In this video, we are going to do python opencv object detection using the Single Shot Detection(SSD) Algorithm. In this tutorial, we will only be using OpenCV for carrying out the deep learning object detection task using Google Colab.

The task will focus on running an inference on images and there will be no scope of fine tuning on a custom dataset. Computer vision object detection is one of the most vibrant fields in computer vision and for trying out models quickly, OpenCV provides the dnn module which we will be using in the video. All the code will be available in Github. The video will also explain cv2.blobfromimage function and also use it for the task.

Code: [ Ссылка ]

!git clone [ Ссылка ]

classNames = { 0: 'background',
1: 'aeroplane', 2: 'bicycle', 3: 'bird', 4: 'boat',
5: 'bottle', 6: 'bus', 7: 'car', 8: 'cat', 9: 'chair',
10: 'cow', 11: 'diningtable', 12: 'dog', 13: 'horse',
14: 'motorbike', 15: 'person', 16: 'pottedplant',
17: 'sheep', 18: 'sofa', 19: 'train', 20: 'tvmonitor' }

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