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Object Detection with Tensorflow, OpenCV, ImageAI and YOLO
Requirements:
Be sure to have the requirements installed.
Project Start - Importing Libraries and Testing
Initialize the libraries
import cv2 as cv #Loads ComputerVision / OpenCV from imageai.Detection import ObjectDetection as od # Loads ImageAI import numpy as np # Imports NumPY import requests as req # Imports Requests import os as os # Imports OS Module
Testing if OpenCV is working:
url = 'https://p7.hiclipart.com/preview/124/937/193/architectural-engineering-engineer.jpg' # Image to be Downloaded r = req.get(url) # Pass the URL as a Request.Get with open('testimage.jpg', 'wb') as outfile: # Writes the Image to the system outfile.write(r.content) img = cv.imread('testimage.jpg') # Reads an image with OpenCV window_name = 'image' # Defines a Window Name cv.imshow(window_name, img) # Show the Image on a Window cv.waitKey(0) # Wait for any Key to be pressed cv.destroyAllWindows() # Destroy (all) previous created Windows
Preparing for the upcoming project:
Now that we tested that OpenCV is working let's edit that last piece of code, change it to a function, so we can reutilize it often. The complete code until now should look like this:
import cv2 as cv from imageai.Detection import ObjectDetection as od import numpy as np import requests as req import os as os def showImage(img): window_name = 'image' cv.imshow(window_name, img) cv.waitKey(0) cv.destroyAllWindows()