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种子名称： GetFreeCourses.Co-Udemy-Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4
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文件数目： 228个文件
文件大小： 12.45 GB
收录时间： 2023-8-6 06:42
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GetFreeCourses.Co-Udemy-Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4.torrent

1. Introduction/1. Course Introduction.mp482.94MB

1. Introduction/2. Course Overview.mp463.77MB

1. Introduction/3. What Makes Computer Vision Hard.mp446.16MB

1. Introduction/4. What are Images.mp444.22MB

10. OpenCV - Working With Video/1. Using Your Webcam and Creating a Live Sketch of Yourself.mp466.54MB

10. OpenCV - Working With Video/2. Opening Video Files in OpenCV.mp433.99MB

10. OpenCV - Working With Video/3. Saving or Recording Videos in OpenCV.mp435.77MB

10. OpenCV - Working With Video/4. Video Streams and CCTV - RTSP and IP.mp442.09MB

10. OpenCV - Working With Video/5. Auto Reconnect to Video Streams.mp436.24MB

10. OpenCV - Working With Video/6. Capturing Video using Screenshots.mp446.3MB

10. OpenCV - Working With Video/7. Importing YouTube Videos into OpenCV.mp464.89MB

11. Deep Learning in Computer Vision Introduction/1. Introduction to Convolution Neural Networks.mp415.87MB

11. Deep Learning in Computer Vision Introduction/10. Fully Connected Layers.mp411.33MB

11. Deep Learning in Computer Vision Introduction/11. Softmax.mp48.88MB

11. Deep Learning in Computer Vision Introduction/12. Putting Together Your Convolutional Neural Network.mp429.38MB

11. Deep Learning in Computer Vision Introduction/13. Parameter Counts in CNNs.mp423.83MB

11. Deep Learning in Computer Vision Introduction/14. Why CNNs Work So Well On Images.mp420.51MB

11. Deep Learning in Computer Vision Introduction/15. Training a CNN.mp427.38MB

11. Deep Learning in Computer Vision Introduction/16. Loss Functions.mp424.89MB

11. Deep Learning in Computer Vision Introduction/17. Backpropagation.mp429MB

11. Deep Learning in Computer Vision Introduction/18. Gradient Descent.mp432.94MB

11. Deep Learning in Computer Vision Introduction/19. Optimisers and Learning Rate Schedules.mp440.92MB

11. Deep Learning in Computer Vision Introduction/2. Convolutions.mp433.85MB

11. Deep Learning in Computer Vision Introduction/20. Deep Learning CNN Recap.mp436.39MB

11. Deep Learning in Computer Vision Introduction/21. Deep Learning History.mp457.52MB

11. Deep Learning in Computer Vision Introduction/22. Deep Learning Libraries Overview.mp459.04MB

11. Deep Learning in Computer Vision Introduction/3. Feature Detectors.mp423.87MB

11. Deep Learning in Computer Vision Introduction/4. 3D Convolutions and Color Images.mp416.63MB

11. Deep Learning in Computer Vision Introduction/5. Kernel Size and Depth.mp413.67MB

11. Deep Learning in Computer Vision Introduction/6. Padding.mp414.17MB

11. Deep Learning in Computer Vision Introduction/7. Stride.mp417.14MB

11. Deep Learning in Computer Vision Introduction/8. Activation Functions.mp421.74MB

11. Deep Learning in Computer Vision Introduction/9. Pooling.mp423.42MB

12. Building CNNs in PyTorch/1. Importing Required Libraries.mp447.72MB

12. Building CNNs in PyTorch/2. Transformation Pipeline.mp429.55MB

12. Building CNNs in PyTorch/3. Inspect and Visualise Data.mp470.58MB

12. Building CNNs in PyTorch/4. Data Loaders.mp429.9MB

12. Building CNNs in PyTorch/5. Building our Model.mp4102.34MB

12. Building CNNs in PyTorch/6. Optimisers and Loss Function.mp414.88MB

12. Building CNNs in PyTorch/7. Training Your Model.mp496.07MB

12. Building CNNs in PyTorch/8. Saving Model and Displaying Results.mp449.27MB

12. Building CNNs in PyTorch/9. Plot and Visualize Your Results.mp425.81MB

13. Building CNNs in TensorFlow with Keras/1. Loading Data.mp426.69MB

13. Building CNNs in TensorFlow with Keras/2. View and Inspect Data.mp429.51MB

13. Building CNNs in TensorFlow with Keras/3. Preprocessing Our Data.mp433.53MB

