added feature enum | fixed image_processing crop

src/feature.py

@@ -0,0 +1,7 @@
+from enum import Enum, auto
+
+class Feature(Enum):
+	OVERALL_COLOR_PERCENTAGE = auto()
+	RASTER_COLOR_PERCENTAGE = auto()
+	CORNERS = auto()
+	EDGES = auto()

src/feature_vector.py

@@ -1,9 +1,9 @@
-from typing import Any
+from typing import Any, Self
 import os
 import pickle
 
-from feature_vector import FeatureVector
 from concept import Concept
+from feature import Feature
 
 
 class FeatureVector:
@@ -13,7 +13,7 @@ class FeatureVector:
 		self.concept: Concept = concept
 
 
-	def add_feature(self, key, value) -> None:
+	def add_feature(self, key: Feature, value: Any) -> None:
 		self.features.update({key: value})
 
 
@@ -25,20 +25,22 @@ class FeatureVector:
 		return len(self.features)
 
 
-	def get_feature_value(self, key) -> Any:
+	def get_feature_value(self, key: str) -> Any:
 		return self.features[key]
 	
 
+	def get_features(self) -> Any:
+		return self.features
+	
+
 	def save(self, path: os.path) -> None:
 		with open(path, "wb") as write:
 			pickle.dump(self, write, pickle.HIGHEST_PROTOCOL)
 
 
-	def load(self, path: os.path) -> FeatureVector:
+	def load(path: os.path) -> Self:
 		with open(path, "rb") as read:
-			feature_vector: FeatureVector = pickle.load(read)
-		self.features = feature_vector.features
-		self.concept = feature_vector.concept
-		return feature_vector
+			self: FeatureVector = pickle.load(read)
+		return self
 
 

src/image_processing.py

@@ -8,9 +8,9 @@ def crop(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarray) -> cv.Mat:
 	for x in range(width):
 		for y in range(height):
 			b, g, r = image[x][y]
-			if(r <= lower_rgb[0] and r >= upper_rgb[0] and
-	  		   g <= lower_rgb[1] and g >= upper_rgb[1] and
-			   b <= lower_rgb[2] and b >= upper_rgb[2]
+			if(not (r >= lower_rgb[0] and r <= upper_rgb[0] and
+	  		   g >= lower_rgb[1] and g <= upper_rgb[1] and
+			   b >= lower_rgb[2] and b <= upper_rgb[2])
 			):
 				x1 = x
 				break
@@ -21,9 +21,9 @@ def crop(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarray) -> cv.Mat:
 	for y in range(height):
 		for x in range(width):
 			b, g, r = image[x][y]
-			if(r <= lower_rgb[0] and r >= upper_rgb[0] and
-	  		   g <= lower_rgb[1] and g >= upper_rgb[1] and
-			   b <= lower_rgb[2] and b >= upper_rgb[2]
+			if(not (r >= lower_rgb[0] and r <= upper_rgb[0] and
+	  		   g >= lower_rgb[1] and g <= upper_rgb[1] and
+			   b >= lower_rgb[2] and b <= upper_rgb[2])
 			):
 				y1 = y
 				break
@@ -34,9 +34,9 @@ def crop(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarray) -> cv.Mat:
 	for x in range(width-1, 0, -1):
 		for y in range(height):
 			b, g, r = image[x][y]
-			if(r <= lower_rgb[0] and r >= upper_rgb[0] and
-	  		   g <= lower_rgb[1] and g >= upper_rgb[1] and
-			   b <= lower_rgb[2] and b >= upper_rgb[2]
+			if(not (r >= lower_rgb[0] and r <= upper_rgb[0] and
+	  		   g >= lower_rgb[1] and g <= upper_rgb[1] and
+			   b >= lower_rgb[2] and b <= upper_rgb[2])
 			):
 				x2 = x
 				break
@@ -47,9 +47,9 @@ def crop(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarray) -> cv.Mat:
 	for y in range(height-1, 0, -1):
 		for x in range(width):
 			b, g, r = image[x][y]
-			if(r <= lower_rgb[0] and r >= upper_rgb[0] and
-	  		   g <= lower_rgb[1] and g >= upper_rgb[1] and
-			   b <= lower_rgb[2] and b >= upper_rgb[2]
+			if(not (r >= lower_rgb[0] and r >= upper_rgb[0] and
+	  		   g >= lower_rgb[1] and g >= upper_rgb[1] and
+			   b >= lower_rgb[2] and b >= upper_rgb[2])
 			):
 				y2 = y
 				break
@@ -59,7 +59,7 @@ def crop(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarray) -> cv.Mat:
 	return image[x1-2:x2+2, y1-2:y2+2]
 
 
-def remove_background(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarray) -> cv.Mat:
+def remove_background(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarray, new_background: np.ndarray) -> cv.Mat:
 	width, height = image.shape[:2]
 
 	# left to right
@@ -70,7 +70,7 @@ def remove_background(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarra
 	  		   g >= lower_rgb[1] and g <= upper_rgb[1] and
 			   b >= lower_rgb[2] and b <= upper_rgb[2]
 			):
-				image[x][y] = [0, 0, 0]
+				image[x][y] = new_background
 			else:
 				break
 	
@@ -78,8 +78,11 @@ def remove_background(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarra
 	# for y in range(height):
 	# 	for x in range(width):
 	# 		b, g, r = image[x][y]
-	# 		if(r >= lower_rgb[0] and g >= lower_rgb[1] and b >= lower_rgb[2]):
-	# 			image[x][y] = [0, 0, 0]
+	# 		if(r >= lower_rgb[0] and r <= upper_rgb[0] and
+	#  		   g >= lower_rgb[1] and g <= upper_rgb[1] and
+	#		   b >= lower_rgb[2] and b <= upper_rgb[2]
+	#		):
+	# 			image[x][y] = new_background
 	# 		else:
 	# 			break
 
@@ -87,8 +90,11 @@ def remove_background(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarra
 	for x in range(width):
 		for y in range(height-1, 0, -1):
 			b, g, r = image[x][y]
-			if(r >= lower_rgb[0] and g >= lower_rgb[1] and b >= lower_rgb[2]):
-				image[x][y] = [0, 0, 0]
+			if(r >= lower_rgb[0] and r <= upper_rgb[0] and
+	  		   g >= lower_rgb[1] and g <= upper_rgb[1] and
+			   b >= lower_rgb[2] and b <= upper_rgb[2]
+			):
+				image[x][y] = new_background
 			else:
 				break
 	
@@ -96,8 +102,11 @@ def remove_background(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarra
 	# for y in range(height):
 	# 	for x in range(width-1, 0, -1):
 	# 		b, g, r = image[x][y]
-	# 		if(r >= lower_rgb[0] and g >= lower_rgb[1] and b >= lower_rgb[2]):
-	# 			image[x][y] = [0, 0, 0]
+	# 		if(r >= lower_rgb[0] and r <= upper_rgb[0] and
+	#  		   g >= lower_rgb[1] and g <= upper_rgb[1] and
+	#		   b >= lower_rgb[2] and b <= upper_rgb[2]
+	#		):
+	# 			image[x][y] = new_background
 	# 		else:
 	# 			break