computer-vision-course/pr_381/en/_app/immutable/nodes/2.6a62dfdb.js

import{s as O,n as j,o as F}from"../chunks/scheduler.7bc62968.js";import{S as R,i as $,g as h,s as d,r as T,A as x,h as u,f as e,c as b,j as M,u as V,x as I,k as L,y as z,a as i,v as N,d as P,t as S,w as D}from"../chunks/index.2f8492b0.js";import{H as E,E as A}from"../chunks/EditOnGithub.2a9ce03a.js";function B(y){let n,f,c,p,r,g,a,C=`Here you can find a list of notebooks that contain accompanying and hands-on material to the chapters you find in this course.
Feel free to browse them at your own speed and interest.`,k,s,U='<thead><tr><th>Chapter Title</th> <th>Notebooks</th> <th>Colabs</th></tr></thead> <tbody><tr><td>Unit 0 - Welcome</td> <td>No Notebook</td> <td>No Colab</td></tr> <tr><td>Unit 1 - Fundamentals</td> <td>No Notebook</td> <td>No Colab</td></tr> <tr><td>Unit 2 - Convolutional Neural Networks</td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/transfer_learning_vgg19.ipynb" rel="nofollow">Transfer Learning with VGG19</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/transfer_learning_vgg19.ipynb" rel="nofollow">Transfer Learning with VGG</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/timm_Resnet.ipynb" rel="nofollow">Using ResNet with timm</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/timm_Resnet.ipynb" rel="nofollow">timm_Resnet</a></td></tr> <tr><td>Unit 3 - Vision Transformers</td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/DETR.ipynb" rel="nofollow">Detection Transformer (DETR)</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/DETR.ipynb" rel="nofollow">Detection Transformer (DETR)</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/Fine-tuning%20Vision%20Transformers%20for%20Object%20detection.ipynb" rel="nofollow">Fine-tuning Vision Transformers for Object Detection</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/Fine-tuning%20Vision%20Transformers%20for%20Object%20detection.ipynb" rel="nofollow">Fine-tuning Vision Transformers for Object Detection</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/KnowledgeDistillation.ipynb" rel="nofollow">Knowledge Distillation</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/KnowledgeDistillation.ipynb" rel="nofollow">Knowledge Distillation</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/LoRA-Image-Classification.ipynb" rel="nofollow">LoRA Fine-tuning for Image Classification</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/LoRA-Image-Classification.ipynb" rel="nofollow">LoRA Fine-tuning for Image Classification</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/fine-tuning-multilabel-image-classification.ipynb" rel="nofollow">Fine-tuning for Multilabel Image Classification</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/fine-tuning-multilabel-image-classification.ipynb" rel="nofollow">Fine-tuning for Multilabel Image Classification</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-image-classification.ipynb" rel="nofollow">Transfer Learning for Image Classification</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-image-classification.ipynb" rel="nofollow">Transfer Learning for Image Classification</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-segmentation.ipynb" rel="nofollow">Transfer Learning for Image Segmentation</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-segmentation.ipynb" rel="nofollow">Transfer Learning for Image Segmentation</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/Swin.ipynb" rel="nofollow">Swin Transformer</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/Swin.ipynb" rel="nofollow">Swin Transformer</a></td></tr> <tr><td>Unit 4 - Multimodal Models</td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/ClipCrop.ipynb" rel="nofollow">Clip Crop</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/ClipCrop.ipynb" rel="nofollow">Clip Crop</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/Clip_finetune.ipynb" rel="nofollow">Fine-tuning CLIP</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/Clip_finetune.ipynb" rel="nofollow">Fine-tuning CLIP</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Clustering%20with%20CLIP.ipynb" rel="nofollow">Clustering with CLIP</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Clustering%20with%20CLIP.ipynb" rel="nofollow">Clustering with CLIP</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image%20classification%20with%20CLIP.ipynb" rel="nofollow">Image Classification with CLIP</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image%20classification%20with%20CLIP.ipynb" rel="nofollow">Image Classification with CLIP</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image_retrieval_with_prompts.ipynb" rel="nofollow">Image Retrieval with Prompts</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image_retrieval_with_prompts.ipynb" rel="nofollow">Image Retrieval with Prompts</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image_similarity.ipynb" rel="nofollow">Image Similarity</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image_similarity.ipynb" rel="nofollow">Image Similarity</a></td></tr> <tr><td>Unit 5 - Generative Models</td> <td>No Notebook</td> <td>No Colab</td></tr> <tr><td>Unit 6 - Basic CV Tasks</td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%206%20-%20Basic%20CV%20Tasks/Fine_tune_SAM_(Segment_Anything_Model)_on_Custom_Dataset.ipynb" rel="nofollow">Fine-tune SAM on Custom