eval gimp compare pics

desktop_env/evaluators/metrics/__init__.py

@@ -11,7 +11,7 @@ from .table import compare_table
 from .vlc import is_vlc_playing, is_vlc_recordings_folder, is_vlc_fullscreen, compare_images, compare_audios, \
     compare_videos
 
-from .gimp import increase_saturation, decrease_brightness
+from .gimp import increase_saturation, decrease_brightness, check_file_exists, compare_triangle_positions
 from .general import check_csv, check_accessibility_tree, check_list
 from .thunderbird import check_thunderbird_prefs, check_thunderbird_filter
 

desktop_env/evaluators/metrics/gimp.py

@@ -20,6 +20,10 @@ def get_gimp_export_path():
         # Handle the case where the configuration file is not found
         print("GIMP configuration file not found")
         return False
+    
+def check_file_exists(directory, filename):
+    file_path = os.path.join(directory, filename)
+    return 1 if os.path.isfile(file_path) else 0
 
 def increase_saturation(image1_path: str, image2_path: str) -> float:
     def calculate_saturation(image):
@@ -61,6 +65,49 @@ def decrease_brightness(image1_path: str, image2_path: str) -> float:
     brightness2 = calculate_brightness(image2)
 
     return 1 if brightness1 > brightness2 else 0
+import cv2
+import numpy as np
+
+def find_yellow_triangle(image):
+    # Convert the image to RGBA
+    rgba = cv2.cvtColor(image, cv2.COLOR_BGR2RGBA)
+
+    # define range of yellow color in HSV
+    lower_yellow = np.array([0, 0, 0], dtype=np.uint8)
+    upper_yellow = np.array([255, 255, 255], dtype=np.uint8)
+
+    # expand the dimensions of lower and upper yellow to match the image dimensions
+    lower_yellow = np.reshape(lower_yellow, (1, 1, 3))
+    upper_yellow = np.reshape(upper_yellow, (1, 1, 3))
+    # build a mask for the yellow color
+    mask = cv2.inRange(rgba, lower_yellow, upper_yellow)
+
+    # search for contours in the mask
+    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    # choose the largest contour
+    max_contour = max(contours, key=cv2.contourArea)
+
+    # calculate the center of the contour
+    M = cv2.moments(max_contour)
+    cx = int(M['m10'] / M['m00'])
+    cy = int(M['m01'] / M['m00'])
+
+    return cx, cy
+
+def compare_triangle_positions(image1, image2):
+    image1 = cv2.imread(image1, cv2.IMREAD_COLOR)
+    image2 = cv2.imread(image2, cv2.IMREAD_COLOR)
+    # find the center of the yellow triangle in each image
+    cx1, cy1 = find_yellow_triangle(image1)
+    cx2, cy2 = find_yellow_triangle(image2)
+
+    # calculate the distance between the center of the triangle and the center of the image
+    center_distance1 = np.sqrt((cx1 - image1.shape[1] // 2)**2 + (cy1 - image1.shape[0] // 2)**2)
+    center_distance2 = np.sqrt((cx2 - image2.shape[1] // 2)**2 + (cy2 - image2.shape[0] // 2)**2)
+
+    return 1 if center_distance1 > center_distance2 else 0
+
 
 if __name__ == "__main__":
     image1_path = "../Downloads/1.png"