13. Building CNNs in TensorFlow with Keras/4. Constructing the CNN.mp464.47MB

13. Building CNNs in TensorFlow with Keras/5. Training the Model.mp445.45MB

13. Building CNNs in TensorFlow with Keras/6. Plotting the Training Results.mp436.39MB

13. Building CNNs in TensorFlow with Keras/7. Saving and Loading and Visualising Results.mp475.55MB

14. Assessing Model Performance/1. Deep Learning Libraries PyTorch vs Keras Review.mp468.2MB

14. Assessing Model Performance/2. Assessing Model Performance.mp422.58MB

14. Assessing Model Performance/3. Confusion Matrix and Classification Report.mp467.59MB

14. Assessing Model Performance/4. Keras Viewing Misclassifications.mp464.91MB

14. Assessing Model Performance/5. Keras - Confusion Matrix and Classification Report.mp443.42MB

14. Assessing Model Performance/6. PyTorch Viewing Misclassifications.mp451.37MB

14. Assessing Model Performance/7. PyTorch - Confusion Matrix and Misclassifications.mp429.25MB

15. Improving Models and Advanced CNN Design/1. What is Overfitting and Generalisation.mp444.04MB

15. Improving Models and Advanced CNN Design/10. Training a Fashion Classifider (FNIST) with Regularization using Keras.mp496.01MB

15. Improving Models and Advanced CNN Design/11. Training a Fashion Classifider (FNIST) with no Regularization using PyTorch.mp464.16MB

15. Improving Models and Advanced CNN Design/12. Training a Fashion Classifider (FNIST) with Regularization using PyTorch.mp4108.05MB

15. Improving Models and Advanced CNN Design/2. Introduction to Regularization.mp48.02MB

15. Improving Models and Advanced CNN Design/3. Drop Out.mp413.06MB

15. Improving Models and Advanced CNN Design/4. L1 and L2 Regularization.mp415.62MB

15. Improving Models and Advanced CNN Design/5. Data Augmentation.mp431.9MB

15. Improving Models and Advanced CNN Design/6. Early Stopping.mp412.98MB

15. Improving Models and Advanced CNN Design/7. Batch Normalization.mp423.84MB

15. Improving Models and Advanced CNN Design/8. When Do We Use Regularization.mp411.57MB

15. Improving Models and Advanced CNN Design/9. Training a Fashion Classifider (FNIST) with no Regularization using Keras.mp482.69MB

16. Visualizing What CNN's Learn/1. Visualizing CNN Filters or Feature Maps.mp420.47MB

16. Visualizing What CNN's Learn/2. Visualising Filter Activations.mp435.54MB

16. Visualizing What CNN's Learn/3. Keras Filter Visualization and Activations.mp4107.23MB

16. Visualizing What CNN's Learn/4. Maximizing Filters.mp423.06MB

16. Visualizing What CNN's Learn/5. Class Maximization.mp430.13MB

16. Visualizing What CNN's Learn/6. Filter and Class Maximization.mp4156.06MB

16. Visualizing What CNN's Learn/7. Grad-CAM Visualize What Influences Your Model.mp414.91MB

16. Visualizing What CNN's Learn/8. Grad-CAM Plus.mp480.37MB

17. Advamced Convolutional Neural Networks/1. History and Evolution of Convolutional Neural Networks.mp49.13MB

17. Advamced Convolutional Neural Networks/10. EfficientNet.mp424.99MB

17. Advamced Convolutional Neural Networks/11. DenseNet.mp432.02MB

17. Advamced Convolutional Neural Networks/12. The ImageNet Dataset.mp429.53MB

17. Advamced Convolutional Neural Networks/2. LeNet.mp418.67MB

17. Advamced Convolutional Neural Networks/3. AlexNet.mp417.53MB

17. Advamced Convolutional Neural Networks/4. VGG16 and VGG19.mp423.05MB

17. Advamced Convolutional Neural Networks/5. ResNets.mp417.8MB

17. Advamced Convolutional Neural Networks/6. Why ResNets Work So Well.mp423.29MB

17. Advamced Convolutional Neural Networks/7. MobileNetV1 and V2.mp443.82MB

17. Advamced Convolutional Neural Networks/8. InceptionV3.mp423.42MB

17. Advamced Convolutional Neural Networks/9. SqueezeNet.mp423.18MB

18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/1. Implementing LeNet and AlexNet in Keras.mp4139.34MB

18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/2. Loading Pre-trained Networks in PyTorch (ResNets, DenseNets, MobileNET, VGG19).mp4153.77MB

