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# Table of Contents for Notebooks | ||
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Welcome to the Community Computer Vision Course! 🤗 | ||
Join us as we delve into the fundamentals and recent developments in computer vision. | ||
Our goal is to offer a beginner-friendly resource. | ||
Let's dive into the chapters for a wealth of knowledge! | ||
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| Chapter Title | Notebooks | Colabs | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 0 - Welcome | No Notebook | No Colab | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 1 - Fundamentals | No Notebook | No Colab | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 2 - Convolutional Neural Networks | [Transfer Learning with VGG19](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/transfer_learning_vgg19.ipynb) | [Transfer Learning with VGG](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/transfer_learning_vgg19.ipynb) | | ||
| | [Using ResNet with timm](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/timm_Resnet.ipynb) | [timm_Resnet](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%202%20-%20Convolutional%20Neural%20Networks/timm_Resnet.ipynb) | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 3 - Vision Transformers | [Detection Transformer (DETR)](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/DETR.ipynb) | [Detection Transformer (DETR)](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/DETR.ipynb) | | ||
| | [Fine-tuning Vision Transformers for Object Detection](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/Fine-tuning%20Vision%20Transformers%20for%20Object%20detection.ipynb) | [Fine-tuning Vision Transformers for Object Detection](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) | | ||
| | [Knowledge Distillation](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/KnowledgeDistillation.ipynb) | [Knowledge Distillation](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/KnowledgeDistillation.ipynb) | | ||
| | [LoRA Fine-tuning for Image Classification](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/LoRA-Image-Classification.ipynb) | [LoRA Fine-tuning for Image Classification](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/LoRA-Image-Classification.ipynb) | | ||
| | [Fine-tuning for Multilabel Image Classification](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/fine-tuning-multilabel-image-classification.ipynb) | [Fine-tuning for Multilabel Image Classification](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/fine-tuning-multilabel-image-classification.ipynb) | | ||
| | [Transfer Learning for Image Classification](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-image-classification.ipynb) | [Transfer Learning for Image Classification](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-image-classification.ipynb) | | ||
| | [Transfer Learning for Image Segmentation](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-segmentation.ipynb) | [Transfer Learning for Image Segmentation](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/transfer-learning-segmentation.ipynb) | | ||
| | [Swin Transformer](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/Swin.ipynb) | [Swin Transformer](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%203%20-%20Vision%20Transformers/Swin.ipynb) | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 4 - Multimodal Models | [Clip Crop](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/ClipCrop.ipynb) | [Clip Crop](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/ClipCrop.ipynb) | | ||
| | [Fine-tuning CLIP](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/Clip_finetune.ipynb) | [Fine-tuning CLIP](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/Clip_finetune.ipynb) | | ||
| | [Clustering with CLIP](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Clustering%20with%20CLIP.ipynb) | [Clustering with CLIP](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) | | ||
| | [Image Classification with CLIP](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image%20classification%20with%20CLIP.ipynb) | [Image Classification with CLIP](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) | | ||
| | [Image Retrieval with Prompts](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image_retrieval_with_prompts.ipynb) | [Image Retrieval with Prompts](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) | | ||
| | [Image Similarity](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image_similarity.ipynb) | [Image Similarity](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%204%20-%20Multimodal%20Models/CLIP%20and%20relatives/Image_similarity.ipynb) | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 5 - Generative Models | No Notebook | No Colab | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 6 - Basic CV Tasks | [Fine-tune SAM on Custom Dataset](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) | [Fine-tune SAM on Custom Dataset](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) | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 7 - Video and Video Processing | No Notebook | No Colab | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 8 - 3D Vision, Scene Rendering, and Reconstruction| No Notebook | No Colab | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 9 - Model Optimization | [Edge TPU](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/edge_tpu.ipynb) | [Edge TPU](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/edge_tpu.ipynb) | | ||
| | [ONNX](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/onnx.ipynb) | [ONNX](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/onnx.ipynb) | | ||
| | [OpenVINO](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/openvino.ipynb) | [OpenVINO](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/openvino.ipynb) | | ||
| | [Optimum](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/optimum.ipynb) | [Optimum](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/optimum.ipynb) | | ||
| | [TensorRT](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tensorrt.ipynb) | [TensorRT](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tensorrt.ipynb) | | ||
| | [TMO](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tmo.ipynb) | [TMO](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/tmo.ipynb) | | ||
| | [Torch](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/torch.ipynb) | [Torch](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%209%20-%20Model%20Optimization/torch.ipynb) | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 10 - Synthetic Data Creation | [Dataset Labeling with OWLv2](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/OWLV2_labeled_image_dataset_with_annotations.ipynb) | [Dataset Labeling with OWLv2](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) | | ||
| | [Generating Synthetic Lung Images](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/Synthetic_lung_images_hf_course.ipynb) | [Generating Synthetic Lung Images](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) | | ||
| | [BlenderProc Examples](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/blenderproc_examples.ipynb) | [BlenderProc Examples](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/blenderproc_examples.ipynb) | | ||
| | [Image Labeling with BLIP-2](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/image_labeling_BLIP_2.ipynb) | [Image Labeling with BLIP-2](https://colab.research.google.com/github/fariddinar/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/image_labeling_BLIP_2.ipynb) | | ||
| | [Synthetic Data Creation with SDXL Turbo](https://github.com/johko/computer-vision-course/blob/main/notebooks/Unit%2010%20-%20Synthetic%20Data%20Creation/synthetic_data_creation_sdxl_turbo.ipynb) | [Synthetic Data Creation with SDXL Turbo](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) | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 11 - Zero Shot Computer Vision | No Notebook | No Colab | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 12 - Ethics and Biases | No Notebook | No Colab | | ||
|--------------------------------------------------------|----------------------------------------------------------|----------| | ||
| Unit 13 - Outlook | No Notebook | No Colab | |
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