| 1. Course content.mp4 | 20.9 MB | ||
| 1. Course content.srt | 5 KB | ||
| 1. Final remarks.mp4 | 2.2 MB | ||
| 1. Final remarks.srt | 1.3 KB | ||
| 1. Object tracking vs Object detection.mp4 | 34.9 MB | ||
| 1. Object tracking vs Object detection.srt | 6.9 KB | ||
| 10. Tracking a single object 3.mp4 | 102.7 MB | ||
| 10. Tracking a single object 3.srt | 13.9 KB | ||
| 11. Tracking a single object 4.mp4 | 96.8 MB | ||
| 11. Tracking a single object 4.srt | 6.7 KB | ||
| 12. Tracking multiple objects 1.mp4 | 32.4 MB | ||
| 12. Tracking multiple objects 1.srt | 4.4 KB | ||
| 13. Tracking multiple objects 2.mp4 | 52 MB | ||
| 13. Tracking multiple objects 2.srt | 6.7 KB | ||
| 14. Tracking multiple objects 3.mp4 | 66.3 MB | ||
| 14. Tracking multiple objects 3.srt | 8 KB | ||
| 15. Tracking objects with Goturn.mp4 | 38.2 MB | ||
| 15. Tracking objects with Goturn.srt | 6.6 KB | ||
| 16. Object detection.mp4 | 68.3 MB | ||
| 16. Object detection.srt | 10.3 KB | ||
| 17. Object detection + object tracking 1.mp4 | 75.2 MB | ||
| 17. Object detection + object tracking 1.srt | 9.8 KB | ||
| 18. Object detection + object tracking 2.mp4 | 146.5 MB | ||
| 18. Object detection + object tracking 2.srt | 14.7 KB | ||
| 19. Meanshift algorithm - intuition.mp4 | 25 MB | ||
| 19. Meanshift algorithm - intuition.srt | 4.9 KB | ||
| 2. Course materials.html | 102.4 B | ||
| 2. Object tracking algorithms - intuition.mp4 | 32.7 MB | ||
| 2. Object tracking algorithms - intuition.srt | 6.3 KB | ||
| 2.1 Object tracking.pdf | 3.7 MB | ||
| 20. Meanshift algorithm - implementation 1.mp4 | 44.1 MB | ||
| 20. Meanshift algorithm - implementation 1.srt | 8.7 KB | ||
| 21. Meanshift algorithm - implementation 2.mp4 | 114.5 MB | ||
| 21. Meanshift algorithm - implementation 2.srt | 13.9 KB | ||
| 22. Meanshift algorithm - implementation 3.mp4 | 116.2 MB | ||
| 22. Meanshift algorithm - implementation 3.srt | 12.2 KB | ||
| 23. CAMShift algorithm - intuition.mp4 | 4.6 MB | ||
| 23. CAMShift algorithm - intuition.srt | 2.8 KB | ||
| 24. CAMShift algorithm - implementation.mp4 | 42.6 MB | ||
| 24. CAMShift algorithm - implementation.srt | 4.4 KB | ||
| 25. Optical flow algorithm (sparse) – intuition.mp4 | 78.5 MB | ||
| 25. Optical flow algorithm (sparse) – intuition.srt | 10.8 KB | ||
| 26. Optical flow algorithm (sparse) – implementation 1.mp4 | 101.9 MB | ||
| 26. Optical flow algorithm (sparse) – implementation 1.srt | 16.9 KB | ||
| 27. Optical flow algorithm (sparse) – implementation 2.mp4 | 127.7 MB | ||
| 27. Optical flow algorithm (sparse) – implementation 2.srt | 16.6 KB | ||
| 28. Optical flow algorithm (sparse) – implementation 3.mp4 | 73.3 MB | ||
| 28. Optical flow algorithm (sparse) – implementation 3.srt | 9 KB | ||
| 29. Optical flow dense algorithm – intuition.mp4 | 20.2 MB | ||
| 29. Optical flow dense algorithm – intuition.srt | 3.5 KB | ||
| 3. Object tracking algorithms - additional materials.html | 14.5 KB | ||
| 30. Optical flow dense algorithm – implementation.mp4 | 106.4 MB | ||
| 30. Optical flow dense algorithm – implementation.srt | 14 KB | ||
| 4. Boosting and MIL algorithms.mp4 | 9.5 MB | ||
| 4. Boosting and MIL algorithms.srt | 5.8 KB | ||
| 5. KCF and CSRT algorithms.mp4 | 44.3 MB | ||
| 5. KCF and CSRT algorithms.srt | 6.4 KB | ||
| 6. MedianFlow, TLD, MOSSE and Goturn algorithms.mp4 | 45.1 MB | ||
| 6. MedianFlow, TLD, MOSSE and Goturn algorithms.srt | 9.7 KB | ||
| 7. Installing Anaconda and PyCharm.mp4 | 20.1 MB | ||
| 7. Installing Anaconda and PyCharm.srt | 5.1 KB | ||
| 8. Tracking a single object 1.mp4 | 43.2 MB | ||
| 8. Tracking a single object 1.srt | 7.3 KB | ||
