GMU:Procedural Cut/Assignment Object Recognition: Difference between revisions

Latest revision as of 22:59, 1 December 2019

This Assignment is a bit different. There is no precise instruction. Goal is to edit video according to image analysis, or more specifically: Object recognition. For this assignment everyone needs to communicate to coordinate the effort and share ideas how to reach that goal. Edit this page here.

Example

Object detection using OpenCV and YOLO.

Input

Output

File:Log dog.txt

Here is the good olde color tracking in the new fancy clothes of "heuristics" https://towardsdatascience.com/real-time-object-detection-without-machine-learning-5139b399ee7d

cloud annotations
Tracking Motion Detection this page is very much outdated since machine learning has become a thing

@@ Line 3: / Line 3: @@
 == Example ==
+Object detection using [https://github.com/opencv/open_model_zoo/tree/master/demos/object_detection_demo_yolov3_async OpenCV and YOLO].
-Object detection using [https://github.com/opencv/open_model_zoo/tree/master/demos/object_detection_demo_yolov3_async OpenCV and Yolo].
 === Input ===
-[[File:input_dog.mp4]]
+[[File:input dog.mp4]]
 === Output ===
-[[File:log_dog.txt]]
+[[File:output dog.mp4]]
+[[File:log dog.txt]]
+Here is the good olde color tracking in the new fancy clothes of "heuristics" https://towardsdatascience.com/real-time-object-detection-without-machine-learning-5139b399ee7d
+* [https://github.com/cloud-annotations/training cloud annotations]
+* [[Tracking Motion Detection]] this page is very much outdated since machine learning has become a thing