Dataset</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%206%20-%20Basic%20CV%20Tasks/Fine_tune_SAM_(Segment_Anything_Model)_on_Custom_Dataset.ipynb" rel="nofollow">Fine-tune SAM on Custom Dataset</a></td></tr> <tr><td>Unit 7 - Video and Video Processing</td> <td><a href="https://github.com/DiwakarBasnet/computer-vision-course/blob/unit-7_Video_and_VideoProcessing/notebooks/Unit%207%20-%20Video%20and%20Video%20Processing/Vivit_Fine_tuned_Video_Classification.ipynb" rel="nofollow">Fine-tune ViViT for Video Classification</a></td> <td><a href="https://github.com/DiwakarBasnet/computervisioncourse/blob/unit7_Video_and_VideoProcessing/notebooks/Unit%207%20%20Video%20and%20Video%20Processing/Vivit_Fine_tuned_Video_Classification.ipynb" rel="nofollow">Fine-tune ViViT for Video Classification</a></td></tr> <tr><td>Unit 8 - 3D Vision, Scene Rendering, and Reconstruction</td> <td>No Notebook</td> <td>No Colab</td></tr> <tr><td>Unit 9 - Model Optimization</td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/edge_tpu.ipynb" rel="nofollow">Edge TPU</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/edge_tpu.ipynb" rel="nofollow">Edge TPU</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/onnx.ipynb" rel="nofollow">ONNX</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/onnx.ipynb" rel="nofollow">ONNX</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/openvino.ipynb" rel="nofollow">OpenVINO</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/openvino.ipynb" rel="nofollow">OpenVINO</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/optimum.ipynb" rel="nofollow">Optimum</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/optimum.ipynb" rel="nofollow">Optimum</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tensorrt.ipynb" rel="nofollow">TensorRT</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tensorrt.ipynb" rel="nofollow">TensorRT</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tmo.ipynb" rel="nofollow">TMO</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tmo.ipynb" rel="nofollow">TMO</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/torch.ipynb" rel="nofollow">Torch</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/torch.ipynb" rel="nofollow">Torch</a></td></tr> <tr><td>Unit 10 - Synthetic Data Creation</td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/OWLV2_labeled_image_dataset_with_annotations.ipynb" rel="nofollow">Dataset Labeling with OWLv2</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/OWLV2_labeled_image_dataset_with_annotations.ipynb" rel="nofollow">Dataset Labeling with OWLv2</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/Synthetic_lung_images_hf_course.ipynb" rel="nofollow">Generating Synthetic Lung Images</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/Synthetic_lung_images_hf_course.ipynb" rel="nofollow">Generating Synthetic Lung Images</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/blenderproc_examples.ipynb" rel="nofollow">BlenderProc Examples</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/blenderproc_examples.ipynb" rel="nofollow">BlenderProc Examples</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/image_labeling_BLIP_2.ipynb" rel="nofollow">Image Labeling with BLIP-2</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/image_labeling_BLIP_2.ipynb" rel="nofollow">Image Labeling with BLIP-2</a></td></tr> <tr><td></td> <td><a href="https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/synthetic_data_creation_sdxl_turbo.ipynb" rel="nofollow">Synthetic Data Creation with SDXL Turbo</a></td> <td><a href="https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/synthetic_data_creation_sdxl_turbo.ipynb" rel="nofollow">Synthetic Data Creation with SDXL Turbo</a></td></tr> <tr><td>Unit 11 - Zero Shot Computer Vision</td> <td>No Notebook</td> <td>No Colab</td></tr> <tr><td>Unit 12 - Ethics and Biases</td> <td>No Notebook</td> <td>No Colab</td></tr> <tr><td>Unit 13 - Outlook</td> <td>No Notebook</td> <td>No Colab</td></tr></tbody>',w,l,_,m,v;return r=new E({props:{title:"Table of Contents for Notebooks",local:"table-of-contents-for-notebooks",headingTag:"h1"}}),l=new A({props:{source:"https://github.com/johko/computer-vision-course/blob/main/chapters/en/unit0/welcome/TableOfContents.mdx"}}),{c(){n=h("meta"),f=d(),c=h("p"),p=d(),T(r.$$.fragment),g=d(),a=h("p"),a.textContent=C,k=d(),s=h("table"),s.innerHTML=U,w=d(),T(l.$$.fragment),_=d(),m=h("p"),this.h()},l(o){const t=x("svelte-u9bgzb",document.head);n=u(t,"META",{name:!0,content:!0}),t.forEach(e),f=b(o),c=u(o,"P",{}),M(c).forEach(e),p=b(o),V(r.$$.fragment,o),g=b(o),a=u(o,"P",{"data-svelte-h":!0}),I(a)!=="svelte-183gnl1"&&(a.textContent=C),k=b(o),s=u(o,"TABLE",{"data-svelte-h":!0}),I(s)!=="svelte-1eqlns6"&&(s.innerHTML=U),w=b(o),V(l.$$.fragment,o),_=b(o),m=u(o,"P",{}),M(m).forEach(e),this.h()},h(){L(n,"name","hf:doc:metadata"),L(n,"content",G)},m(o,t){z(document.head,n),i(o,f,t),i(o,c,t),i(o,p,t),N(r,o,t),i(o,g,t),i(o,a,t),i(o,k,t),i(o,s,t),i(o,w,t),N(l,o,t),i(o,_,t),i(o,m,t),v=!0},p:j,i(o){v||(P(r.$$.fragment,o),P(l.$$.fragment,o),v=!0)},o(o){S(r.$$.fragment,o),S(l.$$.fragment,o),v=!1},d(o){o&&(e(f),e(c),e(p),e(g),e(a),e(k),e(s),e(w),e(_),e(m)),e(n),D(r,o),D(l,o)}}}const G='{"title":"Table of Contents for Notebooks","local":"table-of-contents-for-notebooks","sections":[],"depth":1}';function H(y){return F(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class q extends R{constructor(n){super(),$(this,n,H,B,O,{})}}export{q as component};