| 9. Tracking a single object 2.mp4 | 91.8 MB | ||
| 9. Tracking a single object 2.srt | 12.4 KB | ||
| Bonus Resources.txt | 307.2 B | ||
| DS_Store | 6 KB | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| Tracking.iml | 307.2 B | ||
| _.DS_Store | 102.4 B | ||
| _.idea | 204.8 B | ||
| _Images | 204.8 B | ||
| _Tracking | 204.8 B | ||
| _Videos | 204.8 B | ||
| _cascade | 204.8 B | ||
| _inspectionProfiles | 204.8 B | ||
| _race.mp4 | 409.6 B | ||
| _walking.avi | 204.8 B | ||
| camshift.py | 1.2 KB | ||
| detection_tracking.py | 1.6 KB | ||
| fullbody.xml | 465.6 KB | ||
| gitignore | 0 B | ||
| goturn.caffemodel | 369.9 MB | ||
| goturn.prototxt | 7.8 KB | ||
| goturn.py | 1.1 KB | ||
| haarcascade_eye.xml | 333.4 KB | ||
| haarcascade_frontalface_default.xml | 908.3 KB | ||
| haarcascade_lowerbody.xml | 386.1 KB | ||
| haarcascade_upperbody.xml | 767.4 KB | ||
| meanshift.py | 1.6 KB | ||
| misc.xml | 204.8 B | ||
| modules.xml | 307.2 B | ||
| multiple_tracking.py | 2.1 KB | ||
| optical_flow_dense.py | 1.1 KB | ||
| optical_flow_sparse1.py | 1.5 KB | ||
| optical_flow_sparse2.py | 1.7 KB | ||
| people.jpg?042148 | 39 KB | ||
| profiles_settings.xml | 204.8 B | ||
| race.mp4 | 10.4 MB | ||
| single_tracking.py | 1.7 KB | ||
| test_detection.py | 512 B | ||
| test_opencv.py | 0 B | ||
| walking.avi | 7.8 MB | ||
| workspace.xml | 7.4 KB | ||
| ▲ 104 total files | |||
Object Tracking using Python and OpenCV
https://TutGator.com
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 33 lectures (4h 44m) | Size: 2 GB
Implement 12 different algorithms for tracking objects in videos and webcam!
What you'll learn:
Track objects from videos and from the webcam using Python and OpenCV
Understand the basic intuition about tracking algorithms
Implement 12 tracking algorithms
Understand the differences between object detection and object tracking
Requirements
Programming logic
Basic Python programming
Description
Object tracking is a subarea of Computer Vision which aims to locate an object in successive frames of a video. An example of application is a video surveillance and security system, in which suspicious actions can be detected. Other examples are the monitoring of traffic on highways and also the analysis of the movement of players in a soccer match! In this last example, it is possible to trace the complete route that the player followed during the match.
To take you to this area, in this course you will learn the main object tracking algorithms using the Python language and the OpenCV library! You will learn the basic intuition about 12 (twelve) algorithms and implement them step by step! At the end of the course you will know how to apply tracking algorithms applied to videos, so you will able to develop your own projects. The following algorithms will be covered: Boosting, MIL (Multiple Instance Learning), KCF (Kernel Correlation Filters), CSRT (Discriminative Correlation Filter with Channel and Spatial Reliability), MedianFlow, TLD (Tracking Learning Detection), MOSSE (Minimum Output Sum of Squared) Error), Goturn (Generic Object Tracking Using Regression Networks), Meanshift, CAMShift (Continuously Adaptive Meanshift), Optical Flow Sparse, and Optical Flow Dense.
| torrent name | size | uploader | age | seed | leech |
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| 1.6 GB | freecoursewb | 1 month | 13 | 0 | |
| 613.3 MB | freecoursewb | 3 months | 11 | 6 | |
| 2 GB | freecoursewb | 5 months | 6 | 0 | |
| 1.1 GB | freecoursewb | 8 months | 2 | 2 | |
| 253.8 MB | freecoursewb | 9 months | 15 | 2 |
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