Added conversion from BGR to RGB (#8)

* Added conversion from BGR to RGB

cv2.imread() returns images in BGR format (https://docs.opencv.org/4.5.2/d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56). Added function to convert to RGB.

* BRG to RGB conversion everywhere

Co-authored-by: Jan Jongboom <janjongboom@gmail.com>

Author: ShawnHymel

edge_impulse_linux/image.py

@@ -16,10 +16,6 @@ def __init__(self, model_path: str):
         self.isGrayscale = False
 
     def init(self):
-        if psutil.OSX or psutil.MACOS:
-            print('Make sure that video devices access is granted for your application.')
-            print('If your video device is not responding, try running "tccutil reset Camera" to reset the camera access privileges')
-
         model_info = super(ImageImpulseRunner, self).init()
         width = model_info['model_parameters']['image_input_width'];
         height = model_info['model_parameters']['image_input_height'];
@@ -44,23 +40,36 @@ def __exit__(self, type, value, traceback):
     def classify(self, data):
         return super(ImageImpulseRunner, self).classify(data)
 
+    # This returns images in RGB format (not BGR)
     def get_frames(self, videoDeviceId = 0):
+        if psutil.OSX or psutil.MACOS:
+            print('Make sure to grant the this script access to your webcam.')
+            print('If your webcam is not responding, try running "tccutil reset Camera" to reset the camera access privileges.')
+
         self.videoCapture = cv2.VideoCapture(videoDeviceId)
         while not self.closed:
             success, img = self.videoCapture.read()
+            img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
             if success:
                 yield img
 
+    # This returns images in RGB format (not BGR)
     def classifier(self, videoDeviceId = 0):
+        if psutil.OSX or psutil.MACOS:
+            print('Make sure to grant the this script access to your webcam.')
+            print('If your webcam is not responding, try running "tccutil reset Camera" to reset the camera access privileges.')
+
         self.videoCapture = cv2.VideoCapture(videoDeviceId)
         while not self.closed:
             success, img = self.videoCapture.read()
             if success:
+                img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
                 features, cropped = self.get_features_from_image(img)
 
                 res = self.classify(features)
                 yield res, cropped
 
+    # This expects images in RGB format (not BGR)
     def get_features_from_image(self, img, crop_direction_x='center', crop_direction_y='center'):
         features = []
 

examples/image/classify-full-frame.py

@@ -103,8 +103,8 @@ def main(argv):
                 res_l = runner.classify(features_l)
                 res_r = runner.classify(features_r)
 
-                cv2.imwrite('debug_l.jpg', cropped_l)
-                cv2.imwrite('debug_r.jpg', cropped_r)
+                cv2.imwrite('debug_l.jpg', cv2.cvtColor(cropped_l, cv2.COLOR_RGB2BGR))
+                cv2.imwrite('debug_r.jpg', cv2.cvtColor(cropped_r, cv2.COLOR_RGB2BGR))
 
                 def print_classification(res, tag):
                     if "classification" in res["result"].keys():

examples/image/classify-image.py

@@ -41,13 +41,19 @@ def main(argv):
             labels = model_info['model_parameters']['labels']
 
             img = cv2.imread(args[1])
+            if img is None:
+                print('Failed to load image', args[1])
+                exit(1)
+
+            # imread returns images in BGR format, so we need to convert to RGB
+            img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
 
             # get_features_from_image also takes a crop direction arguments in case you don't have square images
             features, cropped = runner.get_features_from_image(img)
 
             # the image will be resized and cropped, save a copy of the picture here
             # so you can see what's being passed into the classifier
-            cv2.imwrite('debug.jpg', cropped)
+            cv2.imwrite('debug.jpg', cv2.cvtColor(cropped, cv2.COLOR_RGB2BGR))
 
             res = runner.classify(features)
 

examples/image/classify.py

@@ -111,7 +111,7 @@ def main(argv):
                         img = cv2.rectangle(img, (bb['x'], bb['y']), (bb['x'] + bb['width'], bb['y'] + bb['height']), (255, 0, 0), 1)
 
                 if (show_camera):
-                    cv2.imshow('edgeimpulse', img)
+                    cv2.imshow('edgeimpulse', cv2.cvtColor(img, cv2.COLOR_RGB2BGR))
                     if cv2.waitKey(1) == ord('q'):
                         break
 

setup.cfg

@@ -1,6 +1,6 @@
 [metadata]
 name = edge_impulse_linux
-version = 1.0.4
+version = 1.0.5
 author = EdgeImpulse Inc.
 author_email = hello@edgeimpulse.com
 description = Python runner for real-time ML classification