New changes

Cards.py

@@ -132,7 +132,12 @@ def find_cards(thresh_image):
     from largest to smallest."""
 
     # Find contours and sort their indices by contour size
-    dummy,cnts,hier = cv2.findContours(thresh_image,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+    contours = cv2.findContours(thresh_image,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+    if len(contours) == 3:
+        dummy,cnts,hier = contours
+    else:  # OpenCV 4 compatibility
+        cnts,hier = contours
+        dummy = None
     index_sort = sorted(range(len(cnts)), key=lambda i : cv2.contourArea(cnts[i]),reverse=True)
 
     # If there are no contours, do nothing
@@ -212,7 +217,12 @@ def preprocess_card(contour, image):
     Qsuit = query_thresh[186:336, 0:128]
 
     # Find rank contour and bounding rectangle, isolate and find largest contour
-    dummy, Qrank_cnts, hier = cv2.findContours(Qrank, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+    contours = cv2.findContours(Qrank, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+    if len(contours) == 3:
+        dummy, Qrank_cnts, hier = contours
+    else:
+        Qrank_cnts, hier = contours
+        dummy = None
     Qrank_cnts = sorted(Qrank_cnts, key=cv2.contourArea,reverse=True)
 
     # Find bounding rectangle for largest contour, use it to resize query rank
@@ -224,7 +234,12 @@ def preprocess_card(contour, image):
         qCard.rank_img = Qrank_sized
 
     # Find suit contour and bounding rectangle, isolate and find largest contour
-    dummy, Qsuit_cnts, hier = cv2.findContours(Qsuit, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+    contours = cv2.findContours(Qsuit, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+    if len(contours) == 3:
+        dummy, Qsuit_cnts, hier = contours
+    else:
+        Qsuit_cnts, hier = contours
+        dummy = None
     Qsuit_cnts = sorted(Qsuit_cnts, key=cv2.contourArea,reverse=True)
 
     # Find bounding rectangle for largest contour, use it to resize query suit

Rank_Suit_Isolator.py

@@ -3,6 +3,7 @@
 ### Runs through A - K ranks and then the 4 suits.
 
 # Import necessary packages
+import argparse
 import cv2
 import numpy as np
 import time
@@ -20,23 +21,39 @@
 SUIT_WIDTH = 70
 SUIT_HEIGHT = 100
 
-# If using a USB Camera instead of a PiCamera, change PiOrUSB to 2
-PiOrUSB = 1
-
-if PiOrUSB == 1:
-    # Import packages from picamera library
-    from picamera.array import PiRGBArray
-    from picamera import PiCamera
-
-    # Initialize PiCamera and grab reference to the raw capture
-    camera = PiCamera()
-    camera.resolution = (IM_WIDTH,IM_HEIGHT)
-    camera.framerate = 10
-    rawCapture = PiRGBArray(camera, size=(IM_WIDTH,IM_HEIGHT))
-
-if PiOrUSB == 2:
-    # Initialize USB camera
-    cap = cv2.VideoCapture(0)
+parser = argparse.ArgumentParser(description="Rank/Suit isolator camera settings")
+parser.add_argument("--camera-type", choices=["auto","pi","usb"], default="auto",
+                    help="Select camera backend: 'pi' for PiCamera, 'usb' for USB/Continuity Camera, 'auto' tries Pi then USB.")
+parser.add_argument("--camera-index", type=int, default=0,
+                    help="USB camera index (ignored for PiCamera). Use when multiple cameras are connected.")
+args = parser.parse_args()
+
+camera = None
+rawCapture = None
+cap = None
+camera_type_used = None
+
+if args.camera_type in ("pi", "auto"):
+    try:
+        from picamera.array import PiRGBArray
+        from picamera import PiCamera
+        camera = PiCamera()
+        camera.resolution = (IM_WIDTH,IM_HEIGHT)
+        camera.framerate = 10
+        rawCapture = PiRGBArray(camera, size=(IM_WIDTH,IM_HEIGHT))
+        camera_type_used = "pi"
+    except ModuleNotFoundError:
+        if args.camera_type == "pi":
+            raise
+        print("picamera module not found; defaulting to USB camera.")
+
+if camera_type_used != "pi":
+    cap = cv2.VideoCapture(args.camera_index)
+    if not cap.isOpened():
+        raise RuntimeError(f"Unable to open USB camera at index {args.camera_index}.")
+    cap.set(cv2.CAP_PROP_FRAME_WIDTH, IM_WIDTH)
+    cap.set(cv2.CAP_PROP_FRAME_HEIGHT, IM_HEIGHT)
+    camera_type_used = "usb"
 
 # Use counter variable to switch from isolating Rank to isolating Suit
 i = 1
@@ -51,7 +68,7 @@
 
 
 
-    if PiOrUSB == 1: # PiCamera
+    if camera_type_used == "pi": # PiCamera
         rawCapture.truncate(0)
         # Press 'p' to take a picture
         for frame in camera.capture_continuous(rawCapture, format="bgr",use_video_port=True):
@@ -64,7 +81,7 @@
 
             rawCapture.truncate(0)
 
-    if PiOrUSB == 2: # USB camera
+    if camera_type_used == "usb": # USB camera
         # Press 'p' to take a picture
         while(True):
 
@@ -81,7 +98,12 @@
     retval, thresh = cv2.threshold(blur,100,255,cv2.THRESH_BINARY)
 
     # Find contours and sort them by size
-    dummy,cnts,hier = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+    contours = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+    if len(contours) == 3:
+        dummy,cnts,hier = contours
+    else:
+        cnts,hier = contours
+        dummy = None
     cnts = sorted(cnts, key=cv2.contourArea,reverse=True)
 
     # Assume largest contour is the card. If there are no contours, print an error
@@ -114,7 +136,12 @@
     # Isolate suit or rank
     if i <= 13: # Isolate rank
         rank = corner_thresh[20:185, 0:128] # Grabs portion of image that shows rank
-        dummy, rank_cnts, hier = cv2.findContours(rank, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+        contours = cv2.findContours(rank, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+        if len(contours) == 3:
+            dummy, rank_cnts, hier = contours
+        else:
+            rank_cnts, hier = contours
+            dummy = None
         rank_cnts = sorted(rank_cnts, key=cv2.contourArea,reverse=True)
         x,y,w,h = cv2.boundingRect(rank_cnts[0])
         rank_roi = rank[y:y+h, x:x+w]
@@ -123,7 +150,12 @@
 
     if i > 13: # Isolate suit
         suit = corner_thresh[186:336, 0:128] # Grabs portion of image that shows suit
-        dummy, suit_cnts, hier = cv2.findContours(suit, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+        contours = cv2.findContours(suit, cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+        if len(contours) == 3:
+            dummy, suit_cnts, hier = contours
+        else:
+            suit_cnts, hier = contours
+            dummy = None
         suit_cnts = sorted(suit_cnts, key=cv2.contourArea,reverse=True)
         x,y,w,h = cv2.boundingRect(suit_cnts[0])
         suit_roi = suit[y:y+h, x:x+w]
@@ -141,4 +173,7 @@
     i = i + 1
 
 cv2.destroyAllWindows()
-camera.close()
+if camera_type_used == "pi":
+    camera.close()
+elif camera_type_used == "usb" and cap is not None:
+    cap.release()