Merge pull request #2 from DavideTonel/main
Add auto key detection and rectangular selection of target image
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@@ -1,19 +1,84 @@
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import io
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import os
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import sys
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import cv2
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# Imports the Google Cloud client library
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from google.cloud import vision
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def shape_selection(event, x, y, flags, param):
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# grab references to the global variables
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global ref_point, crop
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# if the left mouse button was clicked, record the starting
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# (x, y) coordinates and indicate that cropping is being performed
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if event == cv2.EVENT_LBUTTONDOWN:
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ref_point = [(x, y)]
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# check to see if the left mouse button was released
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elif event == cv2.EVENT_LBUTTONUP:
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# record the ending (x, y) coordinates and indicate that
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# the cropping operation is finished
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ref_point.append((x, y))
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# draw a rectangle around the region of interest
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cv2.rectangle(image, ref_point[0], ref_point[1], (0, 255, 0), 2)
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cv2.imshow("image", image)
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key_rel_path= os.path.join('..', 'keys', 'developerKey.json')
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key = os.path.abspath(key_rel_path)
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os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = key
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# User input from the command line
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image_name = sys.argv[1]
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# The name of the image file to annotate
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file_name = os.path.abspath(image_name)
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# Initialize the list of reference point
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ref_point = []
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crop = False
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image = cv2.imread(file_name)
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clone = image.copy()
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cv2.namedWindow("image")
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cv2.setMouseCallback("image", shape_selection)
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# keep looping until the 'q' key is pressed
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while True:
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# display the image and wait for a keypress
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cv2.imshow("image", image)
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key = cv2.waitKey(1) & 0xFF
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# press 'r' to reset the window
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if key == ord("r"):
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image = clone.copy()
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# if the 'c' key is pressed, break from the loop
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elif key == ord("c"):
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break
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if len(ref_point) == 2:
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crop_img = clone[ref_point[0][1]:ref_point[1][1], ref_point[0][0]:
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ref_point[1][0]]
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#cv2.imshow("crop_img", crop_img) #uncomment --> show cropped image
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cv2.waitKey(0) #maybe useless
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cv2.imwrite('copy1.jpg', crop_img)
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# close all open windows
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cv2.destroyAllWindows()
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# File used for label detection
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target_file = os.path.abspath('copy1.jpg')
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# Loads the image into memory
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with io.open(target_file, 'rb') as image_file:
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content = image_file.read()
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# Instantiates a client
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client = vision.ImageAnnotatorClient()
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# The name of the image file to annotate
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file_name = os.path.abspath('images/mmr.jpg')
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# Loads the image into memory
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with io.open(file_name, 'rb') as image_file:
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content = image_file.read()
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#image = vision.Image(content=content)
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image = vision.Image(content=content)
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# Performs label detection on the image file
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