Curriculum
Unit 01: Set up Necesssary Environments | |||
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Module 01: Driver installation 00:06:00 | ||
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Module 02: Cuda toolkit installation 00:01:00 | ||
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Module 03: Compile OpenCV from source with CUDA support part-1 00:06:00 | ||
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Module 04: Compile OpenCV from source with CUDA support part-2 00:05:00 | ||
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Module 05: Python environment for flownet2-pytorch 00:09:00 | ||
Unit 02: Introduction with a few basic examples! | |||
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Module 01: Read camera & files in a folder (C++) 00:11:00 | ||
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Module 02: Edge detection (C++) 00:08:00 | ||
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Module 03: Color transformations (C++) 00:07:00 | ||
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Module 04: Using a trackbar (C++) 00:06:00 | ||
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Module 05: Image filtering with CUDA (Introduction to using OpenCV GPU methods on C++) 00:13:00 | ||
Unit 03: Background segmentation | |||
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Module 01: Background segmentation with MOG (C++) 00:04:00 | ||
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Module 02: MOG and MOG2 cuda implementation (C++ – CUDA) 00:03:00 | ||
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Module 03: Special app: Track class 00:06:00 | ||
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Module 04: Special app: Track bgseg Foreground objects 00:08:00 | ||
Unit 04: Object detection with openCV ML module (C++ CUDA) | |||
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Module 01: A simple application to prepare dataset for object detection (C++) 00:08:00 | ||
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Module 02: Train model with openCV ML module (C++ and CUDA) 00:13:00 | ||
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Module 03: Object detection with openCV ML module (C++ CUDA) 00:06:00 | ||
Unit 05: Optical Flow | |||
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Module 01: Optical flow with Farneback (C++) 00:08:00 | ||
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Module 02: Optical flow with Farneback (C++ CUDA) 00:06:00 | ||
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Module 03: Optical flow with Nvidia optical flow SDK (C++ CUDA)7 00:05:00 | ||
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Module 04: Optical flow with Nvidia Flownet2 (Python) 00:05:00 | ||
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Module 05: Performance Comparison 00:07:00 |
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