Udemy - Modern Computer Vision & Deep Learning with Python & PyTorch (12.2024)

09. Overview of YOLO Family for Object Detection/01. Overview of YOLO Family.mp4

05. 1. Image Classification Task of Computer Vision/02. Image Classification with Deep Convolutional Neural Networks using Python.mp4

20. Implementation, Optimization and Training Of Segmentation Models/01. Implement Segmentation Models (UNet, PSPNet, DeepLab, PAN, and UNet++).mp4

07. Transfer Learning for Image Classification/assets/Classification-Dataset.zip

25. Training, Evaluating and Visualizing Instance Segmentation on Custom Dataset/02. Train, Evaluate Instance Segmentation Model & Visualizing Results on Custom Data.mp4

04. Computer Vision and Deep Convolutional Neural Networks/03. Coding Convolutional Neural Network Architecture from Scratch.mp4

12. Detectron2 for Ojbect Detection/01. Detectron2 for Ojbect Detection with PyTorch.mp4

13. Training, Evaluating and Visualizing Object Detection on Custom Dataset/03. Train, Evaluate Object Detection Models & Visualizing Results on Custom Dataset.mp4

03. Deep Learning for Computer Vision/01. Basics of Deep Learning for Computer Vision.mp4

11. Overview of RCNN Family for Object Detection/01. Overview of RCNN Family for Object Detection.mp4

15. 3. Semantic Segmentation Task Of Computer Vision/02. Semantic Segmentation Real-World Applications.mp4

12. Detectron2 for Ojbect Detection/02. Perform Object Detection using Detectron2 Pretrained Models.mp4

04. Computer Vision and Deep Convolutional Neural Networks/06. Calculate Accuracy, Precision, Recall and Visualize Confusion Matrix.mp4

21. Test Models and Visualize Segmentation Results/01. Test Models and Calculate IOU,Pixel Accuracy,Fscore.mp4

17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/04. Data Loading with PyTorch Customized Dataset Class.mp4

02. What is Computer Vision & its Applications/01. Introduction to Computer Vision and its Real-world Applications.mp4

10. Video Object Detection in Real-time/04. Testing YOLO8 on Videos and Images.mp4

13. Training, Evaluating and Visualizing Object Detection on Custom Dataset/01. Custom Dataset for Object Detection.mp4

25. Training, Evaluating and Visualizing Instance Segmentation on Custom Dataset/01. Custom Dataset for Instance Segmentation.mp4

21. Test Models and Visualize Segmentation Results/03. Visualize Segmentation Results and Generate RGB Segmented Map.mp4

10. Video Object Detection in Real-time/01. Vehicles Detection Custom Dataset.mp4

17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/06. Data Augmentation using Albumentations with Different Transformations.mp4

18. Performance Metrics (IOU) For Segmentation Models Evaluation/01. Performance Metrics (IOU, Pixel Accuracy, Precision, Recall, Fscore).mp4

10. Video Object Detection in Real-time/02. Setting HyperParameters for YOLO8.mp4

27. Video Instance Segmentation/05. Training Video Instance Segmentation Model.mp4

27. Video Instance Segmentation/02. YOLO8 for Video Instance Segmentation.mp4

10. Video Object Detection in Real-time/05. Calculate Performance Metrics (Precision, Recall, Mean Average Precision mAP).mp4

04. Computer Vision and Deep Convolutional Neural Networks/01. Computer Vision using Convolutional Neural Networks (CNN).mp4

20. Implementation, Optimization and Training Of Segmentation Models/05. Training of Segmentation Models.mp4

17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/02. Data Annotations Tool for Semantic Segmentation.mp4

07. Transfer Learning for Image Classification/04. FineTuning Deep ResNet Model.mp4

27. Video Instance Segmentation/07. Testing Segmentation Model on Videos.mp4

10. Video Object Detection in Real-time/03. Training YOLO8 on Vehicles Dataset.mp4

17. Segmentation Datasets, Annotations, Data Augmentation & Data Loading/01. Datasets for Semantic Segmentation.mp4

06. Pretrained Models for Single and Multi-Label Image Classification/07. Multi-Label Image Classification using Deep Learning Models.mp4

10. Video Object Detection in Real-time/assets/VehiclesDetection-Dataset.zip

27. Video Instance Segmentation/assets/TestVideos.zip

09. Overview of YOLO Family for Object Detection/03. YOLOv8 and its Architecture.mp4

04. Computer Vision and Deep Convolutional Neural Networks/05. Training Convolutional Neural Network from Scratch.mp4

13. Training, Evaluating and Visualizing Object Detection on Custom Dataset/assets/balloon.zip

14. Complete Code and Custom Dataset for Object Detection/assets/balloon.zip

26. Complete Code and Custom Dataset for Instance Segmentation/assets/balloon.zip

07. Transfer Learning for Image Classification/08. Model Optimization, Training and Results Visualization.mp4

27. Video Instance Segmentation/01. Intro to Video Instance Segmentation.mp4

19. Encoders and Decoders For Segmentation In PyTorch/01. Transfer Learning And Pretrained Deep Resnet Architecture.mp4

07. Transfer Learning for Image Classification/02. Dataset, Data Augmentation, and Dataloaders.mp4

04. Computer Vision and Deep Convolutional Neural Networks/04. Convolutional Neural Networks HyperParameters Optimization.mp4

15. 3. Semantic Segmentation Task Of Computer Vision/01. Semantic Segmentation Task Of Computer Vision with Pytorch and Python.mp4

10. Video Object Detection in Real-time/06. Export and Deploy the Model.mp4

04. Computer Vision and Deep Convolutional Neural Networks/02. Setting-up Google Colab for Writing Python Code.mp4