Normalize everything to RGB over BGR, v1.0.7

Author: janjongboom

edge_impulse_linux/image.py

@@ -122,9 +122,9 @@ def get_features_from_image(self, img, crop_direction_x='center', crop_direction
             pixels = np.array(cropped).flatten().tolist()
 
             for ix in range(0, len(pixels), 3):
-                b = pixels[ix + 0]
+                r = pixels[ix + 0]
                 g = pixels[ix + 1]
-                r = pixels[ix + 2]
+                b = pixels[ix + 2]
                 features.append((r << 16) + (g << 8) + b)
 
         return features, cropped

examples/image/classify-image.py

@@ -47,6 +47,9 @@ def main(argv):
                 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)
 

examples/image/classify-video.py

@@ -66,6 +66,9 @@ def getFrame(sec):
 
             while img.size != 0:
 
+                # 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)
 

setup.cfg

@@ -1,6 +1,6 @@
 [metadata]
 name = edge_impulse_linux
-version = 1.0.6
+version = 1.0.7
 author = EdgeImpulse Inc.
 author_email = hello@edgeimpulse.com
 description = Python runner for real-time ML classification