Add target rectangular selection

vision-env/src/vision-test.py

@@ -1,23 +1,80 @@
 import io
 import os
 import sys
+import cv2
 
 # Imports the Google Cloud client library
 from google.cloud import vision
 
+def shape_selection(event, x, y, flags, param):
+    # grab references to the global variables
+    global ref_point, crop
+  
+    # if the left mouse button was clicked, record the starting
+    # (x, y) coordinates and indicate that cropping is being performed
+    if event == cv2.EVENT_LBUTTONDOWN:
+        ref_point = [(x, y)]
+  
+    # check to see if the left mouse button was released
+    elif event == cv2.EVENT_LBUTTONUP:
+        # record the ending (x, y) coordinates and indicate that
+        # the cropping operation is finished
+        ref_point.append((x, y))
+  
+        # draw a rectangle around the region of interest
+        cv2.rectangle(image, ref_point[0], ref_point[1], (0, 255, 0), 2)
+        cv2.imshow("image", image)
+
 # User input from the command line
-image_path = sys.argv[1]
+image_name = sys.argv[1]
 
 # The name of the image file to annotate
-file_name = os.path.abspath(image_path)
+file_name = os.path.abspath(image_name)
+
+# Initialize the list of reference point
+ref_point = []
+crop = False
+  
+image = cv2.imread(file_name)
+clone = image.copy()
+cv2.namedWindow("image")
+cv2.setMouseCallback("image", shape_selection)
+   
+# keep looping until the 'q' key is pressed
+while True:
+    # display the image and wait for a keypress
+    cv2.imshow("image", image)
+    key = cv2.waitKey(1) & 0xFF
+  
+    # press 'r' to reset the window
+    if key == ord("r"):
+        image = clone.copy()
+  
+    # if the 'c' key is pressed, break from the loop
+    elif key == ord("c"):
+        break
+  
+if len(ref_point) == 2:
+    crop_img = clone[ref_point[0][1]:ref_point[1][1], ref_point[0][0]:
+                                                           ref_point[1][0]]
+    #cv2.imshow("crop_img", crop_img)   #uncomment --> show cropped image
+    cv2.waitKey(0)  #maybe useless
+    cv2.imwrite('copy1.jpg', crop_img)
+  
+# close all open windows
+cv2.destroyAllWindows() 
+
+# File used for label detection
+target_file = os.path.abspath('copy1.jpg')
 
 # Loads the image into memory
-with io.open(file_name, 'rb') as image_file:
+with io.open(target_file, 'rb') as image_file:
     content = image_file.read()
 
 # Instantiates a client
 client = vision.ImageAnnotatorClient()
 
+#image = vision.Image(content=content)
 image = vision.Image(content=content)
 
 # Performs label detection on the image file