18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/3. Loading Pre-trained Networks in Keras (ResNets, DenseNets, MobileNET, VGG19).mp4111.38MB

18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/4. The Top-N or Rank-N Accuracy Metric.mp412.42MB

18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/5. Getting the Rank-N Accuracy in PyTorch.mp497.92MB

18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/6. Getting the Rank-N Accuracy in Keras.mp455.85MB

19. Using Callbacks in Keras and PyTorch/1. What are Callbacks.mp416.18MB

19. Using Callbacks in Keras and PyTorch/2. Cats vs Dogs Classifier using Callbacks in PyTorch.mp4114.98MB

19. Using Callbacks in Keras and PyTorch/3. Cats vs Dogs Classifier using Callbacks in Keras.mp4114.72MB

2. Download Code and Setup Colab/2. Setup - Download Code and Configure Colab.mp422.57MB

20. PyTorch Lightning/1. Introduction to PyTorch Lightning.mp438.24MB

20. PyTorch Lightning/2. Lightning Setup and Class.mp462.15MB

20. PyTorch Lightning/3. Auto Batch and Learning Rate Selection plus Tensorboards.mp4106.56MB

20. PyTorch Lightning/4. PyTorch Lightning Calls, Saving, Inference.mp471.64MB

20. PyTorch Lightning/5. Training on Multiple GPU, Profiling and TPUs.mp464.15MB

21. Transfer Learning and Fine Tuning/1. Transfer Learning Introduction.mp431.89MB

21. Transfer Learning and Fine Tuning/2. Transfer Learning in PyTorch Lightning.mp455.89MB

21. Transfer Learning and Fine Tuning/3. Transfer Learning and Fine Tuning with Keras.mp496MB

21. Transfer Learning and Fine Tuning/4. Keras Feature Extraction.mp4131.81MB

21. Transfer Learning and Fine Tuning/5. PyTorch Fine Tuning.mp4121.59MB

21. Transfer Learning and Fine Tuning/6. PyTorch Transfer Learning and Freezing Network Layers.mp428.81MB

21. Transfer Learning and Fine Tuning/7. PyTorch Feature Extraction.mp4103.4MB

22. Google DeepStream and Neural Style Transfer/1. Introduction to Google DeepDream Visualizations.mp439.87MB

22. Google DeepStream and Neural Style Transfer/2. Google DeepDream in Keras.mp472.85MB

22. Google DeepStream and Neural Style Transfer/3. Google DeepDream in PyTorch.mp458.32MB

22. Google DeepStream and Neural Style Transfer/4. Introduction to Neural Style Transfer.mp449.97MB

22. Google DeepStream and Neural Style Transfer/5. Neural Style Transfer in Keras.mp4141.08MB

22. Google DeepStream and Neural Style Transfer/6. Neural Style Transfer in PyTorch.mp457.9MB

23. Autoencoders/1. Introduction to Autoencoders.mp425.37MB

23. Autoencoders/2. Autoencoders in Keras.mp480.55MB

23. Autoencoders/3. Autoencoders in PyTorch.mp466.04MB

24. Generative Adversarial Networks (GANs)/1. Introduction to GANs.mp443.57MB

24. Generative Adversarial Networks (GANs)/2. How Do GANs Work.mp426.55MB

24. Generative Adversarial Networks (GANs)/3. Training GANs.mp449.27MB

24. Generative Adversarial Networks (GANs)/4. Use Cases for GANs.mp4108.13MB

24. Generative Adversarial Networks (GANs)/5. Keras DCGAN with MNIST.mp4100.92MB

24. Generative Adversarial Networks (GANs)/6. PyTorch GANs.mp465.41MB

24. Generative Adversarial Networks (GANs)/7. Super Resolution GAN.mp4102.24MB

24. Generative Adversarial Networks (GANs)/8. AnimeGAN.mp434.77MB

24. Generative Adversarial Networks (GANs)/9. ArcaneGAN.mp431.55MB

25. Siamese Network/1. Introduction to Siamese Networks.mp428.8MB

25. Siamese Network/2. Training Siamese Networks.mp413.34MB

25. Siamese Network/3. Siamese Networks in Keras.mp473.01MB

25. Siamese Network/4. Siamese Networks in PyTorch.mp467.92MB

26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/1. Face Recognition Overview.mp432.03MB

26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/2. Facial Similarity Keras VGGFace.mp456.62MB

26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/3. Face Recognition Keras One Shot Learning and Friends.mp480.6MB

26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/4. Face Recognition PyTorch FaceNet.mp451.29MB

