<\/ul>\n<p><strong>\ub05d!<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub525\ub7ec\ub2dd\uacfc \uc790\uc5f0\uc5b4 \ucc98\ub9ac, \ucef4\ud4e8\ud130 \ube44\uc804 \ubd84\uc57c\uac00 \ubc1c\uc804\ud568\uc5d0 \ub530\ub77c \ub2e4\uc591\ud55c \ubaa8\ub378\ub4e4\uc774 \ub4f1\uc7a5\ud558\uc600\uc2b5\ub2c8\ub2e4. \uadf8 \uc911\uc5d0\uc11c\ub3c4 OpenAI\uc758 CLIP(Contrastive Language-Image Pretraining)\uc740 \ud14d\uc2a4\ud2b8\uc640 \uc774\ubbf8\uc9c0\ub97c \ub3d9\uc2dc\uc5d0 \uc774\ud574\ud558\uace0 \ud65c\uc6a9\ud560 \uc218 \uc788\ub294 \uac15\ub825\ud55c \ubaa8\ub378\uc785\ub2c8\ub2e4. \uc774 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec CLIP \ubaa8\ub378\uc744 \ud65c\uc6a9\ud558\uace0, \uadf8\ub85c\ubd80\ud130 \ub85c\uc9d3(logits)\uc744 \ucd94\ucd9c\ud558\ub294 \uacfc\uc815\uc744 \uc790\uc138\ud788 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. 1. CLIP \ubaa8\ub378 \uac1c\uc694 CLIP\uc740 \ub2e4\uc591\ud55c \uc774\ubbf8\uc9c0\uc640 \ud14d\uc2a4\ud2b8 \uc30d\uc73c\ub85c \uc0ac\uc804 \ud6c8\ub828\ub41c \ubaa8\ub378\uc785\ub2c8\ub2e4. \uc774 &hellip; <a href=\"https:\/\/atmokpo.com\/w\/29574\/\" class=\"more-link\">\ub354 \ubcf4\uae30<span class=\"screen-reader-text\"> &#8220;\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, CLIP \ucd94\ub860\uc5d0\uc11c \ub85c\uc9d3 \ucd94\ucd9c&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[30],"tags":[],"class_list":["post-29574","post","type-post","status-publish","format-standard","hentry","category-30"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, CLIP \ucd94\ub860\uc5d0\uc11c \ub85c\uc9d3 \ucd94\ucd9c - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/atmokpo.com\/w\/29574\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\ud5c8\uae45\ud398\uc774\uc2a4 \ud2b8\ub80c\uc2a4\ud3ec\uba38 \ud65c\uc6a9\uac15\uc88c, CLIP \ucd94\ub860\uc5d0\uc11c \ub85c\uc9d3 \ucd94\ucd9c - \ub77c\uc774\ube0c\uc2a4\ub9c8\ud2b8\" \/>\n<meta property=\"og:description\" content=\"\ub525\ub7ec\ub2dd\uacfc \uc790\uc5f0\uc5b4 \ucc98\ub9ac, \ucef4\ud4e8\ud130 \ube44\uc804 \ubd84\uc57c\uac00 \ubc1c\uc804\ud568\uc5d0 \ub530\ub77c \ub2e4\uc591\ud55c \ubaa8\ub378\ub4e4\uc774 \ub4f1\uc7a5\ud558\uc600\uc2b5\ub2c8\ub2e4. \uadf8 \uc911\uc5d0\uc11c\ub3c4 OpenAI\uc758 CLIP(Contrastive Language-Image Pretraining)\uc740 \ud14d\uc2a4\ud2b8\uc640 \uc774\ubbf8\uc9c0\ub97c \ub3d9\uc2dc\uc5d0 \uc774\ud574\ud558\uace0 \ud65c\uc6a9\ud560 \uc218 \uc788\ub294 \uac15\ub825\ud55c \ubaa8\ub378\uc785\ub2c8\ub2e4. \uc774 \uac15\uc88c\uc5d0\uc11c\ub294 Hugging Face Transformers \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec CLIP \ubaa8\ub378\uc744 \ud65c\uc6a9\ud558\uace0, \uadf8\ub85c\ubd80\ud130 \ub85c\uc9d3(logits)\uc744 \ucd94\ucd9c\ud558\ub294 \uacfc\uc815\uc744 \uc790\uc138\ud788 \uc124\uba85\ud558\uaca0\uc2b5\ub2c8\ub2e4. 1. 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