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Название Deep learning for image segmentation using Tensorflow 2
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001 Brief intro to Tensorflow 2 object detection API.en.srt 1.88Кб
001 Brief intro to Tensorflow 2 object detection API.mp4 7.87Мб
001 Choosing a dataset.en.srt 671б
001 Choosing a dataset.mp4 5.52Мб
001 Conclusion and next steps for you.en.srt 1.93Кб
001 Conclusion and next steps for you.mp4 9.13Мб
001 Course outline.en.srt 4.93Кб
001 Course outline.mp4 22.87Мб
001 Quick introduction to Mask RCNN.en.srt 2.38Кб
001 Quick introduction to Mask RCNN.mp4 12.32Мб
001 Training on premise VS training on the cloud.en.srt 1.79Кб
001 Training on premise VS training on the cloud.mp4 5.15Мб
001 What is cloud computing and what is AI Platform_ (optional).en.srt 5.89Кб
001 What is cloud computing and what is AI Platform_ (optional).mp4 115.93Мб
001 What is image segmentation_.en.srt 4.78Кб
001 What is image segmentation_.mp4 22.23Мб
002 Code for this course.en.srt 978б
002 Code for this course.mp4 6.04Мб
002 Creating a Google Cloud account.en.srt 6.03Кб
002 Creating a Google Cloud account.mp4 36.26Мб
002 Downloading Mask RCNN pretrained model.en.srt 3.47Кб
002 Downloading Mask RCNN pretrained model.mp4 24.17Мб
002 Linux - Exploring the dataset - Part 1.en.srt 4.66Кб
002 Linux - Exploring the dataset - Part 1.mp4 38.69Мб
002 Linux installation _ How to install tensorflow 2 with GPU support (part 1).en.srt 10.58Кб
002 Linux installation _ How to install tensorflow 2 with GPU support (part 1).mp4 83.73Мб
002 Mask RCNN as an extension of Faster RCNN.en.srt 2.67Кб
002 Mask RCNN as an extension of Faster RCNN.mp4 12.92Мб
002 Why deep learning for image segmentation_.en.srt 1.15Кб
002 Why deep learning for image segmentation_.mp4 6.05Мб
003 Downloading Google Cloud SDK.en.srt 6.08Кб
003 Downloading Google Cloud SDK.mp4 50.64Мб
003 Finding the right configuration file.en.srt 1.73Кб
003 Finding the right configuration file.mp4 13.24Мб
003 High level overview of Faster RCNN (optional).en.srt 3.69Кб
003 High level overview of Faster RCNN (optional).mp4 11.90Мб
003 Linux - Exploring the dataset - Part 2.en.srt 6.44Кб
003 Linux - Exploring the dataset - Part 2.mp4 44.28Мб
003 Linux installation _ How to install tensorflow 2 with GPU support (part 2).en.srt 13.16Кб
003 Linux installation _ How to install tensorflow 2 with GPU support (part 2).mp4 102.68Мб
003 Types of image segmentation.en.srt 3.62Кб
003 Types of image segmentation.mp4 16.34Мб
004 Exploring the configuration file.en.srt 5.21Кб
004 Exploring the configuration file.mp4 29.84Мб
004 High level overview of Mask RCNN.en.srt 1.93Кб
004 High level overview of Mask RCNN.mp4 8.10Мб
004 Linux installation _ How to install tensorflow 2 object detection API.en.srt 7.43Кб
004 Linux installation _ How to install tensorflow 2 object detection API.mp4 54.44Мб
004 Setting up a new project on google cloud platform.en.srt 3.08Кб
004 Setting up a new project on google cloud platform.mp4 18.40Мб
004 Windows - Exploring the dataset.en.srt 6.24Кб
004 Windows - Exploring the dataset.mp4 39.18Мб
005 Annotating a custom dataset.en.srt 19.00Кб
005 Annotating a custom dataset.mp4 218.51Мб
005 Creating a google bucket and uploading data to it.en.srt 7.48Кб
005 Creating a google bucket and uploading data to it.mp4 40.87Мб
005 Modifying the configuration file - Part 1.en.srt 14.47Кб
005 Modifying the configuration file - Part 1.mp4 84.81Мб
005 Steps to build an image segmentation model with Mask RCNN for a custom dataset.en.srt 2.67Кб
005 Steps to build an image segmentation model with Mask RCNN for a custom dataset.mp4 14.28Мб
005 Windows installation _ Installing miniconda.en.srt 2.59Кб
005 Windows installation _ Installing miniconda.mp4 14.98Мб
006 From multiple annotation files to one annotation file.en.srt 8.16Кб
006 From multiple annotation files to one annotation file.mp4 55.64Мб
006 Modifying the configuration file - Part 2.en.srt 3.36Кб
006 Modifying the configuration file - Part 2.mp4 21.55Мб
006 Preparing our config file for training on google cloud.en.srt 5.71Кб
006 Preparing our config file for training on google cloud.mp4 50.69Мб
006 Windows installation _ Create virtual environment.en.srt 2.23Кб
006 Windows installation _ Create virtual environment.mp4 11.36Мб
007 Checking connection to google cloud from within our local machine.en.srt 3.79Кб
007 Checking connection to google cloud from within our local machine.mp4 20.99Мб
007 Running the training locally.en.srt 9.63Кб
007 Running the training locally.mp4 58.94Мб
007 Transforming our dataset to tfrecord format.en.srt 8.08Кб
007 Transforming our dataset to tfrecord format.mp4 56.02Мб
007 Windows installation _ Installing tensorflow 2 object detection API.en.srt 15.64Кб
007 Windows installation _ Installing tensorflow 2 object detection API.mp4 107.34Мб
008 Exploring the training command.en.srt 6.81Кб
008 Exploring the training command.mp4 36.86Мб
008 Windows installation _ Installing tensorflow with GPU support.en.srt 25.31Кб
008 Windows installation _ Installing tensorflow with GPU support.mp4 205.30Мб
009 Running the training for Mask RCNN model.en.srt 4.24Кб
009 Running the training for Mask RCNN model.mp4 27.95Мб
010 Checking the progress of the training job on google ai platform.en.srt 3.95Кб
010 Checking the progress of the training job on google ai platform.mp4 28.88Мб
011 Running the evaluation for Mask RCNN model during the training.en.srt 7.69Кб
011 Running the evaluation for Mask RCNN model during the training.mp4 46.42Мб
012 Analyzing the results after the training of Mask RCNN model is finished.en.srt 9.80Кб
012 Analyzing the results after the training of Mask RCNN model is finished.mp4 87.39Мб
013 Analyzing the results of the second training.en.srt 10.01Кб
013 Analyzing the results of the second training.mp4 83.88Мб
014 Further explanation of when to run your evaluation jobs.en.srt 2.58Кб
014 Further explanation of when to run your evaluation jobs.mp4 14.80Мб
015 Downloading the trained model and exporting the SavedModel from checkpoints.en.srt 9.55Кб
015 Downloading the trained model and exporting the SavedModel from checkpoints.mp4 73.87Мб
016 Running the exported model on new examples locally.en.srt 25.97Кб
016 Running the exported model on new examples locally.mp4 227.34Мб
019 damaged_cars_dataset.zip 14.42Мб
030 mask_rcnn_inception_resnet_v2_1024x1024_coco17_gpu-8.config 3.91Кб
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external-assets-links.txt 94б
external-assets-links.txt 217б
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external-assets-links.txt 192б
TutsNode.com.txt 63б
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