26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/5. DeepFace - Age, Gender, Emotion, Ethnicity and Face Recognition.mp4132.36MB

27. Object Detection/1. Object Detection.mp465.25MB

27. Object Detection/2. History of Object Detectors.mp452.87MB

27. Object Detection/3. Intersection Over Union.mp417.44MB

27. Object Detection/4. Mean Average Precision.mp445.71MB

27. Object Detection/5. Non Maximum Suppression.mp419.55MB

27. Object Detection/6. R-CNNs, Fast R-CNNs and Faster R-CNNs.mp441.2MB

27. Object Detection/7. Single Shot Detectors (SSDs).mp430.93MB

28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/1. Introduction to YOLO.mp433.48MB

28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/2. How YOLO Works.mp429.31MB

28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/3. Training YOLO.mp425.03MB

28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/4. YOLO Evolution.mp424.18MB

28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/5. EfficientDet.mp430.74MB

28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/6. Detectron2.mp440.59MB

29. Gun Detector - Scaled-YoloV4/1. Gun Detector - Scaled-YoloV4.mp4128.47MB

3. OpenCV - Image Operations/1. Getting Started with OpenCV4.mp494.74MB

3. OpenCV - Image Operations/10. Dilation, Erosion and Edge Detection.mp479.96MB

3. OpenCV - Image Operations/2. Grayscaling Images.mp452.52MB

3. OpenCV - Image Operations/3. Colour Spaces - RGB and HSV.mp468.3MB

3. OpenCV - Image Operations/4. Drawing on Images.mp452.03MB

3. OpenCV - Image Operations/5. Transformations - Translations and Rotations.mp467.22MB

3. OpenCV - Image Operations/6. Scaling, Re-sizing, Interpolations and Cropping.mp4114.94MB

3. OpenCV - Image Operations/7. Arithmetic and Bitwise Operations.mp466.14MB

3. OpenCV - Image Operations/8. Convolutions, Blurring and Sharpening Images.mp458.96MB

3. OpenCV - Image Operations/9. Thresholding, Binarization & Adaptive Thresholding.mp4117.18MB

30. Mask Detector TFODAPI MobileNetV2_SSD/1. Mask Detector TFODAPI MobileNetV2_SSD.mp481.18MB

31. Sign Language Detector TFODAPI EfficentDet/1. Sign Language Detector TFODAPI EfficentDet.mp485.17MB

32. Pothole Detector - TinyYOLOv4/1. Pothole Detector - TinyYOLOv4.mp459.49MB

33. Mushroom Detector Detectron2/1. Mushroom Detector Detectron2.mp464.96MB

34. Website Region Detector YOLOv4 Darknet/1. Website Region Detector YOLOv4 Darknet.mp449.63MB

35. Drone Maritime Detector R-CNN/1. Drone Maritime Detector R-CNN.mp456.86MB

36. Chess Piece YOLOv3/1. Chess Piece YOLOv3.mp442.66MB

37. Bloodcell Detector YOLOv5/1. Bloodcell Detector YOLOv5.mp458.54MB

38. Hard Hat Detector EfficentDet/1. Hard Hat Detector EfficentDet.mp430.6MB

39. Plant Doctor Detector YOLOv5/1. Plant Doctor Detector YOLOv5.mp471.12MB

4. OpenCV - Image Segmentation/1. Contours - Drawing, Hierarchy and Modes.mp4117.12MB

4. OpenCV - Image Segmentation/2. Moments, Sorting, Approximating and Matching Contours.mp4139.77MB

4. OpenCV - Image Segmentation/3. Line, Circle and Blob Detection.mp456.57MB

4. OpenCV - Image Segmentation/4. Counting Circles, Ellipses and Finding Waldo with Template Matching.mp468.51MB

4. OpenCV - Image Segmentation/5. Finding Corners.mp436.53MB

40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/1. Introduction to Deep Segmentation.mp478.17MB

40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/2. Image Segmentation Keras UNET SegNet.mp473.05MB

40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/3. PyTorch DeepLabV3.mp460.15MB

40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/4. Mask-RCNN Tensorflow Matterport.mp461.72MB

40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/5. Detectron2 Mask R-CNN.mp470.89MB

40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/6. Train Mask R-CNN Shapes Dataset.mp454.97MB

