In this case we will increase our confidence in model prediction as we will use a voting technique (model will be applied on number of frames instead of one frame then it will return the most predicted class)

In this case we will use 2 models (one for predicting the slot marker,and another one for predicting the cylinder type if existed) so, it will duplicate the inference time on each frame which is a constrain for us

we will face another problems in data collection for the model that is responsible for detecting the markers in slots

As the marker is fexed on slots , the existing of a cylinder may cause the disappearance of a marker (have to be checked on CAD)

In this case we will apply the model on frame which will cause decreasing in inference time

As we will apply a model on one frame , we cannot validate how the model works well

easy in implementation

QR code should be perpendicular on the camera position to be detected

Data collection

Data cleaning

Data annotating

Yolov5 model for object detection problem

INCEPTIONV3 model for classification problem

Data collection

Data cleaning

Data annotating

Yolov5 model for object detection problem

RESNET106 model for classification problem