>what is a model? about nfl_kaggle HOT 8 CLOSED

https://everitt257.github.io/post/2018/08/10/object_detection.html

from nfl_kaggle.

@gsvsumanth please add your ideas here.

from nfl_kaggle.

well, you are trying to maintain the higher accuracy and reduce complexity. Faster RCNN is using VGG as a backbone model and is a two-stage object detector i.e. RPN and VGG while YOLO(Darknet backbone) is a single shot detector utilizing anchor boxes. one possible combination is to try using Darknet in faster RCNN replacing VGG and vice versa for YOLO. the other possible option is to remove RPN and utilize anchor boxes similar to YOLO in faster RCNN.
But again, it depends on your problem. what kind of dataset you want to use. like YOLO results are extremely bad on the self-driving cars dataset.

from nfl_kaggle.

fasterrcnn.pdf

from nfl_kaggle.

https://towardsdatascience.com/faster-r-cnn-a-step-towards-real-time-object-detection-98c186732a69

from nfl_kaggle.

well, you are trying to maintain the higher accuracy and reduce complexity. Faster RCNN is using VGG as a backbone model and is a two-stage object detector i.e. RPN and VGG while YOLO(Darknet backbone) is a single shot detector utilizing anchor boxes. one possible combination is to try using Darknet in faster RCNN replacing VGG and vice versa for YOLO. the other possible option is to remove RPN and utilize anchor boxes similar to YOLO in faster RCNN.
But again, it depends on your problem. what kind of dataset you want to use. like YOLO results are extremely bad on the self-driving cars dataset.

This is for real time detection

from nfl_kaggle.

Ideas
In order to avoid the anomalies ( like detecting objects other than helmets in a image and also finding a person who is missing in a frame (x+1) and reappearance of that person in (x+10) ) in object detection in real time using yolo v5

starting with speed and acceleration of each player we will track each player movement
there is a High chance that our player might get colloid in such a case the speed of the player will change this drastic change will help us in finding out whether there is Collision or not.
From end zone or from side zone the player helmets will not be able view as there are situation were they are hidden beside the other player in such a situation we tackle this problem by taking the number of helmets present in that frame (X) compared with the average number of players present in the (X+5) and (X-5) if it is equal to then we can take out
we can take the count of number of helmets from starting of a frame if the count of the number of helmets for a particular frame has increased we can look into frames were these anomalies have occurred

from nfl_kaggle.

@gsvsumanth please close this issue if there's nothing more to add.

from nfl_kaggle.