scan orientation fix

check.py

@@ -23,20 +23,27 @@
 		images = glob.glob("*.jpg") + glob.glob("*.JPG") + glob.glob("*.png") + glob.glob("*.PNG")
 		# if image then process
 		if len(images) > 0:
-			cmd = "python scan.py --image " + images[0]
-			os.system(cmd)
-			# send back
-			cmd = "mutt -s 'Your scanned image' -i message_ok.txt " + sender +  " -a *.pdf < /dev/null"
-			os.system(cmd)
+			returncode = call(["python", "scan.py", "--image", image[0]])
+			if returncode == 0:
+				# send back the ok message with the file attached
+				cmd = "mutt -s 'Voilà ton scan !' -i ok_msg.txt " + sender +  " -a *.pdf < /dev/null"
+				os.system(cmd)
+			else:
+				# the image was not correctly processed
+				# send back the "file not processed" error message
+				cmd = "mutt -s 'Elle est moche ta photo' -i error_process_msg.txt " + sender +  " < /dev/null"
+				os.system(cmd)			
 		else:
-			# send back an error mail
-			cmd = "mutt -s 'No image to scan' -i message_error.txt " + sender +  " < /dev/null"
+			# there is no image to process
+			# send back the "no image attached" error message
+			cmd = "mutt -s 'Euh, elle est où ton image ?' -i error_empty_msg.txt " + sender +  " < /dev/null"
 			os.system(cmd)
 
 
 		# clean
 		os.remove(mail)
 		os.system("rm -f *.JPG *.jpg *.PNG *.png *.desc")
+		os.system("rm -f ~/scanMail/sent/cur/*")
 		#call(["rm part*"])
 		#call(["rm "+mail,])
 

pyimagesearch/transform.py

@@ -51,10 +51,10 @@ def four_point_transform(image, pts):
 	# in the top-left, top-right, bottom-right, and bottom-left
 	# order
 	dst = np.array([
-		[0, 0],
 		[maxWidth - 1, 0],
 		[maxWidth - 1, maxHeight - 1],
-		[0, maxHeight - 1]], dtype = "float32")
+		[0, maxHeight - 1],
+		[0, 0]], dtype = "float32")
 
 	# compute the perspective transform matrix and then apply it
 	M = cv2.getPerspectiveTransform(rect, dst)

scan.py

@@ -49,15 +49,19 @@
 		screenCnt = approx
 		break
 
+		file =open
+		file.write
+		file.close
+
 # apply the four point transform to obtain a top-down
 # view of the original image
 warped = four_point_transform(orig, screenCnt.reshape(4, 2) * ratio)
 
 # convert the warped image to grayscale, then threshold it
 # to give it that 'black and white' paper effect
-warped = cv2.cvtColor(warped, cv2.COLOR_BGR2GRAY)
-warped = threshold_adaptive(warped, 250, offset = 10)
-warped = warped.astype("uint8") * 255
+# warped = cv2.cvtColor(warped, cv2.COLOR_BGR2GRAY)
+# warped = threshold_adaptive(warped, 250, offset = 10)
+# warped = warped.astype("uint8") * 255
 
 final = imutils.resize(warped, height = 650)