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- Here is an example of YOLO algorithm Python code12. The code uses the OpenCV library and the YOLO algorithm to perform object detection. The code loads the YOLO algorithm and the weights and configuration files1. It then uses the algorithm to detect objects in an image2. The code is written in Python and can be used to detect objects in images or videos.
Learn more:✕This summary was generated using AI based on multiple online sources. To view the original source information, use the "Learn more" links.Here is the complete code for this program import cv2 import numpy as np #Load YOLO Algorithm net=cv2.dnn.readNet("yolov3.weights","yolov3.cfg")www.codespeedy.com/yolo-object-detection-from-i…!./darknet yolo test /content/darknet/cfg/yolov1.cfg /content/yolov1.weights /content/darknet/data/kite.jpgimport cv2 import matplotlib.pyplot as plt import os.pathfig,ax = plt.subplots ()ax.tick_params (labelbottom="off",bottom="off") ax.tick_params (labelleft="off",left="off") ax.set_xticklabels ([]) ax.axis ('off')file = '/content/darknet/predictions.jpg'if os.path.exists (file): img = cv2.imread (file) show_img =...
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YOLO Object Detection with OpenCV and Python
Object detection using OpenCV dnn module with a pre-trained YOLO v3 model with Python. Detect 80 common objects in context including car, bike, dog, cat etc. See more
DNN (Deep Neural Network) module was initially part of opencv_contrib repo. It has been moved to the master branch of opencvrepo last … See more
Read the input image and get its width and height. Read the text file containing class names in human readable form and extract the class names to a list. Generate different colors for … See more
outs = net.forward(get_output_layers(net)) Above line is where the exact feed forward through the network happens. Moment of truth. If we don’t … See more
Generally in a sequential CNN network there will be only one output layer at the end. In the YOLO v3 architecture we are using there are … See more
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