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Commit070ab98

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added contour detection tutorial
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‎README.md

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@@ -29,6 +29,7 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
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-[How to Use Transfer Learning for Image Classification using Keras in Python](https://www.thepythoncode.com/article/use-transfer-learning-for-image-flower-classification-keras-python). ([code](machine-learning/image-classifier-using-transfer-learning))
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-[How to Perform Edge Detection in Python using OpenCV](https://www.thepythoncode.com/article/canny-edge-detection-opencv-python). ([code](machine-learning/edge-detection))
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-[How to Detect Shapes in Images in Python](https://www.thepythoncode.com/article/detect-shapes-hough-transform-opencv-python). ([code](machine-learning/shape-detection))
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-[How to Detect Contours in Images using OpenCV in Python](https://www.thepythoncode.com/article/contour-detection-opencv-python). ([code](machine-learning/contour-detection))
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-[How to Recognize Optical Characters in Images in Python](https://www.thepythoncode.com/article/optical-character-recognition-pytesseract-python). ([code](machine-learning/optical-character-recognition))
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-[Building a Speech Emotion Recognizer using Scikit-learn](https://www.thepythoncode.com/article/building-a-speech-emotion-recognizer-using-sklearn). ([code](machine-learning/speech-emotion-recognition))
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-[How to Convert Speech to Text in Python](https://www.thepythoncode.com/article/using-speech-recognition-to-convert-speech-to-text-python). ([code](machine-learning/speech-recognition))
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#[How to Detect Contours in Images using OpenCV in Python](https://www.thepythoncode.com/article/contour-detection-opencv-python)
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To run this:
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-`pip3 install -r requirements.txt`
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- To detect contour of the the image`thumbs_up_down.jpg` using 225 value of binary threshold conversion:
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```
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python contour-detector.py thumbs_up_down.jpg 225
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```
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- For live detection, consider using `live-contour-detector.py` script.
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importcv2
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importmatplotlib.pyplotasplt
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importsys
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# read the image
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image=cv2.imread(sys.argv[1])
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# convert to RGB
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image=cv2.cvtColor(image,cv2.COLOR_BGR2RGB)
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# convert to grayscale
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gray=cv2.cvtColor(image,cv2.COLOR_RGB2GRAY)
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# create a binary thresholded image
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_,binary=cv2.threshold(gray,sys.argv[2],255,cv2.THRESH_BINARY_INV)
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# show it
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plt.imshow(binary,cmap="gray")
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plt.show()
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# find the contours from the thresholded image
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contours,hierarchy=cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
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# draw all contours
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image=cv2.drawContours(image,contours,-1, (0,255,0),2)
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# show the image with the drawn contours
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plt.imshow(image)
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plt.show()
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importcv2
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cap=cv2.VideoCapture(0)
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whileTrue:
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_,frame=cap.read()
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# convert to grayscale
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gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
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# create a binary thresholded image
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_,binary=cv2.threshold(gray,255//2,255,cv2.THRESH_BINARY_INV)
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# find the contours from the thresholded image
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contours,hierarchy=cv2.findContours(binary,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
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# draw all contours
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image=cv2.drawContours(frame,contours,-1, (0,255,0),2)
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# show the images
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cv2.imshow("gray",gray)
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cv2.imshow("image",image)
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cv2.imshow("binary",binary)
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ifcv2.waitKey(1)==ord("q"):
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break
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cap.release()
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cv2.destroyAllWindows()
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opencv-python
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matplotlib
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