41. Body Pose Estimation/1. Body Pose Estimation.mp446.21MB

42. Tracking with DeepSORT/1. DeepSORT Introduction.mp459.56MB

42. Tracking with DeepSORT/2. DeepSORT with YOLOv5.mp458.34MB

43. Deep Fakes/1. Creating a Deep Fake.mp458.67MB

44. Vision Transformers - ViTs/1. Introduction to Vision Transformers.mp426.74MB

44. Vision Transformers - ViTs/2. Vision Transformer in Detail with PyTorch.mp476.24MB

44. Vision Transformers - ViTs/3. Vision Transformers in Keras.mp447.99MB

45. BiT BigTransfer Classifier Keras/1. BiT BigTransfer Classifier Keras.mp458.62MB

46. Depth Estimation/1. Depth Estimation Project.mp476.77MB

47. Image Similarity using Metric Learning/1. Image Similarity using Metric Learning.mp456.01MB

48. Image Captioning with Keras/1. Image Captioning with Keras.mp496.09MB

49. Video Classification usign CNN+RNN/1. Video Classification usign CNN+RNN.mp456.76MB

5. OpenCV - Haar Cascade Classifiers/1. Face and Eye Detection with Haar Cascade Classifiers.mp4110.22MB

5. OpenCV - Haar Cascade Classifiers/2. Vehicle and Pedestrian Detection.mp486.09MB

50. Video Classification with Transformers/1. Video Classification with Transformers.mp449.24MB

51. Point Cloud Classification PointNet/1. Point Cloud Classification PointNet.mp459.53MB

52. Point Cloud Segmentation Using PointNet/1. Point Cloud Segmentation Using PointNet.mp492.05MB

53. Medical Project - X-Ray Pneumonia Prediction/1. X-Ray Pneumonia Prediction.mp461.41MB

54. Medical Project - 3D CT Scan Classification/1. 3D CT Scan Classification.mp460.32MB

55. Low Light Image Enhancement MIRNet/1. Low Light Image Enhancement MIRNet.mp491.55MB

56. Deploy your CV App using Flask RestFUL API & Web App/1. Flask RestFUL API.mp454.94MB

56. Deploy your CV App using Flask RestFUL API & Web App/2. Flask Web App.mp437.26MB

57. OCR Captcha Cracker/1. OCR Captcha Cracker.mp446.38MB

6. OpenCV - Image Analysis and Transformation/1. Perspective Transforms.mp464.42MB

6. OpenCV - Image Analysis and Transformation/2. Histograms and K-Means Clustering for Dominant Colors.mp479.89MB

6. OpenCV - Image Analysis and Transformation/3. Comparing Images MSE and Structual Similarity.mp442.1MB

6. OpenCV - Image Analysis and Transformation/4. Filtering on Colour.mp440.87MB

6. OpenCV - Image Analysis and Transformation/5. Watershed Algorithm Marker-Dased Image Segmentation.mp443.33MB

6. OpenCV - Image Analysis and Transformation/6. Background and Foreground Subtraction.mp466.11MB

7. OpenCV - Motion and Object Tracking/1. Motion Tracking with Mean Shift and CAMSHIFT.mp471.05MB

7. OpenCV - Motion and Object Tracking/2. Object Tracking with Optical Flow.mp495.15MB

7. OpenCV - Motion and Object Tracking/3. Simple Object Tracking by Color.mp448.62MB

8. OpenCV - Facial Landmark Detection & Face Swaps/1. Facial Landmark Detection with Dlib.mp437.54MB

8. OpenCV - Facial Landmark Detection & Face Swaps/2. Face Swapping with Dlib.mp449.4MB

9. OpenCV Projects/1. Tilt Shift Effects.mp459.03MB

9. OpenCV Projects/10. Add and Remove Noise and Fix Contrast with Histogram Equalization.mp488.97MB

9. OpenCV Projects/11. Detect Blur in Images.mp439.57MB

9. OpenCV Projects/12. Facial Recognition.mp484.31MB

9. OpenCV Projects/2. GrabCut Algorithm for Background Removal.mp445.65MB

9. OpenCV Projects/3. OCR with PyTesseract and EasyOCR (Text Detection).mp4119.5MB

9. OpenCV Projects/4. Barcode, QR Generation and Reading.mp468.68MB

9. OpenCV Projects/5. YOLOv3 in OpenCV.mp479.52MB

9. OpenCV Projects/6. Neural Style Transfer with OpenCV.mp4143.03MB

9. OpenCV Projects/7. SSDs in OpenCV.mp451.82MB

9. OpenCV Projects/8. Colorize Black and White Photos using a Caffe Model in OpenCV.mp480.98MB

9. OpenCV Projects/9. Inpainting to Restore Damaged Photos.mp428.48MB