Perform the following steps to implement object detection with a Yolo v3 pretrained model, using the opencv-python library functions:
- First, initialize all of the parameters (for example, thresholds for non-maximum suppression and confidence for classification) with appropriate values:
conf_threshold = 0.5 # Confidence thresholdnms_threshold = 0.4 # Non-maximum suppression thresholdwidth = 416 # Width of network's input imageheight = 416 # Height of network's input image
- Load the names of the object classes (there are 80 classes corresponding to the MS-COCO dataset, including a person, bicycle, car, motorbike, and airplane) from the text file provided. Create unique colors corresponding to each object class (to distinguish ...
