added method to get vector of FeatureVector | added method to get color percentage per raster

src/concept.py

@@ -7,4 +7,3 @@ class Concept(Enum):
 	STOP = auto()
 	RECHTS_ABBIEGEN = auto()
 	LINKS_ABBIEGEN = auto()
-	# TODO: add remaining signs

src/featue_extraction.py

@@ -1,6 +1,8 @@
 import cv2 as cv
 import numpy as np
 
+from image_processing import raster_image
+
 blue_lower_hsv = np.array([90, 75, 75])
 blue_upper_hsv = np.array([130, 255, 255])
 
@@ -54,3 +56,14 @@ def get_color_percentage(image: cv.Mat) -> dict:
 		"none": none_percentage
 	}
 
+def get_raster_color_percentage(image: cv.Mat, rows: int, cols: int) -> list[list[dict]]:
+	rasters2d = raster_image(image, cols, rows)
+	ret = []
+	for raster1d in rasters2d:
+		new = []
+		for raster in raster1d:
+			color_percentage = get_color_percentage(raster)
+			new.append(color_percentage)
+		ret.append(new)
+	return ret
+

src/feature_vector.py

@@ -1,4 +1,5 @@
 from typing import Any, Self
+import numpy as np
 import os
 import pickle
 
@@ -13,10 +14,50 @@ class FeatureVector:
 		self.concept: Concept = concept
 
 
+	def _get_values_of_feature(self, feature: Feature) -> list[int]:
+		try:
+			feature_data = self.features[feature]
+		except KeyError:
+			print("missing key: ", feature)
+			return [-1]
+
+		ret = []
+		if feature == Feature.OVERALL_COLOR_PERCENTAGE:
+			feature_data: dict
+			for val in feature_data.values():
+				ret.append(val)
+			print(ret)
+			return ret
+		
+		elif feature == Feature.RASTER_COLOR_PERCENTAGE:
+			feature_data: list[list[dict]]
+			
+			for feature_data1d in feature_data:
+				for data in feature_data1d:
+					for val in data.values():
+						ret.append(val)
+			print(ret)
+			return ret
+		
+		elif feature == Feature.CORNERS:
+			#feature_data: int #?
+			return [-1]
+		elif feature == Feature.EDGES:
+			#feature_data: int #?
+			return [-1]
+
+
 	def add_feature(self, key: Feature, value: Any) -> None:
 		self.features.update({key: value})
 
 
+	def get_vector(self) -> list:
+		ret = []
+		for feature in Feature:
+			ret = ret + self._get_values_of_feature(feature)
+		return ret
+
+
 	def get_concept(self) -> Concept:
 		return self.concept
 
@@ -43,4 +84,3 @@ class FeatureVector:
 			self: FeatureVector = pickle.load(read)
 		return self
 
-

src/image_processing.py

@@ -115,16 +115,13 @@ def remove_background(image: cv.Mat, lower_rgb: np.ndarray, upper_rgb: np.ndarra
 
 def raster_image(image: cv.Mat, num_cols: int = 4, num_rows: int = 4) -> list[list[cv.Mat]]:
 	width, height = image.shape[:2]
-	print("w", width, " h", height)
 	rasters = [[0 for x in range(num_rows)] for y in range(num_cols)]
-	print(rasters)
 	for y in range(num_cols):
 		for x in range(num_rows):
 			x1 = int(x * (width/num_rows))
 			y1 = int(y * (height/num_cols))
 			x2 = int((x+1) * (width/num_rows))
 			y2 = int((y+1) * (height/num_cols))
-			print(" x1", x1, " y1", y1, " x2", x2, " y2", y2)
 
 			rasters[x][y] = image[x1:x2, y1:y2]