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Object Detection using PyTorch for images using Faster RCNN | PyTorch object detection in colab

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In this video, we are going to implement Object Detection in PyTorch for images. For PyTorch Object Detection, we will be using the Faster RCNN algorithm and the code will be available on Github.
PyTorch framework has excelled in tasks like object detection in Computer Vision and carrying on its legacy, we have one of the most famous Object Detection algorithms Faster RCNN. The video basically focuses on detecting objects in an image and this can easily be scaled to multiple images and even videos. We use the pretrained version of Faster RCNN meaning that there is no fine tuning involved. We also use OpenCV for making bounding boxes for the detections. The whole project is implemented in Google Colab without any GPU.
Image:
coco_names = ["person" , "bicycle" , "car" , "motorcycle" , "airplane" , "bus" , "train" , "truck" , "boat" , "traffic light" , "fire hydrant" , "street sign" , "stop sign" , "parking meter" , "bench" , "bird" , "cat" , "dog" , "horse" , "sheep" , "cow" , "elephant" , "bear" , "zebra" , "giraffe" , "hat" , "backpack" , "umbrella" , "shoe" , "eye glasses" , "handbag" , "tie" , "suitcase" ,
"frisbee" , "skis" , "snowboard" , "sports ball" , "kite" , "baseball bat" ,
"baseball glove" , "skateboard" , "surfboard" , "tennis racket" , "bottle" ,
"plate" , "wine glass" , "cup" , "fork" , "knife" , "spoon" , "bowl" ,
"banana" , "apple" , "sandwich" , "orange" , "broccoli" , "carrot" , "hot dog" ,
"pizza" , "donut" , "cake" , "chair" , "couch" , "potted plant" , "bed" ,
"mirror" , "dining table" , "window" , "desk" , "toilet" , "door" , "tv" ,
"laptop" , "mouse" , "remote" , "keyboard" , "cell phone" , "microwave" ,
"oven" , "toaster" , "sink" , "refrigerator" , "blender" , "book" ,
"clock" , "vase" , "scissors" , "teddy bear" , "hair drier" , "toothbrush" , "hair brush"]
PyTorch framework has excelled in tasks like object detection in Computer Vision and carrying on its legacy, we have one of the most famous Object Detection algorithms Faster RCNN. The video basically focuses on detecting objects in an image and this can easily be scaled to multiple images and even videos. We use the pretrained version of Faster RCNN meaning that there is no fine tuning involved. We also use OpenCV for making bounding boxes for the detections. The whole project is implemented in Google Colab without any GPU.
Image:
coco_names = ["person" , "bicycle" , "car" , "motorcycle" , "airplane" , "bus" , "train" , "truck" , "boat" , "traffic light" , "fire hydrant" , "street sign" , "stop sign" , "parking meter" , "bench" , "bird" , "cat" , "dog" , "horse" , "sheep" , "cow" , "elephant" , "bear" , "zebra" , "giraffe" , "hat" , "backpack" , "umbrella" , "shoe" , "eye glasses" , "handbag" , "tie" , "suitcase" ,
"frisbee" , "skis" , "snowboard" , "sports ball" , "kite" , "baseball bat" ,
"baseball glove" , "skateboard" , "surfboard" , "tennis racket" , "bottle" ,
"plate" , "wine glass" , "cup" , "fork" , "knife" , "spoon" , "bowl" ,
"banana" , "apple" , "sandwich" , "orange" , "broccoli" , "carrot" , "hot dog" ,
"pizza" , "donut" , "cake" , "chair" , "couch" , "potted plant" , "bed" ,
"mirror" , "dining table" , "window" , "desk" , "toilet" , "door" , "tv" ,
"laptop" , "mouse" , "remote" , "keyboard" , "cell phone" , "microwave" ,
"oven" , "toaster" , "sink" , "refrigerator" , "blender" , "book" ,
"clock" , "vase" , "scissors" , "teddy bear" , "hair drier" , "toothbrush" , "hair brush"]
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